Research on the potential of district
cooling and energy savings in Wuhan,
China
Tsen-Che Chu
Borlänge Energi and Umeå Energi
Master of Science Thesis in Energy Engineering
Institute of Applied Physics and Electronics
Umeå University
(löpnr. som tilldelas)
Abstract
Research on the potential of district cooling and energy savings in Wuhan, China
Tsen-Che Chu
China is facing several serious environmental problems at the present time. Some of the most
polluted cities in the world reside in China. Cities are becoming highly polluted due to the
rapid urbanization and by the high economical growth. With the developing industrialization
comes a higher thirst for electricity, this has lead to an increased numbers of blackout periods
in the country, some industries are even cut off during the peak periods due to insufficient
electricity funds. In China the most common way to produce cold is by using electrical driven
cooling machines. These machines stand for a majority of the electricity used in residential
homes during peak seasons.
The main objective with this master thesis was to find a suitable district cooling technology to
replace the electrical driven air conditioning machines. The benefits should be both
environmental and energy savings. Results obtained should also point out that a potential
investment in district cooling should be financially profitable. The aim with the minor field
study in Wuhan was to acquire important information needed for the objective of this master
thesis. Currently in Wuhan the new standard for cooling is central cooling for newer buildings,
however these systems are still designed to use electricity, produced by coal or oil as fuels.
From the results of this thesis an introduction of a waste incineration plant powering an
absorption chiller machine that produces the cold was considered the best solution for the
given situation and circumstances. The reason for this is the possibility of producing both
electricity and cooling energy to the customers. This solution also brings with energy savings
in form of less used electricity and environmental savings such as reduced CO2 and SO2
emissions. Based on the result the potential of district cooling in Wuhan is very high.
I
摘要
中国武汉市区域集中供冷和能源节约的潜力研究
朱增志
中国目前面临着几个比较严重的环境问题。世界上污染最严重的城市中，就有几座在
中国。由于高度的城市化和经济的快速增长，这些城市的污染问题变得越来越严重。
随着工业化的快速发展，以及随之而来对电力的需求，导致了在中国时常会发生拉闸
限电的情况，某些工业企业甚至也会因为高峰时段的电力供应紧张而导致减产。在中
国，制冷最普遍的方式是用电能驱动的制冷器。在用电高峰时段，这些电器的使用占
了居民住宅用电的一大部分。
本次硕士论文的主要目的是为武汉市找到合适的区域集中供冷技术，以此来代替由电
能驱动的空调。该技术运用的好处就是环保和节约能源。论文得出的结论也指出，区
域集中供冷设备在该地具有盈利的潜力。在武汉调研工作的次要目的是为本次硕士论
文收集重要的信息。目前在武汉，新建的大型建筑中仍然使用中央空调系统。然而，
这些系统的运行仍旧是依靠由煤炭或者汽油产生的电能。
本篇论文的结论给出解决目前情况的最佳方式：引入一座安装了吸收冷却器的垃圾焚
烧厂，将焚烧产生的化学能转化为制冷需要的能量。这样既可以生产电能，同时也可
以为消费者提供冷源。这个方式可以通过减少用电的方式达到节约能源的目的，同时
也可以保护环境，减少二氧化碳和二氧化硫的排放。基于上述论述，在武汉地区推广
使用区域集中供冷的潜力非常高。
II
Referat
Undersökning av potentialen för fjärrkyla och energibesparingar i Wuhan, Kina.
Tsen-Che Chu
Kina står i dagsläget inför en rad allvarliga miljöproblem. Några av världens mest förorenade
städer finns i Kina. Städerna blir alltmer förorenade p.g.a. den snabba urbaniseringen och den
växande ekonomin. I samband med industrins utveckling har behovet av elektricitet blivit allt
större. Detta har lett till ett antal ökade elavbrottsperioder i landet, vissa industrier stängs av
under ”peak” perioderna p.g.a. att elproducenterna inte klarar av att producera tillräckligt. I
Kina är den vanligaste metoden för produktion av kyla eldrivna kylmaskiner vilka står för
majoriteten av elanvändningen hos privat konsumenter under sommarsäsongen.
Målet med detta examensarbete var att hitta en lämplig lösning för fjärrkyla som kan ersätta
de eldrivna kylmaskinerna. Fördelarna bör vara både miljö- och energibesparingar. Resultaten
från detta projekt bör även belysa ekonomiska aspekter för en investering i fjärrkyla. Syftet
med fältstudien i Wuhan utgör viktig informationsinsamling som behövs för att uppnå målet
med examensarbetet. I nuläget finns en ny standard för de nya byggnaderna i Wuhan, dessa
designas för att använda central fjärrkyla, men dessa system använder fortfarande elektricitet,
som framställs med kol och olja som bränsle.
Av resultatet från examensarbetet så kan investering i en avfallsanläggning som driver en
absorptionkylmaskin anses vara den bästa lösningen under de rådande förutsättningarna.
Anledningen till detta är den möjlighet det finns att producera både elektricitet och fjärrkyla
till konsumenterna. Denna lösning medför även energibesparingar i form av mindre
elanvändning och miljöbesparning i form av reducerade utsläpp av CO2 och SO2. Av
resultaten och fältstudien att döma är potential för fjärrkyla väldigt hög i Wuhan.
III
Preface
This master thesis is the final step before achieving a Master of Science degree in Energy
Engineering at Umeå University. I have always wanted to go aboard and study during my
student period in Umeå, and when I saw the opportunity of doing my master thesis in China I
just had to take this opportunity. The time in China has been very instructive and given me
valuable experience that I will take with me into the working life.
Some of the information obtained from the minor field study are strictly confidential and can
therefore not be published. As a precaution for this all the financial input data concerning
investment cost will not be revealed in this thesis. A special appendix containing the financial
input data used in the computer simulation part will be enclosed to Borlänge Energi and Umeå
Energi for internal use only.
I´ve come in contact and worked with several people whom I would like to take the
opportunity to thank for making this master thesis possible and for providing invaluable
information:
From Umeå University, I would like to thank my supervisor Mr. Ronny Östin whom has
given me great advice on how to structure this report in a suitable way. I would also like to
thank Mr. Lars Bäckström for your help in providing me with a research license for the
program What´s Best!
I’m grateful to Borlänge Energi for giving me the opportunity to do my master thesis in
China; it’s been an unforgettable experience. Miss Anna Hagberg you have been one of the
key persons in this project and you have always been very supportive and positive. I
appreciate your help in contacting different departments in Wuhan for the information
research part of this thesis, and also for your kind friendship during my stay in Wuhan. Your
help has truly been invaluable for this project, you have my sincerest gratitude.
Mr. Jörgen Carlsson my supervisor from Umeå Energi, I would like to thank you for
accepting the role as my supervisor and taking time out of your busy schedule for the several
hours spent on video conference meetings with me. You have been a guiding light during this
project, after each video conference I have always been able to see new angles on how to deal
with the problems in this project. I’m very grateful to you for all your help and support.
Wuhan Environmental Protection of Science Research Institute:
Mr. Zhu Zhichao I would like to thank you for taking me into your department and for
providing me with the proper office resources during my stay in Wuhan. Mr. Gong Yuan
thank you for your help in arranging meetings and for your commitment in attaining
information on my behalf. Mrs. Kong Lingli thanks for your help in acquiring an apartment
and taking care of administrative matters for me.
Mr. Xia Kai and Miss Xiong Yu, both of you have helped me so much, all from acting as
interpreters for meetings and doing translation of documents to helping me out with everyday
situations. I appreciate all your help, it’s been truly priceless. I would also like to thank you
both for your friendship it made my stay in Wuhan very pleasant, you two have been very
kind to me.
IV
Mr. Yu Qi, Miss Li Xu, Miss Feng Chanchan, Miss Zhang Wei, Miss Ding Hua, Miss
Cai Yi, Mr. Huang Fei and Mr. Li Pan, even though there´s been a problem with the
language barrier all of you have made me feel very welcome during my stay in Wuhan. You
have been very kind to me and always greeted me with a warm smile. I would like to thank
you all for making my stay in Wuhan very pleasant.
Mr. Yu Xiao, Wuhan Environmental Sanitation Science Research & Design Institute,
you have provided me with valuable information concerning the municipal solid waste
situation, but also priceless information concerning the future plans on waste incineration
plants in Wuhan. I am very grateful for all your help.
Miss Wang Shaohua, Foreign Affairs Office of Wuhan People´s Municipal Government,
I appreciate the effort you have made for me, contacting different key government
departments for setting up meetings. You have been a tremendous help in that aspect.
V
Abbreviations
AC – Air Conditioner
CFB - Circulating Fluidized Bed
CFC – Chloro Fluoro Carbon
COP – Coefficient of Performance
EPSRI – Environmental Protection Sciences Research Institute
H2O - Water
HRSG – Heat Recovery Steam Generator
KTH – Royal Institute of Technology
LiBr - Lithium Bromide
MOHURD - Ministry of Housing and Urban-Rural Development of People’s Republic of
China
MSW – Municipal Solid Waste
Rmb - Renminbi
TES – Thermal Energy Storage
VI
Index
1. Introduction ............................................................................................................................ 3
1.1 Background ...................................................................................................................... 3
1.2 Circumstances .................................................................................................................. 4
1.3 Purpose of the project ....................................................................................................... 5
1.3.1 Project Aim ............................................................................................................... 5
2. Methods .................................................................................................................................. 6
2.1 Literature Study ................................................................................................................ 6
2.2 Minor field study .............................................................................................................. 6
2.3 Simulation and Calculations............................................................................................. 6
3. Energy Quality ....................................................................................................................... 7
4. District Cooling ...................................................................................................................... 8
4.1 District Cooling Benefits .................................................................................................. 9
4.2 Production Techniques ..................................................................................................... 9
4.2.1 Free Cooling .............................................................................................................. 9
4.2.2 Absorption Chiller ..................................................................................................... 9
4.2.3 Cooling From Heat Pumps ...................................................................................... 10
5. The Field Study .................................................................................................................... 11
5.1 Interviews and Meetings with Companies (Visit in Wuhan) ......................................... 11
5.1.1 Situation in Wuhan .................................................................................................. 11
5.1.2 Wuhan Building Energy Efficiency Office ............................................................. 12
5.1.3 Wuhan Environmental Sanitation Science Research & Design Institute ................ 13
5.1.4 Wuhan High Technology Heat Power Plant ........................................................... 14
5.1.4.1 Case Study 1: Wuhan High Technology Heat Power Plant ............................. 14
5.1.5 Wuhan Huaneng Power- Generating CO., LTD ..................................................... 15
5.1.5.1 Case Study 2: Wuhan Huaneng Power- Generating CO., LTD ....................... 15
5.2 District Cooling Technology .......................................................................................... 16
5.2.1 Absorption Chiller Theory ...................................................................................... 16
5.2.2 Working Fluids ........................................................................................................ 18
5.2.3 Coefficient of Performance ..................................................................................... 19
5.2.4 Cooling Water ......................................................................................................... 20
5.2.5 Thermal Energy Storage.......................................................................................... 21
1
5.3 Air Conditioning Appliance ........................................................................................... 22
5.4 Computer Simulation ..................................................................................................... 23
6. Results .................................................................................................................................. 25
6.1 Case Study 1: Wuhan High Technology Heat Power Plant ........................................... 25
6.2 Case Study 2: Wuhan Huaneng Power- Generating CO., LTD 300 and 600 MW ........ 25
6.3 Computer Simulation ..................................................................................................... 27
7. Discussion ............................................................................................................................ 31
7.1 Case Study 1: Wuhan High Technology Heat Power Plant ........................................... 31
7.2 Case Study 2: Wuhan Huaneng Power- Generating CO., LTD ..................................... 31
7.3 Computer Simulation ..................................................................................................... 32
8. Conclusions .......................................................................................................................... 34
9. References ............................................................................................................................ 35
10. Appendix ............................................................................................................................ 38
10.1 Appendix A. Case Study 1: Wuhan High Technology Heat Power Plant ................... 38
10.2 Appendix B. Case Study 2: Wuhan Huaneng Power- Generating CO.,LTD............... 42
10.2.1 Calculation of Huaneng 300 MW ......................................................................... 44
10.2.2 Calculation of Huaneng 600 MW ......................................................................... 47
10.3 Appendix C. Computer Simulation .............................................................................. 50
2
1. Introduction
One of China's major problems is the environmental crisis the country is facing. Due to
China's rapid industrialization the pollution in China has increased substantially with a huge
impact on the environment, illustrated by picture 1. The pollution is not only affecting the
environment negatively but also affecting people’s health. Some of the world’s most polluted
cities are situated in China (World Bank, 2008).
Picture 1. Air pollution in China (Encyclopedia Britannica, 2008).
1.1 Background
The demand for energy in China is increasing rapidly because of the industrialization. Energy
production is one of the largest pollution sectors in China. The largest fuel resource is coal
and 66% of the energy production came from coal in 2003 (Swedish Energy Agency, 2005),
the use of coal is still increasing for every year. Most buildings don’t meet the requirements
when it comes to reducing its use of energy. In today’s China it’s standard to have air
conditioners (AC) in each apartment for both cooling and heating purposes. An image of this
is illustrated in picture 2.
Picture 2. A common view of the buildings in Wuhan with each apartment having the hot coil
of the AC hanging on the outside of the building. This is not very appealing for the façade of
the building. It also drips water regularly from this part of the AC.
3
One of China's largest cities is Wuhan, with a population of approximately 9 million situated
in the province of Hubei (Picture 3). Wuhan is one of the warmest cities in China and known
as one of the three furnaces in China because of the subtropical climate that dominates the
region. Since the standard for comfort cooling in the majority of the old Chinese buildings is
electrical powered AC's, there’s a strong interest in working towards a more sustainable
development within the areas of energy and environment for comfort cooling solutions. One
small step for this development could be district cooling.
Picture 3. A map of China with Wuhan encircled (Lonely Planet, 2008). Wuhan is the capital
of the province Hubei.
1.2 Circumstances
In the year 2000 a co-operation began between Wuhan in China and Borlänge Energi in
Sweden. The two parties decided in 2005 together with IVL, the Swedish Environmental
Research Institute, to co-operate in the fields of sustainable energy production, sustainable
waste management, and establishment of an environmental technology centre, by supplying
Swedish environmental expertise to companies in Wuhan. As a first step for the establishment
of an environmental technology centre in Wuhan, an investigation was made to find out in
which sectors Swedish environmental technology could be established.
In 2006, Umeå Energi AB began a co-operation with both Borlänge Energi and IVL
concerning a co-operation within the fields of exporting knowledge about sustainable waste to
energy solutions. Umeå Energi has also started a co-operation with the Chinese cities Xi'an
and Lanzhou.
4
1.3 Purpose of the project
The main objective with this master thesis was to investigate the potential for district cooling.
An investment in district cooling should be profitable and less energy consuming. Also
highlight on the advantage by using district cooling technology instead of using a separate air
conditioner in each apartment, energy and environmental benefits.
The result of this thesis will be used on a decision basis for a further coherent investment in
district cooling.
1.3.1 Project Aim
The thesis includes the following steps:
•
•
•
•
•
•
•
Selecting the most suitable technology for district cooling.
Engaging Chinese industrial companies that were interested in co-operation for district
cooling systems.
Collecting useful data from the different companies.
Formation and simulation of a district cooling system based on customers need e.g. a
construction company or an industry.
Financial background e.g. the pay-off time and re-current costs.
Environmental benefits with district cooling.
Case study of rebuilding a coal fired power plant to a heat power plant.
5
2. Methods
2.1 Literature Study
Before the field study in China, a literature study was done in Sweden. The preparation
involved different topics like;
•
•
•
•
•
•
Structuring and planning of the project.
Information about Wuhan.
District cooling technologies.
Mapping of potential companies in China for co-operation.
Preparation for possible interviews.
Preparation of a useful data list that were collected from the different companies or
persons.
2.2 Minor field study
During a four months period, a minor field study was carried out in Wuhan. Valuable
information was collected with the help of Environmental Protection Sciences Research
Institute (EPSRI). The department helped with arranging meetings with interesting companies,
with translation of documents and provided translators for the meetings with companies and
power plants.
2.3 Simulation and Calculations
For the simulation and dimensioning of the cooling plant the simulation software What'sBest!
from Lindo Systems Inc was used. The simulation required important data that was provided
by the field study process. Several case studies were performed in the simulation process to
achieve a better understanding on how some of the key variables affect the results. With the
help of the simulation program calculations were made for both the economy and
environmental parts of this thesis.
6
3. Energy Quality
In order to understand the basic idea with this master thesis, one need to understand the term
“energy quality” when comparing electrical driven cooling versus heat driven cooling. From
the world of physics, (Alvarez, 2006), energy can be expressed according to;
Energy = Exergy + Anergy
This expression is used to understand the meaning of energy quality, where exergy is called
high-grade energy and anergy is called low-grade energy.
Taking a power plant as an example (Figure 1), the energy that is used to produce the
electrical energy is called exergy, high-grade energy. Meanwhile the rest of the energy from
the boiler that can’t be used for producing electrical energy is anergy, low-grade energy.
Anergy is the waste heat from the power plant.
Figure 1. Energy flow chart of a power plant (KTH, 2008)1.
Approximately one third of the energy from the boiler is exergy while the rest of it is anergy.
From an energy perspective using electrical energy for cooling is a “waste” of high-grade
energy when there exist cooling technology which can utilize low-grade energy, anergy to
produce the cooling energy for the same purpose.
The electrical energy should instead be used for more important purposes e.g. lighting,
powering electrical appliances and hospitals. Taking advantage of the anergy energy can save
energy and increase a city’s energy efficiency. It will also help reduce the emission of green
house gases.
1
The picture has been modified from its original format.
7
4. District Cooling
District cooling is an environmental friendly solution when it comes to comfort cooling. The
production is centralized, as illustrated by picture 4, at a cooling plant and then distributed by
chilled water, around 6°C, through a network of pipelines to the customers. The return water
to the cooling plant is typically at a temperature around 16°C. Each customer has a heat
exchanger installed in order to transfer heat to the district cooling network.
Picture 4. District cooling plant and network (Umeå Energi, 2008)2.
The need for cooling is caused by several reasons such as, heat radiation from the sun, heat
from heat sources like electrical apparatus in the buildings e.g. heat radiation from humans,
computers and other electrical appliances found in offices.
There is a wide range of customers for district cooling:
•
•
•
•
2
Private consumers who utilize the cooling for the living comfort in their own homes,
when the indoor temperature is unbearable high. District cooling is appropriate to
apartment homes due to the high potential of connecting a large number of customers
in the same building.
Industries that operate heavy machinery that needs cooling for optimal performance.
Companies that have offices that are heated up by their electrical appliances, such as
computer equipments and copy machines have a need for cooling the office space
because warm climate affects people’s ability to perform well.
Public buildings that have a large number of visitors during the day have a large
cooling demand such as shopping centers, museums, civic centers and libraries.
The picture has been modified from its original format.
8
4.1 District Cooling Benefits
District cooling is equally as competitive and beneficial as district heating is for the
environment and the customers.
Benefits of district cooling compared to conventional cooling systems with respect to the
customer (Umeå Energi, 2008):
•
•
•
•
•
•
•
Requires less space than cooling equipments.
No vibration or noise since the production of the cooling energy is at the cooling plant.
Higher energy efficiency since the production is at a larger scale compared to smaller
multiple units producing the same amount of cooling energy.
The repair and maintenance is very low.
District cooling replaces the need of chloro fluoro carbon (CFC) as refrigerants.
Very competitive price for district cooling.
Lower investment cost for customers.
4.2 Production Techniques
There are several ways to produce district cooling e.g.:
•
•
•
Free cooling.
Absorption chillers.
Cooling from heat pumps.
In the decision of which technique is most suitable, one has to take in consideration the local
conditions residing in the actual area. The combination of the two should be that the cooling
energy produced is the most profitable method.
In the next section different cooling techniques are described. In the theory section the most
suitable technique for the situation in Wuhan is chosen and described more detailed.
4.2.1 Free Cooling
Free cooling means utilizing the surrounding nature’s cooling. The most common way for
free cooling is to use cold water from lakes and oceans. The cold water is pumped into the
district cooling plant; the district cooling water becomes cooled by a heat exchanger using the
cold lake or ocean water. The water is then released back to the recipient (Svensk Fjärrvärme,
2008).
Another way to use free cooling is to store a large amount of snow or ice in a thermal storage
system, during the winter. And during the summer use it for cooling purposes. This solution is
applied in Sundsvall, Sweden for cooling of a hospital (Svensk Fjärrvärme, 2008).
4.2.2 Absorption Chiller
One way to produce cooling energy is to use waste heat from industries or district heat. The
absorption chiller machine uses heat to produce cold. Although this machine isn’t very
efficient, it’s a very common solution to produce district cooling (Svensk Fjärrvärme, 2008).
9
This method is profitable if the absorption machine is powered by cheap heat that comes from
industries or a district heat plant. The key condition is to have accesses to a large amount of
cheap heat to make it profitable (Svensk Fjärrvärme, 2008).
4.2.3 Cooling From Heat Pumps
Cooling energy can also be produced by heat pumps. The main component is a compressor
and the heat pump process is the same as a refrigerator. The compressor is powered by
electricity. The process can produce two units of cooling energy for each electric unit it
disposes of (Svensk Fjärrvärme, 2008).
Heat pumps are e.g. applied on sewer water where the heat is extracted from the water, this
leads to that the sewer water gets cooled off. This waste cooling can then be used for district
cooling (Svensk Fjärrvärme, 2008).
10
5. The Field Study
5.1 Interviews and Meetings with Companies (Visit in Wuhan)
This section contains information obtained from the interviews and meetings with companies
and persons active within the field of energy. Obtained documents from the department
EPSRI with information that are valuable for this thesis was translated to English and
summarized in this section.
5.1.1 Situation in Wuhan
Depending on who are asked if they know or have ever heard of district cooling, the answers
are widely spread in Wuhan, everything from district cooling does not exist in Wuhan to its
too expensive. However in the district called “high technology development zone” in Wuhan
there is one company who provides district cooling due to request of the Wuhan government.
The company is called Wuhan High Technology Heat Power Plant.
Older buildings in Wuhan don’t have joint cooling system installed so the tenants have their
own AC installed; the number of AC’s in the apartments/premises depends on how wealthy
the tenants are. The average number of AC’s for residential homes in Wuhan is 1.45; this
number is higher than the average national number (Mr. Tong, 2008).
The newer buildings in Wuhan have central air conditioning systems installed, however the
major energy source for the central air conditioning systems is electricity (Li et al. 2006).
These new buildings include shopping malls, public buildings and office blocks.
The operational time of the AC’s for an average residential home in Wuhan is around 11
hours from 08:00 PM - 07:00 AM. Public buildings have around 9 hours ranging from 08:30
AM - 05:30 PM, and shopping malls have 12 hours of operational time from 09:30 AM 09:30 PM (Mr. Tong, 2008).
Blackouts are very common in China; planned blackouts are carried out due to extreme heat
climate in Wuhan. In Wuhan the planned blackouts are implemented one by one for each
district during July and August. The government takes precautions in ensuring the residential
home electricity supply during the peak hours, by limiting the power supply to the industry
during the nights (Mr. Tong, 2008).
Most of the district cooling plants in China seem to be placed in Chinese cities close to the
Chinese coast e.g. Beijing, Guangzhou, Shanghai and Shenzhen. The technology used for
district cooling in China are electrical driven, heat driven absorption chiller machines and free
cooling plants (Hui et al. 2007). At the moment district cooling technology in China is not as
developed as in Sweden or other European countries, even though the development still is at
its initial stage efforts are being made to take the development further. Several coal fired heat
power plants are being rebuilt for co-generation for cooling production across China (Hui et al.
2007).
11
5.1.2 Wuhan Building Energy Efficiency Office
Concerning future ideas about district cooling in Wuhan, the government doesn’t have any
suggestions for district cooling during the next 3-5 years, perhaps in the future it will be
included (Mr. Tong, 2008). The reasons for this are the following:
•
•
•
•
The high investment cost concerning the pipeline network.
There are hardly any investors interested because of the long pay-back time.
A main concern is that district cooling would have difficulty generating an income.
The attitude towards district cooling and the local perception that other electrical
driven cooling systems are more efficient and economical.
Saving energy has become a big concern throughout the whole country and the department of
Ministry of Housing and Urban-Rural Development of People’s Republic of China
(MOHURD) are in charge of making the policies concerning energy saving goals (Mr. Tong,
2008). Examples of energy saving policies made by the MOHURD are as following:
•
•
•
All new building with less than 12 floors should integrate a solar energy system to the
building.
A policy to all new large public buildings and office blocks try to save 50% energy
and that the Wuhan government should try to reach 65% energy saving in 2009.
The MOHURD has established a special fund to encourage local governments to
spread and implement the energy saving policies made by MOHURD.
The directive of energy savings in today’s Wuhan is focused mainly on energy conservation
in buildings.
The government encourages real estate development companies to build central cooling and
heating systems based on ground heat source pumps and also to integrate solar power systems
into the building’s design to save energy (Mr. Tong, 2008).
When it comes to energy resources other than coal, the Wuhan government wants to promote
energy sources like solar power, wind power and nuclear power. The government of the
Hubei province has started a nuclear power plant in Xiang Ning 80 km south of Wuhan in
2008 (Mr. Tong, 2008).
12
5.1.3 Wuhan Environmental Sanitation Science Research & Design Institute
There are currently no waste incinerations plants in Wuhan, however there are plans on
building five plants. Three of the plants are designed to use the circulating fluidized bed (CFB)
technology with a total capacity of 3500 municipal solid waste (MSW) ton/day together, and
the other two are designed to use the stoker technology with a total capacity of 2000 MSW
ton/day together (Mr. Yu, 2008). A more detailed description of each plant is compiled in
table 1.
Table 1. Specification of each incineration plant planned to be built in Wuhan.
Estimated
Turbines
MSW Capacity
Plant Type
Operational Time
Circulating Fluidized Bed 1
1000 ton/day
2 x 12 MW
7000 hours
Circulating Fluidized Bed 2
1000 ton/day
2 x 12 MW
7000 hours
Circulating Fluidized Bed 3
1500 ton/day
3 x 12 MW
7000 hours
Stoker 1
1000 ton/day
2 x 12 MW
8000 hours
Stoker 2
1000 ton/day
2 x 12 MW
8000 hours
In 2007 the MSW production in Wuhan was 5800 ton/day; this production has an annual
increase by 3-5%. The average heating value of the MSW in Wuhan is 5.44 MJ/kg; the
heating value has a variation between 3.76-8.37 MJ/kg. In China the average heating value of
MSW is 5 MJ/kg (Nie, 2008). The reasons for these low heating values are because of the
high humidity in Wuhan during the summer season and also due to the high content of water
coming from the household kitchen waste. The water content in the MSW has a variation
between 40-60%.
The two stoker plants will have a MSW pretreatment system. The MSW used will be dried in
bunkers for 3-5 days before being incinerated. This pretreatment system can increase the
MSW heating value by 10-20%. The water recovered from the MSW will then be treated at a
water plant. For the three CFB plants there won’t be any MSW storage instead the MSW will
be crushed into pieces with a diameter less than 15 cm before being incinerated (Mr. Yu,
2008).
Supplementary fuel will be used because of the low heating value of the MSW. The fuel
supplement is coal. By regulation of the Ministry of Environmental Protection China the coal
mass mixed with the MSW should not exceed 20% of the input fuel mix weight (Mr. Yu,
2008).
The incineration plants will receive a gate fee for taking care of the MSW. The gate fee is 60
Rmb3/ton. For the electricity they will receive 0.405 Rmb/kWh from the state grid and also
0.25 Rmb/kWh from the government (Mr. Yu, 2008).
From earlier experiences of CFB plants in China the planned CFB incinerators have 1000
hours less estimated operational time than the stoker incinerators. The main reason behind this
is because the CFB incinerators have a higher demand of repair time than the Stoker grate
incinerators. The need for longer repair time is caused by the combustion technique and the
status of the MSW used in CFB incinerators. These effects shortens the life span of the
incinerators material; some parts of the stove need to be improved (Mr. Yu, 2008).
3
The Chinese currency is renminbi, Rmb.
13
The CFB technology used in China is provided by Zheijiang University and Beijing China
Sciences General Energy-Envier. Co Ltd (Nie, 2008).
5.1.4 Wuhan High Technology Heat Power Plant
The Wuhan High Technology Heat Power Plant was built in 1998, and provides heat to more
than 40 factories in the high technology development zone of Wuhan. The plant has already
replaced several small industrial boilers at different factories. The service area for this plant
has a radius of 8 km, which almost covers the entire high technology development zone.
By request from the Wuhan government this plant provides both cooling and heating for
schools, hospitals and residential areas. The plant has a double effect steam fired absorption
chiller installed from the Chinese company Broad. The used steam has a temperature of
300°C and a pressure of 0.8-1.3 MPa. The capacity of this double effect absorption chiller is
9304 kW and the lifetime of this machine is approximately 25 years (Mr. Wang, 2008).
The plant has two boilers installed with a capacity of 120 ton coal/h each, and two 25 MW
turbines for each boiler. The primary fuel in the plant is coal and occasionally diesel oil is
used for co-firing the boilers. The thermal efficiency of the plant is 91%, and the annual
energy supply from the plant is 260 GWh (Mr. Wang, 2008).
The Wuhan High Technology Heat Power Plant is a unique plant; it’s the only plant in Wuhan
that supplies electricity, steam and cooling. There are four other plants in the Wuhan district
that can supply both electricity and steam to customers (Mr. Wang, 2008).
Information given by this company concerning investment cost of pipelines and absorption
chiller machine was used in the computer simulation part of this thesis.
5.1.4.1 Case Study 1: Wuhan High Technology Heat Power Plant
This is a study to see if there is potential to extract more energy from this plant by
implementing a heat recovery steam generator (HRSG) to utilize the energy from the flue
gases without affecting the plants electricity production, since the electricity is a high income
source for the plant.
Calculations were made on how much energy can be extracted from the flue gases, financial
questions on investment cost of a HRSG and income generated by this HRSG. The study
shows weather if it would be beneficial or not to extract the flue gas energy. For theory used
for this case study see Appendix A.
14
5.1.5 Wuhan Huaneng Power- Generating CO., LTD
The location of the Wuhan Huaneng power generation company is very convenient since it’s
located on the north shore of the Yangtze River, close to Jingguang railroad and 20 km east of
the urban areas. The location opens up for easier land and sea transportation. The company is
one of the two biggest power suppliers in the Wuhan area (Mrs. Liu, 2008).
This plant has two systems, one 300 MW output turbine and the other one is a 600 MW
output turbine. In 2007 the annual use of coal for the plant was 5 million tons. Operational
time for the systems is 6500 hours annually. Information acquired from this plant has been
used for a minor case study calculation as a part of this thesis (Mrs. Liu, 2008).
5.1.5.1 Case Study 2: Wuhan Huaneng Power- Generating CO., LTD
The case study involved a rebuild of an already existing coal fired power plant in China. The
main idea is to take advantage of the waste heat from this plant using it to produce cooling
energy, converting it into a heat power plant. The reason for this is to try to compare how
much cooling energy that can be produced by the waste heat versus how much cooling energy
the electricity that is sacrificed for heat production can produce; this is called the specific
electricity loss factor. Both of the power plants cycles were used for this case study.
From a thermodynamic aspect this comparison would point out if the heat driven cooling
from a heat and cooling power plant would be preferred (Figure 2), because this option results
in less electricity loss in the national and regional power grid. Of course on a decision basis
one has to consider other aspects in addition to the thermodynamic aspect e.g. the consumer
basis in the surrounding area.
Figure 2. Illustration of the two scenarios, electrical driven cooling versus heat driven cooling.
The price for the cooling energy has been set by the electricity price divided by the average
COP factor in an average AC machine. The reason for this is to be able to make a fair
comparison between electrical driven and heat driven cooling. Another reason is to be able to
have a competitive price for the district cooling, and also to attract customers to switch from
electrical driven to heat driven cooling.
For theory and input data used for this case study see Appendix B.
15
5.2 District Cooling Technology
The most suitable choice of district cooling technology in this case was an absorption chiller
plant solution powered by waste heat from a waste incineration plant. The reason for this is
that a large number of Chinese cities are facing problems with disposal of the MSW. The
problem is the lack of space for new landfills in the country. Currently there are some
municipalities that have great difficulty finding appropriate locations for landfill sites. Even
though a significant investment cost and operational cost are involved with the incineration of
MSW, the MSW incineration role is increasing significantly in the MSW management in
China (Nie, 2008).
5.2.1 Absorption Chiller Theory
The single effect absorption process is founded by two fundamental circumstances, first of all
it’s the absorbent solutions ability to absorb the refrigerant vapor and the second is that the
refrigerant boils at a very low temperature during high pressure. What makes the cycle work
is the strong affinity4 these substances have for each other (York International, 2008).
The whole absorption cycle has four main components; generator, condenser, evaporator and
the absorber (Figure 3). Other components are electrical pumps for keeping the refrigerant
and absorbent circulating inside the cycle, and also a heat exchanger. The single effect
absorption system described in this chapter is a system using lithium bromide (LiBr) as
absorbent and water (H2O) as refrigerant (York International, 2008).
Figure 3. Schematic sketch over the absorption cycle process (Rydstrand et al., 2004)5.
4
5
Affinity – Chemical attraction force between different substances.
The picture has been modified from its original format.
16
The cooling energy to the district cooling water is produced in the evaporator, where the
refrigerant is sprayed out at low pressure and absorbs the heat energy from the incoming
district cooling water. This process vaporizes the refrigerant and the vapor is then transported
to the absorber (York International, 2008).
In the absorber, the concentrated absorbent solution in this case, LiBr is sprayed out and
absorbs the refrigerant vapor H2O. Thermal energy is released by this absorption process
(Figure 4). The mixture of these two is then condensed by the incoming cooling water to a
diluted solution LiBr + H2O (York International, 2008).
Figure 4. Absorption process (Herold et al., 1996).
The diluted solution is then pumped through the heat exchanger to the generator, where heat
energy is added by the waste heat. The added thermal energy makes the solution vaporize,
which means a desorption process occurs (Figure 5). The process separates the refrigerant and
the absorbent into a concentrated solution and refrigerant vapor. The solution is then pumped
back to the absorber through the heat exchanger, while the vapor is transferred to the
condenser (York International, 2008).
Figure 5. Desorption process (Herold et al., 1996).
17
The function of the heat exchanger is to increase the efficiency of the cycle by helping to cool
down the concentrated solution and heat up the weak solution (York International, 2008).
The refrigerant vapor from the generator is then condensed by the cooling water. The
condensed refrigerant is then transferred back to the evaporator. With that the entire
absorption cycle is closed (York International, 2008).
5.2.2 Working Fluids
There are many combinations of working fluids that have been considered for absorption
machines e.g. water/sulfuric acid, ammonia/water, water/lithium bromide and water/sodium
hydroxide. The most conventional absorption fluids are ammonia/water and water/lithium
bromide. The reason for this is that one has to take in to consideration several properties of
the fluids when choosing combination of the working fluids, a compilation has been made of
the properties for the two most conventional combinations in table 2. As mentioned before
one of the key criteria is the high affinity between the absorbent and the refrigerant. To find a
mixture that meets all the criteria for the desirable properties is not possible, some
compromises have to be made (Herold et al., 1996).
Table 2. Compilation of the property criteria’s for the most conventional absorption working
fluids (Herold et al., 1996).
Refrigerant/Absorbent
Water/Lithium
Ammonia/Water
Property
Bromide
Refrigerant
Good
Excellent
High latent heat6
Too high
Too low
Moderate vapor pressure
Excellent
Limited application
Low freezing temperature
7
Good
Good
Low viscosity
Absorbent
Poor
Excellent
Low vapor pressure
Good
Good
Low viscosity
Mixture
Excellent
Limited application
No solid phase
Poor
Good
Low toxicity
Good
Good
High affinity between refrigerant and
absorbent
As one can see from table 2 the water/lithium bromide is more suitable for air conditioning
because of the solid phase of water and the fluid mixture and low toxicity, while the
ammonia/water combination is more suitable for cooling refrigerators and freezers because it
can achieve lower temperature without having any problems with solid phase changes.
LiBr is chosen as the absorbent due to its great ability to absorb water vapor. And water is
chosen as the refrigerant because of its ability to boil at low pressure and temperature.
6
7
Latent Heat – Heat energy released or absorbed during a substance phase change.
Viscosity – Measurement of a fluids resistance to flow.
18
5.2.3 Coefficient of Performance
The coefficient of performance (COP) is a term used for measuring the efficiency of the
absorption chiller. The COP factor for the absorption chiller (Martin et al., 2005) can be
expressed as
COP =
Where
Qc
Wnet ,in
Qc
W net ,in
Desired cooling energy
Required input energy
The single effect absorption chillers have a COP approximately around 0.6-0.8 of an ideal 1
(Martin et al., 2005). The waste heat that is available during the summer to power this
absorption chiller, is usually lower than the temperature the absorption chiller is designed for
which is 120°C. The reason for this is because of the reduced heat demand from customer
(Martin et al., 2005). This affects the absorption chillers COP negatively (Figure 6).
Figure 6. Variation of COP with the heat energy temperature for an absorption chiller
machine designed for 120°C (Martin et al., 2005).
To be able to use lower temperature modifications are needed to maintain a COP factor
around 0.6-0.8. Researchers at the royal institute of technology (KTH) in Stockholm have
designed a low temperature driven absorption chiller (Figure 7).
The main difference from the conventional single effect absorption machine is that the
evaporator and condenser part is smaller if the generator has the same capacity as the
conventional absorption chiller using 120°C heat energy. This design also needs more pumps
to be able to increase the velocity of heat and mass transfers. The two extra heat exchangers
are solely used for heat transfer. The KTH design of low temperature driven absorption chiller
is not mass-produced, it’s tailor-made depending on its application area (Rydstrand et al.,
2004).
19
Figure 7. KTH design of low temperature driven absorption chiller (Rydstrand et al., 2004)8.
5.2.4 Cooling Water
The absorption chiller machine needs cooling because; the machine is charged with heat from
the heat power plant and it also absorbs heat from the district cooling system. If low
temperature water is available from a nearby lake or river, then it would be optimal to utilize
this water for external cooling of the absorption chiller machine (Martin et al., 2005). A
temperature below 24°C is preferred; otherwise the economy of the absorption chiller will be
affected (Martin et al., 2005). If the plant is nearby a lake or river this cooling solution is the
most economical one, since it only requires a pump system and a heat exchanger that cools
the cooling water circulating inside the machine.
In cases where no lakes or rivers are nearby, the only option is a cooling tower. This solution
is more expensive, since the size of the heat exchanger is dependent on the temperature of the
cooling water (Martin et al., 2005).
In this thesis the simulation plant was assumed to be located nearby one of the rivers in
Wuhan. According to EPSRI the average water temperature in Changjiang River is 19.8°C.
8
The picture has been modified from its original format.
20
5.2.5 Thermal Energy Storage
Thermal energy storage (TES) is needed to support the cooling plant when peak periods of the
day occur, otherwise the cooling plant may experience difficulties to supply enough cooling
energy to the customers. Cooling energy is stored during the night and periods, when usage is
low and then discharged when the peak periods occurs. The TES unit gives the cooling plant a
more stable production. In this thesis a water tank was used as the TES unit. The TES unit
also reduces the needed installed capacity of the cooling plant.
When it comes to applications of cooling the temperature difference between the supply and
return line is relative small. This leads to a demand of a large volume of water to store the
cooling energy. The storage capacity for water is approximately 9 kWh/m3 (Setterwall et al.,
2003).
The energy storage capacity of a water tank (Fällström, 2006) can be expressed as
Q = ρ ⋅ Cp,H 2 O ⋅ V ⋅ ΔT
Where
Cp,H 2 O
V
ΔT
Density of water
Specific heat capacity
Volume
Temperature difference
21
Eq 1
[kg/m3 ]
[J/kg ⋅ K]
[𝑚𝑚3 ]
[°𝐶𝐶]
5.3 Air Conditioning Appliance
There are several different designs of the AC machine, but the most dominating one in China
is the one called split structure type. This means that the AC is divided into an indoor part and
outdoor part (Lin et al., 2006). The range of the COP factor for the AC machines varies
between approximately 2-3.5 depending on design. The average COP factor in China is
approximately 2.4 (Mr. Tong, 2008). In 2009 efforts are being made in China to increase the
efficiency of these machines by regulation e.g. setting a minimum COP factor depending on
cooling capacity (Table 3). Studies have been made on how much energy and CO2 emissions
this new standard for AC machines will save for China.
Table 3. The minimum standard of COP factors for AC machines in China 2009 (Lin et al.,
2006).
Rated Cooling Capacity (CC) W COP W/W
Category
2.9
Single-package
CC ≤ 4500
3.2
Split
4500 < CC ≤ 7100
3.1
7100 < CC ≤ 14000
3.0
The AC machine is basically an electrical driven heat pump. Its main components are
compressor, condenser, evaporator and an expansion valve (Figure 8).
Figure 8. Schematic sketch of an air conditioner.
In the compressor the refrigerant vapor is compressed and heated up by process. The
compressed vapor is then transferred to the condenser. In the condenser the refrigerant vapor
is condensed, this process makes the refrigerant give up its thermal energy to the outside
environment. The function of the expansion valve is to control the amount of liquid
refrigerant that flows through to the low pressure part of the cycle. The refrigerant liquid is
then evaporated in the evaporator; this process makes the refrigerant absorb thermal heat.
With that the entire heat pump cycle is closed (McDowell, 2006).
22
5.4 Computer Simulation
The computer simulation model was designed in the program What'sBest! 9.0.3.2 from Lindo
Systems, Inc. What's Best! is an add on software for Microsoft Excel.
The purpose of the simulation model was to simulate the operation of a heat power plant with
a CFB incinerator powering a low temperature absorption chiller machine (Figure 9). The
main objective with this simulation was to optimize the parameters; capacity of the CFB
incinerator, capacity of the absorption chiller machine and the TES unit while maximizing the
annual net profit for this plant. The main income sources are electricity sale, cooling sale and
gate fee for taking care of the MSW.
Figure 9. An overview scheme of the system for this planned simulation.
Restrictions were made in the simulation model by using boundary conditions, as a
reassurance that the size of the CFB incinerator and TES unit are realistic to what is possible
to build.
Input data
The cooling need for an area in Wuhan has been approximated because the data for electricity
use in a district in Wuhan has not been attained. The parameters used to approximate the
cooling need were provided by the Wuhan Building Energy Efficiency Office. The cooling
area used in this simulation is 512 600 m2. For more detailed overview of the area model see
Appendix C.
Under the circumstances that this simulation involved an incinerator plant and a residential
area that does not exist, setting an appropriate length of the pipeline network was difficult. In
discussions with Umeå Energi a length of 25 km was chosen as a reasonable pipeline length
when considering the size of the residential area.
23
Financial investment costs and other economic issues involving a CFB incinerator plant have
been attained; these numbers are strictly confidential and can therefore not be revealed for the
public.
From the Wuhan High Technology Heat Power Plant, financial investment cost and economy
for an absorption chiller machine have been attained. Fuel properties of the coal and price
have also been attained from this company.
Since the average heating value of the Wuhan MSW is only 5.44 MJ/kg, there is a need for a
supplementary fuel that is mixed together with the MSW to increase the heating value
otherwise the fuel will not ignite. The heating value of the fuel mix needs to be over 6 MJ/kJ.
The MSW was mixed with coal; the percentage coal cannot exceed 20% of the fuel mix
weight according to regulations by Ministry of Environmental Protection China.
Analysis
The net present value (NPV) was used for analyzing the economics of this simulation. The
NPV analysis shows weather an investment in this kind of plant will be profitable or not.
A more detailed analysis of the key numbers was analyzed to increase the understanding on
how this affects the fallout for this computer simulation. The parameters that were analyzed
were the investment price of the CFB incinerator, COP factor of the absorption chiller
machine and also the heating value of the MSW.
An environmental analysis on how much CO2 and SO2 a CFB plant can save compared to a
coal fired power plant. A calculation was also made on how much CO2 and SO2 is emitted
from the absorption chiller production of cooling energy versus the emission from the cooling
energy equivalent of electricity production from a coal fired power plant.
24
6. Results
6.1 Case Study 1: Wuhan High Technology Heat Power Plant
The potential of extracting heat from the flue gases is 1.18 MW. This would generate an
annual heat production of 14.42 GWh. The heat production 14.42 GWh would generate an
income of 2.27 million Rmb. If the heat is used to produce cold the generated income would
be 1.63 million Rmb. For calculation details see Appendix A.
6.2 Case Study 2: Wuhan Huaneng Power- Generating CO., LTD 300 and 600
MW
The results of the calculations for both the 300 and 600 MW are compiled in the table 4.
Table 4. Calculation results for the 300 and 600 MW cycles.
300 MW
Specific electricity loss [%]
13
Electricity income loss [Rmb]
128 520 284
Potential cooling capacity [MW]
217
Potential cooling income [Rmb]
293 865 030
Potential net profit [Rmb]
165 344 746
Potential net profit including tax [Rmb]
140 543 034
600 MW
15
290 947 426
389
526 852 810
235 905 383
200 519 575
The need of extracting maximum heat from this process may not be necessary depending on
the required cooling need from the consumers. An analysis has been made for different heat
extractions as a function of the potential cooling net profit (Figure 10 and Figure 11).
Analysis of Huaneng 300 MW
200 000 000,00
150 000 000,00
R
m
b
100 000 000,00
Potential Profit
50 000 000,00
0,00
-50 000 000,00
139,50 186,10 232,60 279,10 325,70 372,20 401,80
Heat Extraction [MW]
Figure 10. Analysis of the heat extraction from the already existing 300 MW power plant
cycle as a function of the potential cooling net profit.
25
Analysis of Huaneng 600 MW
300 000 000,00
250 000 000,00
200 000 000,00
R
m
b
150 000 000,00
100 000 000,00
Potential Profit
50 000 000,00
0,00
-50 000 000,00
330,95 401,87 472,79 543,71 614,63 685,55 720,48
-100 000 000,00
Heat Extraction [MW]
Figure 11. Analysis of the heat extraction from the already existing 600 MW power plant
cycle as a function of the potential cooling net profit.
More heat can be extracted if needed from these systems at a higher temperature, by
extracting the steam from a higher pressure.
26
6.3 Computer Simulation
The standard simulation model contains two boundary conditions one for the TES unit and the
other one for CFB incinerator. The boundary conditions were implemented to avoid
unrealistic sizes of these units.
The investment cost for the whole plant is 424.4 million Rmb, the size of the TES unit is 8
000 m3, CFB incinerator is 100 MW and the absorption chiller machine is 17.47 MW. The
annual profit for this plant would be 40.5 million Rmb (Table 5).
Table 5. A compilation of the simulation result of the basic simulation model.
Simulations
Thermal Storage System
8000 m3
CFB Dimension Effect
100 MW
ABS Chiller Dimension Effect
17.47 MW
Total Investment Cost
424 373 474 Rmb
Annual Fixed Cost
21 978 504 Rmb
Annual Variable Cost
101 688 540 Rmb
Annual Total Income
164 168 060 Rmb
Annual Total Profit Earnings
40 501 015 Rmb
Input parameters for the standard simulation model can be found in Appendix C.
According to the NPV analysis the breakeven point is when the cost of capital value is
approximately 8% (Figure 12).
Cost of Capital
400 000 000,00
N
P
V
300 000 000,00
[
0,00
R
m
b
200 000 000,00
100 000 000,00
-100 000 000,00
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20
]
-200 000 000,00
-300 000 000,00
Cost of Capital [%]
Figure 12. NPV analysis on how the cost of capital affects the NPV value.
A cost of capital of 8.76% was used in the standard simulation model, which gives a NPV of
−48 million Rmb. An investment is not feasible for this project with a cost of capital of 8.76%.
27
The environmental analysis of the CO2 and SO2 emission shows that this simulation plant
could save the environment 341 865 tones CO2 and 2 917 tones SO2 compared to a coal fired
power plant (Table 6).
Table 6. A compilation of emission rates of CO2 and SO2 from the CFB incinerator plant,
coal fired power plant and AC machines.
CFB Incinerator Vs.
CO2 ton SO2 ton Calculation
Coal Fired Power Plant
R
1 Emission CFB Incinerator
107 039
584
2 Emission Coal Fired Power Plant
413 215
3 222
3 Emission AC Electricity
35 689
278
Annual Environmental Saving [ton]
341 865
2 917 R2+R3-R1
An analysis of the parameters of investment cost of CFB incinerator, COP factor of the
absorption chiller and the heating value of the MSW is compared with the standard simulation
models results. These analyses are based on a cost of capital of 8.76%.
The investment cost for a CFB incinerator was analyzed to see how this affects the NPV
analysis (Figure 13).
Analysis of CFB Incinerator Investment Cost
0,00
N
P
V
[
R
m
b
-200 000 000,00
X1
X2
X3
-400 000 000,00
-600 000 000,00
-800 000 000,00
]
-1 000 000 000,00
-1 200 000 000,00
Investment Cost [Rmb]
Figure 13. An analysis of how an increase of the CFB incinerator investment cost affect the
NPV.
The analysis shows that the NPV for the standard simulation model is very sensitive to an
increase of the investment price of the CFB incinerator. An increase of the investment price
from X1 to X2 increases the infeasibility of this project.
28
The COP factor of the absorption chiller machine was analyzed to see how this affects the
NPV analysis (Figure 14).
Analysis of COP factor
-40 000 000,00
N
P
V
[
R
m
b
50
-42 000 000,00
60
70
80
-44 000 000,00
-46 000 000,00
-48 000 000,00
-50 000 000,00
]
-52 000 000,00
-54 000 000,00
COP factor [%]
Figure 14. An analysis on how the COP factor of the absorption chiller machine affects the
NPV.
From the analysis a change in the COP factor from 0.5-0.8 affects the NPV by 8 million Rmb.
The COP factor used in the standard simulation model is 0.6.
Changing the COP factor affects the size of the absorption chiller machine (Figure 15).
Analysis of COP factor
25
20
[
M
W
15
]
10
5
0
50
60
70
80
COP factor [%]
Figure 15. An analysis on how the COP factor of the absorption chiller machine affects the
size of the absorption chiller machine.
A change of the average COP factor also affects the size of the absorption chiller. A range
from 0.5-0.8 in COP factor changes the needed size from approximately 21-13 MW of the
absorption chiller machine. The dimensioned size of the absorption chiller machine in the
standard simulation model was 17.47 MW.
29
The average heating value for the Wuhan MSW was analyzed to see how its heating value
affects the NPV analysis (Figure 16).
Analysis of Heating Value
N
P
V
[
R
m
b
]
200 000 000,00
150 000 000,00
100 000 000,00
50 000 000,00
0,00
-50 000 000,00
-100 000 000,00
-150 000 000,00
-200 000 000,00
-250 000 000,00
-300 000 000,00
4,00
5,00
6,00
7,00
8,00
Heating Value of MSW [MJ/kg]
Figure 16. An analysis on how the MSW heating value affects the NPV.
A variation of the MSW heating value from 4-8 MJ/kg affects the NPV value from
approximately −230-160 million Rmb. The average heating value should not be lower than
approximately 6 MJ/kg for this investment to profitable. The average heating value used in
the standard simulation model was 5.44 MJ/kg.
30
7. Discussion
7.1 Case Study 1: Wuhan High Technology Heat Power Plant
The generated income is quite low considering the investment cost of installing HRSG in an
already built power plant. So in this case study it is not beneficial in the aspect of the
company to install the HRSG considering the investment cost of a HRSG unit. Since the plant
already produces electricity combined with heat and cooling production, the plant itself seems
to be optimized in this aspect of utilizing the low quality waste heat for heating and cooling
purposes.
7.2 Case Study 2: Wuhan Huaneng Power- Generating CO., LTD
From the calculation results, the Huaneng 300 MW and 600 MW cycles could generate
together a potential net profit of 400 million Rmb annually by producing district cooling.
Eventual investments in a rebuild of the power plant into a heat power plant with cooling
production have a good potential of being executed, of course one have to take in
consideration the investment cost of building a cooling plant and drawing the pipelines.
Drawing a new pipeline network stands for the majority of the investment cost.
Please keep in mind that the economy calculations are roughly calculated based for an entire
year, assuming that all of the cooling production is sold even though the fact that the
residential need for cooling is only during seven months of the year. A more thorough and
detailed calculation would be advised for more exact financial numbers.
Depending on the cooling need of the surrounding residential area, the plant may not even
need to rebuild both power cycles, one of them might be enough.
From a company aspect a possible rebuild of the power plant could very well be an option,
based on the results mentioned in the text above, benefits for the company will be an
increased annual profit, reduced electricity peaks during days and nights, a more stable and
even production line, better possibilities on providing electricity and satisfying the electricity
need to the state grid. This is very important because an insufficient electricity production
results in; some industrial factories are cut off during the night to ensure electricity
availability for residential AC’s. For the industrial factories to have a production stop could
have a negative effect on their business and also slow down their economical growth.
In the aspect of the society the district cooling system is a more reliable system, because it is
not competing with industrial factories for electricity. Residents don’t have to worry about
unplanned or planned blackouts. The government of China doesn’t have to plan blackouts
throughout different districts, which also increase the living comfort across the country.
Converting over to district cooling also benefits the environment by saving tones of CO2.
Another aspect is also the reduced power need this rebuild brings with it; the reduced power
consumption could also mean a reduced usage of fossil fuel.
This case study involved a low temperature driven absorption chiller. However using a double
effect steam driven absorption chiller in this case study, the size of the cooling machine can
be reduced because of a higher COP factor, average COP factor for a steam driven double
effect chiller machine is around 1.2.
31
7.3 Computer Simulation
A district cooling plant is competitive and more environmental friendly compared to a coal
fired power plant, powering electrical driven cooling machines. The emission calculations are
based on that the plants don’t have any flue gas cleaning systems; if a cleaning system is
present the emission rates will be different. The standard computer simulation model is
limited by the boundary conditions similar to Umeå Energi and the preliminary planned CFB
incinerator plant in Wuhan so that benchmarking with them would be easier.
According to the results from the standard simulation model, an investment for this kind of
plant is not feasible with a cost of capital of 8.76%. This result means that the cost of capital
needs to be lower to make this investment feasible; this however might have negative effect
on the investors. The key factor to solve the infeasibility is the gate fee. The gate fee plays a
significant role for waste incineration plants economy; compared to Sweden’s gate fee 7001200 Kr9/ton Wuhan’s gate fee 60 Rmb/ton is very low. A raise of the gate fee in Wuhan
could increase the prospects in overall of investing in more waste incineration plants.
Benchmarking the investment cost of the CFB incinerator obtained from Wuhan with Umeå
Energi, the investment cost seems very low even by Chinese standards. The analysis on how
the investment cost of the CFB incinerator affects the investment prospects; shows that if the
investment cost is increased, the plants profitability is affected negatively. If the investment
cost is higher than the one obtained from Wuhan, then the key factor to solve this problem is
the gate fee, as mentioned above for the cost of capital infeasibility problem.
Another possible option to solve the infeasibility problem could be heat production during the
winter period; this can improve the economy of this simulation model. However the possible
income that the heat can generate is entirely dependent on how great the heating need is
during the winter in Wuhan.
The COP factor plays an important role for the economy of the plant. Operating with a high
average COP factor for the absorption chiller machine will require an optimized automatic
control system. Maintaining a high COP factor can also reduce the needed installed capacity
of the absorption chiller machine.
From the analysis of the average heating value of the Wuhan MSW, it shows that the heating
value plays a significant role and affects the NPV negatively the lower it gets. The biggest
issue with the Wuhan MSW is the high moisture level, which is caused by the kitchen waste
and the high humidity during summer periods. An effective drying pretreatment of the MSW
is necessary to increase the heating value. Also changing the coal level from 15-20% for the
fuel mix could be an option, then one has to keep in mind that the fuel properties changes in
the aspect of heating value, CO2 and SO2 emission rates.
There are several uncertainties in the computer simulation model. The approximated cooling
need for the constructed residential area; the numbers used for calculation of the cooling need
have a large interval which creates an instability factor in the cooling need calculations. A
constant average heating value has been used while in reality this will vary. The COP factor is
also kept constant during the simulation process but in reality the COP factor can be lower or
higher depending on the operational circumstances. The thermal efficiency of the furnace and
9
Swedish currency is kronor, Kr.
32
mechanical efficiency for the turbine and generator are set by the average standard for these
parts of a CFB incinerator plant. The expression “lost in translation” also creates an important
instability factor that is worth mentioning, when translating from Chinese to English and
English to Chinese. Information can be lost during translation.
Taking the uncertainties in consideration the purpose with the computer simulation was to
illustrate the benefits of an investment of district cooling plant that is powered by a waste
incineration plant. Considering the economy part of this simulation, the investment price for a
Chinese CFB incinerator needs to be further investigated to be able to conclude weather the
investment price used in this thesis is realistic or not by Chinese measurements.
33
8. Conclusions
When comparing the emissions only from the district cooling production from a CFB
incinerator plant with the emissions from the electricity equivalent from a coal fired power
plant used by AC machines, the potential annual saving of CO2 is approximately 35 700 tons
and of SO2 is 278 ton, this is the environmental benefit saving. The electricity equivalent of
the produced district cooling is 18.2 GWh. This amount of electricity is the energy saving
benefit by using the district cooling technology. This electricity is gained for the national and
regional power grid and will help reducing blackouts.
The reason for choosing a waste incineration plant powering an absorption chiller plant as the
most appropriate was the following reasons:
•
•
•
•
•
Production of electricity from the incineration plant.
Waste is used as fuel, taking the pressure of the currently overloaded landfills.
Production of waste heat, which can be used for heating or cooling purposes.
The cooling production from the cooling plant reduces the use of electricity during
summer periods.
The possible heating production from the incineration plant could reduce the use of
electricity during winter periods.
As mentioned before in chapter 5.1.2 the biggest bottlenecks for district cooling is the
pipeline cost, the pay-back time of the investment and the low income district cooling
generates. In this case the government needs to take initiative, by setting an example that
investments in district cooling pays off and is a better choice for the environment.
There are no plans that involve district cooling from the local government in Wuhan for the
next 5 years; hopefully by then China has taken the step from being a developing country to a
developed country. And as a developed country take the responsibility for the country’s CO2
emission. Taking responsibility for CO2 emissions could very well open up for district cooling
as a new construction standard due to its environmental benefits.
Another way to open the way for district cooling could be the government of National and
Local Development & Reform Commission that are in charge of setting standards in China.
However contacting and convincing this government to set a new standard for cooling could
be very difficult. Hopefully together with the fact that China will soon become a developed
country this government will set a new standard that involves district cooling.
The potential for district cooling in Wuhan is very high, because of the following reasons:
•
•
•
•
The subtropical climate in Wuhan that brings with a wide range of customers that
have a large cooling need.
The newer buildings in Wuhan are designed to have a centralized cooling system.
Access to cheap waste heat from the waste incinerator plants that are planned on
being built in Wuhan.
The city of Wuhan has some experience from district cooling operations, from the
Wuhan High Technology Heat Power Plant.
34
9. References
Alvarez, H. (2006) Energiteknik del 2. Studentlitteratur AB
Bergström, U. (2005) Kinas växande energibehov. Swedish Energy Agency
Available at Internet:
http://www.swedishenergyagency.se/web/biblshop.nsf/FilAtkomst/ET2005_6W.pdf/$FILE/E
T2005_6W.pdf?OpenElement
Accessed: 25/6/2008
Ekstrand, Sofia., Wänn, Annicka. (2007) Waste incineration plant in Wuhan, China – A
feasibility study.
Uppsala University
Encyclopedia Britannica. (2008) Photographer: Mark Henley
Available at Internet: http://student.britannica.com/eb/art-92262/Air-pollution-in-Liaoningprovince-China
Accessed: 1/9/2008
Environmental Protection Sciences Research Institute (EPSRI). (2008) Personal Contact
Fällström, S, (2006) Absorptionskylmaskin för Gålnäs industriområde. Umeå University
Herold, K E., Radermacher, R., Klien, S A. (1996) Absorption Chillers and Heat Pumps.
Crc Press
ISBN: 0-8493-9427-9
Hui, R1., Xu, Q2., Xu, W3. (2007) The Existing Condition and Development of the District
Cooling System in China. Heating/Cooling Energy Saving No.3 [In Chinese]
1
Xi'an University of Architecture and Technology
2
Beijing Institute of Civil Engineering and Architecture
3
China Institute of Urban Construction
KTH. (2008) Tillämpad Termodynamik – Föreläsning 8.
Available at Internet: http://www.energy.kth.se/COURSES/4a1112/FILES/F8.pdf
Accessed: 30/8/2008
Li, Y., Zhang, C. (2006) The Current Situation and Energy-saving Analysis of the Central Air
Conditioning System in the Typical Public Buildings of Wuhan. [In Chinese]
Building Energy & Environment Vol. 24 No. 4 Aug 2006.38~41
School of Urban Construction, Wuhan University of Science and Technology
Lin, J., Rosenquist, G. (2006) China Cools with Tighter RAC Standard.
Lawrence Berkeley National Lab
Available at Internet: http://mail.mtprog.com/CD_Layout/Day_2_22.06.06/16151815/ID164_Lin_final.pdf
Accessed: 30/8/2008
35
Lonely Planet. (2008) Lonely Planet Maps: Map of China.
Available at Internet: http://www.lonelyplanet.com/maps/asia/china/
Accessed: 18/8/2008
Martin, V., Setterwall, F., Andersson, M.,(2005) Kylprocessers Design i Fjärrvärmesystem
Forskning och Utveckling │2005:128
ISSN 1401-9264
McDowall, R. (2006) Fundamentals of HVAC Systems.
Elsevier, Oxford, United Kingdom.
ISBN: 0-12-372497-X
Mr. Tong. (2008) Wuhan Building Energy Efficiency Office - Interview with Mr. Tong.
Mr. Wang. (2008) Wuhan High Technology Heat Power Plant - Interview with Mr. Wang.
Mr. Yu. (2008) Wuhan Environmental Sanitation Science Research & Design Institute Interview with Mr. Yu.
Mrs. Liu. (2008) Wuhan Huaneng Power Generation Company – Interview with Mrs. Liu.
Nie, Y., (2008) Development and prospects of municipal solid waste (MSW) incineration in
China.
Department of Environmental Science and Engineering, Tsinghua University, Beijing 100084,
China. Higher Education Press and Springer-Verlag 2008
Process Systems Enterprise Limited (PSE). (2009) Figure - Coal fired power plant Schematic
Available at Internet:
http://www.psenterprise.com/consulting/r_and_d/images/vpdm_coal_fired.jpg
Rydstrand, M., Martin, V., Westermark, M. (2004) Värmedriven Kyla .
Forskning och Utveckling │ 2004:112
Setterwall, F., Andersen, B. (2003) Kylager i Befintligt Kylnät.
Forskning och Utveckling │ 2003:102
ISSN 1402-5191
Umeå Energi. (2008) Fjärrkylans Fördelar.
Available at Internet: http://www.umeaenergi.se/default.asp?id=1462
Accessed: 12/7/2008
World Bank. (2008) China Quick Facts.
Available at Internet:
http://web.worldbank.org/WBSITE/EXTERNAL/COUNTRIES/EASTASIAPACIFICEXT/C
HINAEXTN/0,,contentMDK:20680895~isCURL:Y~menuPK:318976~pagePK:141137~piPK
:141127~theSitePK:318950,00.html
Accessed: 25/6/2008
36
York International. (2008) YIA Single-Effect Absorption Chillers: Steam and Hot Water
Chillers.
Available at Internet: http://www.york.com/products/esg/YorkEngDocs/776.pdf
Accessed: 25/8/2008
37
10. Appendix
10.1 Appendix A. Case Study 1: Wuhan High Technology Heat Power Plant
The plant before the rebuild is illustrated in figure A 1.
Figure A 1. Scheme over the Wuhan High Technology Heat Power Plant cycle.
The plant after the rebuild is illustrated in figure A 2.
Figure A 2. Scheme over the Wuhan High Technology Heat Power Plant cycle with an HRSG
unit added to the plant.
38
The equation needed for this calculation is the following:
Where
Q
𝑄𝑄 = G ∙ CP ∙ (T1 − T2 )
Power output
[W]
G
Mass flow rate of flue gas
�
Cp
Specific heat of flue gas
T1
T2
Ingoing temperature to HRSG
Outgoing temperature from HRSG
Eq A 1
[
m 3n
s
J
�
m 3n ∙K
]
[K]
[K]
Input data
T1 was known from the Wuhan High Technology Heat Power Plant. T2 was chosen to 403 K
due to fact that if gas is cooled lower than that, the dew point will be reached, condensation of
the gas will begin and water droplets will be formed. The water droplets will cause corrosion
in the furnace. A loss factor of 10% is used for transition losses.
The following proximate analysis (Table A 1) and ultimate analysis (Table A 2) of Chinese
coal for the Hubei province has been provided by the EPSRI and is needed as input data for
the fuel template:
Table A 1. The proximate analysis of the coal used in Wuhan.
Proximate Analysis Percent %
Moisture
2.52
Ash
18.14
Volatile
15.75
Table A 2. The ultimate analysis of the coal used in Wuhan.
Ultimate Analysis Percent %
C
64.48
H
4.18
O
0.96
N
9.12
S
0.61
39
A print screen of the fuel template (Figure A 3):
Combustion calculation based on 1 kg Chinese coal
Syrebehov
Molvikt Analys Antal
mol
mol
g
g
12,01
644,8
53,69
53,69
C
2,02
41,8
20,69
10,35
H2**
28
91,2
3,26 N2**
32
9,6
0,30
– 0,30
O2**
32,1
6,1
0,19
0,19
S
181,4 Aska
974,9
63,93
Totalt torrt
18,0
25,1
1,39 F
1000,0
Totalt bränsle
Råkväve i luft (3,77)*syrebehovet
241,19
Torr luft, lot
305,11
Fukt i luft Φ
0,02
6,10
Stökiometriskt luftbehov, loTS
311,22
Torra stökiometriska rökgaser, got
298,33
Totala stökiometriska rökgaser för TS,
goTS
326,51
Torrt luftöverskott
0,00
Fukt i luftöverskott
0,00
Torra rökgaser, gt
298,33
Totala rökgaser, g (gTS)
326,51
Torrt luftöverskott ltTs
311,22 Halt på torr gas
Halt på totala
gaser
Ämne
H2O
Rökgaser (mol/kg bränsle)
SO2 Ar
N2
CO2
53,69
O2
20,69
3,26
0,19
1,39
0,09 238,26
2,84
6,10
28,19
-
53,78 241,52
0,19
2,84
53,78 241,52
0,00
0,00
0,19
2,84
0,00
0,00
0,00
28,19
53,78 241,52 0,19 2,84 0,00
53,78 241,52 0,19 2,84 0,00
0,180 0,810 0,001 0,010 0,000
0,086
0,165
-
0,740 0,001 0,009 0,000
Figure A 3. The cell marked with blue is the percentage of H2O in the flue gas and the grey
one is the percentage of CO2 in the flue gas.
The specific heat was calculated by using 8.6% H2O and 16.5% CO2 in the following equation:
𝑥𝑥 =
H2 O %
CO2 %
x was used to read of the specific heat value Cp from the diagram “Gas- och
förbränningsdata”.
𝑥𝑥 =
8.6%
= 0.52
16.5%
From the diagram (Figure A 4), see below. Cp = 1425
40
Figure A 4. Print screen of the diagram where the specific heat of the flue gases can be
determined. CP is determined to be 1425 J/m3n*K. The drawn redline shows the process of
determining CP.
Calculation of the possible heat extraction from the flue gases by using equation A 1 is
𝑄𝑄 = 41.67 �
J
m3n
� ∙ 1425 � 3 � ∙ (423[K] − 403[K]) = 1.18 𝑀𝑀𝑀𝑀
s
mn ∙ K
With an operational time of 6000 hours for each boiler the potential of heat production from
the HRSG is the following:
𝑃𝑃 = 1.18 ∙ 106 [𝑊𝑊] ∙ 6000[ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜] ∙ 2[𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏] = 14.42 𝐺𝐺𝐺𝐺ℎ
The price for heat given from the company was 0.16 Rmb/kWh, an annual income would be:
𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻 = 14.42 ∙ 106 [𝑘𝑘𝑘𝑘ℎ] ∙ 0.16 �
𝑅𝑅𝑅𝑅𝑅𝑅
� = 2.27 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑅𝑅𝑅𝑅𝑅𝑅
𝑘𝑘𝑘𝑘ℎ
If the heat would be used for district cooling, the annual income would be:
𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 = 14.42 ∙ 106 [𝑘𝑘𝑘𝑘ℎ] ∙ 0.6[𝐶𝐶𝐶𝐶𝐶𝐶] ∙ 0.9[𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿] ∙ 0.21 �
= 1.63 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑅𝑅𝑅𝑅𝑅𝑅
41
𝑅𝑅𝑅𝑅𝑅𝑅
�
𝑘𝑘𝑘𝑘ℎ
10.2 Appendix B. Case Study 2: Wuhan Huaneng Power- Generating CO.,LTD
All the theory and equations needed and used for this case study is presented below:
The specific electricity loss is expressed as the following:
Where
Z
𝑃𝑃𝑚𝑚𝑚𝑚𝑚𝑚
𝑃𝑃𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄
𝑄𝑄𝑚𝑚𝑚𝑚𝑚𝑚
𝑍𝑍 =
𝑃𝑃𝑚𝑚𝑚𝑚𝑚𝑚 −𝑃𝑃𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄
Eq B 1
𝑄𝑄𝑚𝑚𝑚𝑚𝑚𝑚
Specific electricity loss
Max production of electricity capacity,
power plant
Max production of electricity capacity,
heat power plant
Max heat production, heat power plant
[%]
[W]
[W]
[W]
Power production equations
The power production equations for the all the turbines and different cases can be expressed
as the following:
Where
𝑃𝑃𝐻𝐻𝐻𝐻𝐻𝐻 = 𝑀𝑀1 ∙ (ℎ1 − ℎ2 ) + 𝑀𝑀2 ∙ (ℎ2 − ℎ3 )
𝑃𝑃𝐼𝐼𝐼𝐼𝐼𝐼 = 𝑀𝑀5 ∙ (ℎ5 − ℎ6 ) + … + 𝑀𝑀9 ∙ (ℎ9 − ℎ10 )
𝑃𝑃𝐿𝐿𝐿𝐿𝐿𝐿 = 𝑀𝑀11 ∙ (ℎ10 − ℎ11 ) + … + 𝑀𝑀12 ∙ (ℎ12 − ℎ13 )
Eq B 2
Eq B 3
Eq B 4
𝑃𝑃𝐻𝐻𝐻𝐻𝐻𝐻
𝑃𝑃𝐼𝐼𝐼𝐼𝐼𝐼
𝑃𝑃𝐻𝐻𝐻𝐻𝐻𝐻
𝑃𝑃𝑚𝑚𝑚𝑚𝑚𝑚
𝑃𝑃𝐼𝐼𝐼𝐼𝐼𝐼,𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄
𝑃𝑃𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄
𝑄𝑄𝑚𝑚𝑚𝑚𝑚𝑚
𝜂𝜂𝑚𝑚𝑚𝑚𝑚𝑚 ℎ𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎
𝑀𝑀𝑥𝑥
ℎ𝑏𝑏,𝑥𝑥 − ℎ𝑎𝑎,𝑥𝑥
[W]
[W]
[W]
[W]
[W]
[W]
[W]
[%]
[kg/s]
[kJ/kg]
𝑃𝑃𝑚𝑚𝑚𝑚𝑚𝑚 = 𝜂𝜂𝑚𝑚𝑚𝑚𝑚𝑚 ℎ𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 ∙ (𝑃𝑃𝐻𝐻𝐻𝐻𝐻𝐻 + 𝑃𝑃𝐼𝐼𝐼𝐼𝐼𝐼 + 𝑃𝑃𝐿𝐿𝐿𝐿𝐿𝐿 )
𝑃𝑃𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄 = 𝜂𝜂𝑚𝑚𝑚𝑚𝑚𝑚 ℎ𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 ∙ �𝑃𝑃𝐻𝐻𝐻𝐻𝐻𝐻 + 𝑃𝑃𝐼𝐼𝐼𝐼𝐼𝐼,𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄 �
𝑃𝑃𝐿𝐿𝐿𝐿𝐿𝐿,𝑄𝑄𝑄𝑄𝑄𝑄𝑄𝑄 = 𝑀𝑀10 ∙ (ℎ10 − ℎ11 ) + … + 𝑀𝑀12 ∙ (ℎ12 − ℎ14 )
𝑄𝑄𝑚𝑚𝑚𝑚𝑚𝑚 = 𝑀𝑀14 ∙ (ℎ14 − ℎ15 )
Power production from high pressure turbine
Power production from intermediate pressure turbine
Power production from low pressure turbine
Maximum power production, no heat production
Power production, with heat production
Power production, with heat production
Maximum heat production
Efficiency of turbine and generator together
Mass flow rate of the steam
Enthalpy difference for one turbine step
Eq B 5
Eq B 6
Eq B 7
Eq B 8
Cooling energy equations
Cooling energy production from heat production is expressed by:
Where
𝑄𝑄𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 ,𝐷𝐷𝐷𝐷
𝑄𝑄𝑚𝑚𝑚𝑚𝑚𝑚
𝐶𝐶𝐶𝐶𝐶𝐶𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴
L
𝑄𝑄𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 ,𝐷𝐷𝐷𝐷 = 𝑄𝑄𝑚𝑚𝑚𝑚𝑚𝑚 ⋅ 𝐶𝐶𝐶𝐶𝐶𝐶𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴
𝐶𝐶ℎ𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
𝐶𝐶ℎ𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
∙ 𝐿𝐿
Cooling energy production
Maximum heat production
Efficiency of absorption chiller
Loss factor, set to 10%
42
Eq B 9
[W]
[W]
[%]
[%]
Cooling energy production from the specific electricity loss of Z is expressed as:
Where
𝑄𝑄𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 ,𝐴𝐴𝐴𝐴
Z
𝑃𝑃𝑚𝑚𝑚𝑚𝑚𝑚
𝑄𝑄𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 ,𝐴𝐴𝐴𝐴 = 𝑍𝑍 ⋅ 𝑃𝑃𝑚𝑚𝑚𝑚𝑚𝑚 ⋅ 𝐶𝐶𝐶𝐶𝐶𝐶𝐴𝐴𝐴𝐴𝐴𝐴 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶
𝐶𝐶𝐶𝐶𝐶𝐶𝐴𝐴𝐴𝐴𝐴𝐴 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶
Cooling energy production
from AC machines
Specific electricity loss
Maximum power production,
no heat production
Efficiency of AC machine
Eq B 10
[W]
[%]
[W]
[%]
Economy equations
The potential income that can be generated by starting to produce cooling energy is expressed
as:
Where
𝐼𝐼𝐷𝐷𝐷𝐷
𝑄𝑄𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 ,𝐷𝐷𝐷𝐷
𝐶𝐶𝐶𝐶𝐶𝐶𝐷𝐷𝐷𝐷
𝐶𝐶𝐶𝐶𝐶𝐶𝐴𝐴𝐴𝐴
E
𝐼𝐼𝐷𝐷𝐷𝐷 = 𝑄𝑄𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 ,𝐷𝐷𝐷𝐷 ∙
𝐶𝐶𝐶𝐶𝐶𝐶 𝐷𝐷𝐷𝐷
𝐶𝐶𝐶𝐶𝐶𝐶 𝐴𝐴𝐴𝐴
∙ 𝐸𝐸
Income generated by the district cooling
Cooling energy, district cooling
COP factor, district cooling
COP factor, AC
Electricity price
Eq B 11
[Rmb]
[kWh]
[%]
[%]
[Rmb/kWh]
The electricity income is reduced when producing district cooling energy is expressed as the
following:
𝐼𝐼𝐸𝐸 = 𝑍𝑍 ⋅ 𝑃𝑃𝑚𝑚𝑚𝑚𝑚𝑚 ⋅ 𝐸𝐸
Eq B 12
Where
𝐼𝐼𝐸𝐸
Z
𝑃𝑃𝑚𝑚𝑚𝑚𝑚𝑚
E
Income generated by the electricity of Z
Specific electricity loss
Max production of electricity capacity,
power plant
Electricity price
[Rmb]
[%]
[kWh]
[Rmb/kWh]
The net potential profit when producing district cooling energy can be expressed as the
following:
𝑁𝑁𝑁𝑁𝑁𝑁 = 𝑇𝑇𝑇𝑇𝑇𝑇 ∙ (𝐼𝐼𝐷𝐷𝐷𝐷 − 𝐼𝐼𝐸𝐸 )
Eq B 13
Where
𝑁𝑁𝑁𝑁𝑁𝑁
Tax
𝐼𝐼𝐷𝐷𝐷𝐷
𝐼𝐼𝐸𝐸
Net potential profit
Tax on the sale, tax is 15.4%
Income generated by the district cooling
Income generated by the electricity of Z
43
[Rmb]
[%]
[Rmb]
[Rmb]
10.2.1 Calculation of Huaneng 300 MW:
Plant scheme before the rebuild illustrated in figure B 1.
Figure B 1. Scheme over the Huaneng 300 MW cycle (Process Systems Enterprise Limited,
2009)10.
Plant scheme after the rebuild illustrated in figure B 2.
Figure B 2. Scheme over the Huaneng 300 MW cycle with heat production for the district
cooling plant (Process Systems Enterprise Limited, 2009)10.
10
The picture has been modified from its original format.
44
Input data:
The tables below contains important input data used for the calculations
Table B 1. Important data from the coal fired power plant cycle, used for calculation.
T [Celsius] P [Bar] h [kJ/kg] M [kg/s]
300 MW
1 Before HPT
538
166.7
3 410.00
284.73
2 Drainage 1 HPT
60
3 146.50
268.73
3 Drainage 2 HPT
32
3 019.00
253.73
4 Before Re-heater after HPT
32
3 019.00
253.73
5 After Re-heater before IPT
538
32
3 540.00
253.73
6 Drainage 1 IPT
24
3 472.00
242.73
7 Drainage 2 IPT
20
3 421.00
232.73
8 Drainage 3 IPT
15
3 357.25
222.73
9 Drainage 4 IPT
12
3 272.25
212.73
10 After IPT, before LPT
337
7.8
3 200.00
212.73
11 Drainage 1 LPT
6
3 123.00
192.73
12 Drainage 2 LPT
3
2 978.00
172.73
13 After IPT, before CC
32
0.05
2 404.75
172.73
If Maximum Heat is extracted
14 Heat Extraction
1
2 745.60
172.73
15 Warm Condenser
1
419.04
172.73
16 After IPT, before CC
32
0.05
2 404.75
0
Table B 2. Price information and efficiency of cooling machines.
Input data: power plant,
price, and COP factors
COP-factor AC
2.40 Chapter 5.3
COP-factor Absorption Chiller
0.60 Chapter 5.2.3
Electricity Price
0.50 Rmb/kWh, Chapter 5.1.5
Cooling Price
0.21 Rmb/kWh Chapter 5.1.5.1
Operational Time
6 500 Hours, Chapter 5.1.5
Table B 3. Assumptions are made due to lack of information from the power plant.
Assumptions
Isentropic Efficiency
HPT
0.85
Isentropic Efficiency
IPT
0.85
Isentropic Efficiency
LPT
0.85
Mechanical Efficiency * Generator Efficiency
0.90
45
In the tables below the calculation process is shown together with the results of each
calculation.
Table B 4. Calculation process and results of the power calculations.
kW
Calculation of Huaneng 300 MW Cycle
HPT
109 289.43
IPT
91 535.00
LPT
130 569.73
Pmax
299 083.23
Calculation of Heat Power Plant Rebuild Cycle
Max Electricity Production Without Heat
Production
Pmax
299 083.23
Electricity from LPT With Heat Production
LPT,qmax
71 694.71
Max Electricity Production With Heat Production
Pqmax
245 948.53
Heat Production From LPT
Qmax
401 866.71
Key Numbers for Heat Power Plant
Power to Heat Ratio
α
0.61
Specific Electricity Loss
Z
0.13
Table B 5. Calculation process and results of the economy calculations.
Equations
Economy Calculations
Z -> Electricity -> Cooling Capacity
94.91 MW B 10
Z -> Electricity Income Loss
128 520 284 Rmb B 12
Qmax -> Cooling Capacity
Qmax -> Cooling Income
217.01 MW
293 865 030 Rmb
B9
B 11
Potential Profit
165 344 746 Rmb
B 11 - B 12
Potential Profit After Tax
140 543 034 Rmb
B 13
46
Equations
B2
B3
B4
B5
Equations
B5
B7
B6
B8
Equations
B 6/ B 8
B1
10.2.2 Calculation of Huaneng 600 MW:
Plant scheme before the rebuild illustrated in figure B 4.
Figure B 3. Scheme over the Huaneng 300 MW cycle (Process Systems Enterprise Limited,
2009)11.
Plant scheme after the rebuild illustrated in figure B 4.
Figure B 4. Scheme over the Huaneng 600 MW cycle with heat production for the district
cooling plant (Process Systems Enterprise Limited, 2009)11.
11
The picture has been modified from its original format.
47
Input data:
The tables below contains important input data used for the calculations
Table B 6. Important data from the coal fired power plant cycle, used for calculation.
M LPT1 M LPT2
M
h
P
T
[kg/s]
[Celsius] [Bar] [kJ/kg] [kg/s] [kg/s]
600 MW
1 Before HPT
566 242
3 420 527.78
2 Drainage 1 HPT
60
3 071.5 503.78
3 Drainage 2 HPT
41.1 2 999.25 479.78
4 Before Re-heater after HPT
41.1 2 999.25 479.78
5 After Re-heater before IPT
566 41.1
3 610 479.78
6 Drainage 1 IPT
29
3 516.5 456.78
7 Drainage 2 IPT
22
3 431.5 433.78
8 Drainage 3 IPT
16
3 346.5 409.78
9 Drainage 4 IPT
14
3 304 384.78
10 After IPT, before LPT
9 3 210.50 384.78
192.39
192.39
11 Drainage 1 LPT
3.5
2987
172.39
172.39
12 Drainage 2 LPT
2.4 2914.75
152.39
152.39
13 After IPT, before CC
32 0.054
2 392
152.39
152.39
If Maximum Heat is
extracted
14 Heat Extraction
1
2783
152.39
152.39
15 Warm Condenser
1
419.04
152.39
152.39
16 After IPT, before CC
32 0.05 2 362.25
0
0
Table B 7. Price information and efficiency of cooling machines.
Input data: power plant,
price, and COP factors
COP-factor AC
2.40 Chapter 5.3
COP-factor Absorption
Chiller
0.60 Chapter 5.2.3
Electricity Price
0.50 Rmb/kWh, Chapter 5.1.5
Rmb/kWh Chapter
Cooling Price
0.21 5.1.5.1
Operational Time
6 500 Hours
Table B 8. Assumptions are made due to lack of information from the power plant.
Assumptions
Isentropic Efficiency
HPT
0.85
Isentropic Efficiency
IPT
0.85
Isentropic Efficiency
LPT
0.85
Mechanical Efficiency * Generator Efficiency
0.90
48
In the tables below the calculation process is show together with the results of each
calculation.
Table B 9. Calculation process and results of the power calculations.
kW
Calculation Huaneng 600MW
HPT
220 328.50
IPT
201 075.56
LPT1
121 551.89
LPT2
121 551.89
Pmax
599 718.32
Calculation Heat Power Plant Rebuild
Only Electricity Production
Pmax
599 718.32
Electricity from LPT1 With Heat Production LPT1_Q
61 967.83
Electricity from LPT2 With Heat Production LPT2_Q
61 967.83
Pqmax
492 169.10
Heat Production From LPT1
Qmax_LPT1 360 241.24
Heat Production From LPT2
Qmax_LPT2 360 241.24
Qmax_tot
720 482.48
Key Numbers for Heat Power Plant
Power to Heat Ratio
α
0.68
Specific Electricity Loss
Z
0.15
Equations
B2
B3
B4
B4
B5
Equations
B5
B7
B7
B6
B8
B8
B 8*2
Equations
B 6/(B 8*2)
B1
Table B 10. Calculation process and results of the economy calculations.
Equations
Economy Calculations
Z -> Electricity -> Cooling Capacity
214.85 MW B 10
Z -> Electricity Income Loss
290 947 426 Rmb B 12
Qmax -> Cooling Capacity
Qmax -> Cooling Income
389.06 MW
526 852 810 Rmb
B9
B 11
Potential Profit
235 905 383 Rmb
B 11 - B 12
Potential Profit After Tax
200 519 575 Rmb
B 13
49
10.3 Appendix C. Computer Simulation
Approximation of a Residential Area
Input data from the Wuhan Building Energy Efficiency Office is used to calculate the cooling
need for the average Chinese buildings (Table C 1).
Table C 1. Input data used for modeling the residential area that is used for the computer
simulation
Shopping
Office
Calculation
Mall
Apartment Room
R Parameters
Electricity Need
1 [kWh/m2 * annually]
19
25
73.74
2 Average COP
2.4
2.4
2.4
2
3 Size [m ]
50
25
5 000
4 Operational Time Each Day [h]
11
9
12
Cooling Need
5 [kWh/m2 * annually]
45,6
60
176.96
R1*R2
6 Cooling Period [Number of Days]
214
214
214
7 Total Operational Time [h]
2 354
1 926
2 568
R4*R6
8 Annual Cooling Need [kWh/year]
2 280
1 500
884 880
R3*R5
A daily cycle load is constructed with the data above; the daily cooling need for the area is
125.87 MWh, this daily cooling energy need is then matched with the annual cooling energy
need. The total area of the residential area is 512 600 m2 (Table C 2).
Table C 2. Layout of the constructed residential area.
Apartment Office Shopping Mall
Layout
Room/Floor
16
24
Floors/Building
27
27
Rooms/Building
432
648
Number of Buildings
16
10
1
2
Total Size [m ]
512 600
Approximation of Cooling Need
In order to get a variation in the cooling need for each day, a scale factor is constructed for
each day by using the average temperature of each day divided with 15°C. Then the daily
cooling need is multiplied with the scale factor for each day (Table C 3).
The idea behind this is to get a non laminar production line for the absorption chiller; this
would also reflect the real cooling energy better. The reference temperature of 15°C (Ekstand
et al., 2007) is used as a temperature limit for when the real cooling need begins in an average
Chinese home.
50
Table C 3. Average temperature, scale factor and cooling need during the hot summer period
of Wuhan.
Temp °C
Rescaled
Normal
Cooling
Cooling
Scale
Need [MWh]
Need [kWh]
Mean Low factor
High
Date
2007-04-01
20.00 16.67 13.89
1.11
44 823.18
49.80
2007-04-02
15.00 12.22 10.00
0.81
44 823.18
36.52
2007-04-03
15.56 10.56 5.56
0.70
44 823.18
31.54
2007-04-04
15.56 11.67 7.78
0.78
44 823.18
34.86
2007-04-05
18.89 14.44 10.56
0.96
44 823.18
43.16
2007-04-06
20.56 15.56 10.56
1.04
44 823.18
46.48
2007-04-07
21.67 16.67 11.67
1.11
44 823.18
49.80
2007-04-08
23.89 18.33 12.78
1.22
44 823.18
54.78
2007-04-09
21.67 17.78 13.89
1.19
44 823.18
53.12
2007-04-10
23.89 18.89 13.89
1.26
44 823.18
56.44
2007-04-11
26.67 21.11 15.00
1.41
44 823.18
63.08
2007-04-12
27.78 21.67 15.56
1.44
44 823.18
64.74
2007-04-13
27.78 22.78 17.78
1.52
44 823.18
68.06
2007-04-14
25.00 21.11 16.67
1.41
44 823.18
63.08
2007-04-15
25.56 21.11 16.67
1.41
44 823.18
63.08
2007-04-16
21.67 17.22 12.78
1.15
44 823.18
51.46
2007-04-17
16.67 13.33 10.56
0.89
44 823.18
39.84
2007-04-18
21.67 15.56 10.00
1.04
44 823.18
46.48
2007-04-19
27.78 20.00 12.78
1.33
44 823.18
59.76
2007-04-20
28.89 22.78 16.67
1.52
44 823.18
68.06
2007-04-21
28.89 24.44 20.00
1.63
44 823.18
73.05
2007-04-22
21.67 18.33 13.89
1.22
44 823.18
54.78
2007-04-23
20.56 16.67 12.78
1.11
44 823.18
49.80
2007-04-24
21.67 16.67 11.67
1.11
44 823.18
49.80
2007-04-25
25.56 20.00 13.89
1.33
44 823.18
59.76
2007-04-26
23.89 20.00 16.67
1.33
44 823.18
59.76
2007-04-27
23.89 19.44 15.00
1.30
44 823.18
58.10
2007-04-28
23.89 21.11 17.78
1.41
44 823.18
63.08
2007-04-29
17.78 16.67 15.00
1.11
44 823.18
49.80
2007-04-30
25.00 19.44 13.89
1.30
44 823.18
58.10
2007-05-01
27.78 21.67 15.56
1.44
44 823.18
64.74
2007-05-02
30.00 22.22 15.00
1.48
44 823.18
66.40
2007-05-03
28.89 24.44 20.56
1.63
44 823.18
73.05
2007-05-04
30.00 25.00 20.00
1.67
44 823.18
74.71
2007-05-05
31.67 25.56 18.89
1.70
44 823.18
76.37
2007-05-06
28.89 22.78 16.67
1.52
44 823.18
68.06
2007-05-07
30.56 24.44 17.78
1.63
44 823.18
73.05
2007-05-08
33.89 27.22 20.56
1.81
44 823.18
81.35
2007-05-09
25.56 22.78 20.00
1.52
44 823.18
68.06
51
2007-05-10
2007-05-11
2007-05-12
2007-05-13
2007-05-14
2007-05-15
2007-05-16
2007-05-17
2007-05-18
2007-05-19
2007-05-20
2007-05-21
2007-05-22
2007-05-23
2007-05-24
2007-05-25
2007-05-26
2007-05-27
2007-05-28
2007-05-29
2007-05-30
2007-05-31
2007-06-01
2007-06-02
2007-06-03
2007-06-04
2007-06-05
2007-06-06
2007-06-07
2007-06-08
2007-06-09
2007-06-10
2007-06-11
2007-06-12
2007-06-13
2007-06-14
2007-06-15
2007-06-16
2007-06-17
2007-06-18
2007-06-19
2007-06-20
2007-06-21
2007-06-22
2007-06-23
30.00
25.00
23.89
27.78
30.00
22.78
27.78
28.89
28.89
30.00
32.78
32.78
30.56
30.00
25.56
30.56
31.67
32.78
33.89
32.78
31.67
26.67
25.56
25.56
27.78
27.78
30.00
30.56
32.78
33.89
30.56
27.78
30.56
27.78
25.00
28.89
28.89
30.56
30.56
28.89
26.67
25.00
27.78
30.56
28.89
23.89
20.00
19.44
22.22
23.89
20.00
23.33
24.44
24.44
15.00
26.67
27.22
27.22
26.67
23.33
25.56
27.22
28.89
29.44
28.89
28.89
24.44
23.33
23.33
23.89
24.44
26.67
27.22
28.33
29.44
27.78
26.67
26.11
25.56
23.33
24.44
24.44
26.11
26.67
26.67
24.44
22.22
24.44
26.67
25.56
17.78
15.00
15.00
16.67
17.78
16.67
18.89
20.00
20.56
0.00
20.56
21.67
23.89
21.67
20.56
20.56
22.78
25.00
25.00
25.56
26.67
21.67
21.67
20.56
20.00
21.67
22.78
23.89
23.89
25.00
25.56
25.00
21.67
22.78
21.67
20.00
20.56
21.67
22.78
25.00
21.67
20.00
21.67
22.78
21.67
1.59
1.33
1.30
1.48
1.59
1.33
1.56
1.63
1.63
1.00
1.78
1.81
1.81
1.78
1.56
1.70
1.81
1.93
1.96
1.93
1.93
1.63
1.56
1.56
1.59
1.63
1.78
1.81
1.89
1.96
1.85
1.78
1.74
1.70
1.56
1.63
1.63
1.74
1.78
1.78
1.63
1.48
1.63
1.78
1.70
52
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
71.39
59.76
58.10
66.40
71.39
59.76
69.72
73.05
73.05
44.82
79.69
81.35
81.35
79.69
69.72
76.37
81.35
86.33
87.99
86.33
86.33
73.05
69.72
69.72
71.39
73.05
79.69
81.35
84.67
87.99
83.01
79.69
78.03
76.37
69.72
73.05
73.05
78.03
79.69
79.69
73.05
66.40
73.05
79.69
76.37
2007-06-24
2007-06-25
2007-06-26
2007-06-27
2007-06-28
2007-06-29
2007-06-30
2007-07-01
2007-07-02
2007-07-03
2007-07-04
2007-07-05
2007-07-06
2007-07-07
2007-07-08
2007-07-09
2007-07-10
2007-07-11
2007-07-12
2007-07-13
2007-07-14
2007-07-15
2007-07-16
2007-07-17
2007-07-18
2007-07-19
2007-07-20
2007-07-21
2007-07-22
2007-07-23
2007-07-24
2007-07-25
2007-07-26
2007-07-27
2007-07-28
2007-07-29
2007-07-30
2007-07-31
2007-08-01
2007-08-02
2007-08-03
2007-08-04
2007-08-05
2007-08-06
2007-08-07
30.00
30.56
30.00
30.00
32.78
33.89
32.78
31.67
28.89
33.89
35.56
35.56
35.00
35.00
36.67
26.67
32.78
35.00
30.00
26.67
25.00
28.89
30.00
35.56
35.56
33.89
32.78
26.67
27.78
25.56
27.78
26.67
31.67
35.00
35.56
36.67
36.67
35.56
36.67
36.67
25.56
28.89
31.67
35.00
35.56
26.67
26.67
27.78
26.67
28.89
30.00
30.00
27.78
26.67
30.00
31.11
32.22
32.22
32.22
31.67
25.56
28.89
31.11
28.33
25.56
23.33
25.56
27.78
31.11
31.67
32.22
28.33
24.44
24.44
23.33
25.56
24.44
27.78
30.00
30.00
32.22
32.22
31.11
32.78
32.22
24.44
26.67
28.33
31.11
31.67
23.89
22.78
25.00
23.89
25.00
25.56
26.67
23.89
23.89
26.67
26.67
28.89
28.89
30.00
26.67
25.00
25.00
26.67
26.67
25.00
21.67
22.78
25.00
26.67
27.78
30.00
23.89
21.67
21.67
21.67
23.89
22.78
23.89
25.00
23.89
27.78
27.78
26.67
28.89
26.67
23.89
25.00
25.00
26.67
27.78
1.78
1.78
1.85
1.78
1.93
2.00
2.00
1.85
1.78
2.00
2.07
2.15
2.15
2.15
2.11
1.70
1.93
2.07
1.89
1.70
1.56
1.70
1.85
2.07
2.11
2.15
1.89
1.63
1.63
1.56
1.70
1.63
1.85
2.00
2.00
2.15
2.15
2.07
2.19
2.15
1.63
1.78
1.89
2.07
2.11
53
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
79.69
79.69
83.01
79.69
86.33
89.65
89.65
83.01
79.69
89.65
92.97
96.29
96.29
96.29
94.63
76.37
86.33
92.97
84.67
76.37
69.72
76.37
83.01
92.97
94.63
96.29
84.67
73.05
73.05
69.72
76.37
73.05
83.01
89.65
89.65
96.29
96.29
92.97
97.95
96.29
73.05
79.69
84.67
92.97
94.63
2007-08-08
2007-08-09
2007-08-10
2007-08-11
2007-08-12
2007-08-13
2007-08-14
2007-08-15
2007-08-16
2007-08-17
2007-08-18
2007-08-19
2007-08-20
2007-08-21
2007-08-22
2007-08-23
2007-08-24
2007-08-25
2007-08-26
2007-08-27
2007-08-28
2007-08-29
2007-08-30
2007-08-31
2007-09-01
2007-09-02
2007-09-03
2007-09-04
2007-09-05
2007-09-06
2007-09-07
2007-09-08
2007-09-09
2007-09-10
2007-09-11
2007-09-12
2007-09-13
2007-09-14
2007-09-15
2007-09-16
2007-09-17
2007-09-18
2007-09-19
2007-09-20
2007-09-21
35.56
35.56
35.56
28.89
32.78
33.89
33.89
30.56
25.00
33.89
33.89
32.78
32.78
33.89
32.78
31.67
35.00
33.89
35.56
31.67
31.67
32.78
35.00
27.78
22.78
28.89
26.67
27.78
30.00
30.00
30.00
26.67
27.78
28.89
28.89
30.56
28.89
23.89
28.89
31.67
30.56
30.00
28.89
28.89
30.00
31.67
31.67
31.67
27.22
28.89
28.89
30.00
27.22
23.33
28.33
29.44
28.89
30.00
29.44
28.89
28.89
30.00
30.00
30.00
28.89
28.33
28.89
31.11
24.44
21.11
24.44
24.44
23.89
25.00
25.00
25.00
24.44
24.44
24.44
25.56
27.22
25.56
22.22
23.89
26.11
25.56
25.56
23.33
23.33
23.89
27.78
27.78
27.78
25.56
25.00
23.89
25.56
23.89
21.67
22.78
25.00
25.56
26.67
25.00
25.56
25.56
25.56
25.56
25.00
25.56
25.00
25.00
26.67
21.67
20.00
20.56
21.67
20.00
20.00
20.00
20.00
21.67
20.56
20.56
21.67
23.89
22.78
20.00
18.89
20.56
20.56
20.56
17.78
17.78
17.78
2.11
2.11
2.11
1.81
1.93
1.93
2.00
1.81
1.56
1.89
1.96
1.93
2.00
1.96
1.93
1.93
2.00
2.00
2.00
1.93
1.89
1.93
2.07
1.63
1.41
1.63
1.63
1.59
1.67
1.67
1.67
1.63
1.63
1.63
1.70
1.81
1.70
1.48
1.59
1.74
1.70
1.70
1.56
1.56
1.59
54
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
94.63
94.63
94.63
81.35
86.33
86.33
89.65
81.35
69.72
84.67
87.99
86.33
89.65
87.99
86.33
86.33
89.65
89.65
89.65
86.33
84.67
86.33
92.97
73.05
63.08
73.05
73.05
71.39
74.71
74.71
74.71
73.05
73.05
73.05
76.37
81.35
76.37
66.40
71.39
78.03
76.37
76.37
69.72
69.72
71.39
2007-09-22
2007-09-23
2007-09-24
2007-09-25
2007-09-26
2007-09-27
2007-09-28
2007-09-29
2007-09-30
2007-10-01
2007-10-02
2007-10-03
2007-10-04
2007-10-05
2007-10-06
2007-10-07
2007-10-08
2007-10-09
2007-10-10
2007-10-11
2007-10-12
2007-10-13
2007-10-14
2007-10-15
2007-10-16
2007-10-17
2007-10-18
2007-10-19
2007-10-20
2007-10-21
2007-10-22
2007-10-23
2007-10-24
2007-10-25
2007-10-26
2007-10-27
2007-10-28
2007-10-29
2007-10-30
2007-10-31
30.00
28.89
28.89
31.67
33.89
35.00
21.67
21.67
25.56
30.00
30.00
31.67
33.89
32.78
32.78
25.56
22.78
23.89
25.00
22.78
20.00
15.56
16.67
21.67
22.78
21.67
21.67
22.78
20.56
23.89
25.00
25.00
25.00
23.89
25.00
22.78
17.78
11.67
13.89
12.78
24.44
24.44
25.56
26.67
28.89
29.44
20.00
20.00
22.22
25.00
24.44
25.56
28.33
27.78
27.78
23.33
18.89
18.89
19.44
18.89
17.78
14.44
15.56
18.33
17.78
17.22
18.33
17.78
15.56
18.89
20.00
19.44
21.11
20.00
20.00
20.00
15.56
10.00
11.11
12.22
18.89
20.56
21.67
21.67
23.89
22.78
17.78
17.78
18.89
20.00
18.89
20.00
22.78
22.78
22.78
20.00
15.56
13.89
13.89
15.56
15.00
13.89
13.89
15.00
12.78
12.78
15.00
12.78
10.56
13.89
15.56
13.89
17.78
15.56
15.00
16.67
12.78
8.89
8.89
11.67
1.63
1.63
1.70
1.78
1.93
1.96
1.33
1.33
1.48
1.67
1.63
1.70
1.89
1.85
1.85
1.56
1.26
1.26
1.30
1.26
1.19
0.96
1.04
1.22
1.19
1.15
1.22
1.19
1.04
1.26
1.33
1.30
1.41
1.33
1.33
1.33
1.04
0.67
0.74
0.81
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
44 823.18
73.05
73.05
76.37
79.69
86.33
87.99
59.76
59.76
66.40
74.71
73.05
76.37
84.67
83.01
83.01
69.72
56.44
56.44
58.10
56.44
53.12
43.16
46.48
54.78
53.12
51.46
54.78
53.12
46.48
56.44
59.76
58.10
63.08
59.76
59.76
59.76
46.48
29.88
33.20
36.52
Fuel Mix
The coal level can’t exceed 20% of the fuel mix according to the regulation, the level is set to
15% just to make sure the fuel mixtures heating value is high enough to be able to ignite
(Table C 4).
55
Table C 4. Input data and calculation of the property of the fuel mix.
R
Coal
MSW
5.44
20.00
0.85
0.15
Properties
1 Fuel Heating Value [MJ/kg]
2 Fuel Mix Levels
Fuel Mix
Fuel Heating Value [MJ/kg]
7.60
Calculation
MSW*(R1*R2)+Coal*( R1*R2)
Environmental Emission
The needed equations for calculation of the emission coming out from using coal and MSW
are the following:
𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑜𝑜𝑜𝑜 𝑋𝑋 =
𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑜𝑜𝑜𝑜 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 ∙𝑋𝑋 %
Where X is the substance to be calculated.
𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝑜𝑜𝑜𝑜 𝑋𝑋
Y 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 = 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑜𝑜𝑜𝑜 𝑋𝑋 ∙ 𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀 𝑜𝑜𝑜𝑜 Y
Eq C 1
Eq C 2
Where Y is the chemical substance that forms from X together with O2
Y 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 =
𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 ∙𝑌𝑌 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃
Eq C 3
The input data is provided from EPSRI, Wuhan Environmental Sanitation Science Research
& Design Institute and Wuhan High Technology Heat Power Plant (Table C 5 and Table C 6).
Table C 5. Calculation process and results for the CO2 emission levels.
Equations
Coal Fuel Mix
MSW
CO2 Calculation
Operational Time
7 000
12 000
7 000
Hours
Production
160 800 260 000
160 800
MWh
Fuel Input
15 000
18 100
15 000
kg Fuel/h
Carbon level %
13.67
64.00
21.20
kg C/kg Fuel
C-mass
12
12
12
kg/kmol
CO2-mass
44
44
44
kg/kmol
Calculation
C in Fuel
170.94
965.33
265.07
kmol/h Eq C 1
CO2 emission Fuel
7 521.33 42 474.67 11 663.03
kg/h Eq C 2
kg CO2/MWh
327.42 1 960.37
507.72 kg CO2/MWh Eq C 3
56
Table C 6. Calculation process and results for the SO2 emission levels.
Equations
Coal Fuel Mix
MSW
SO2 Calculation
Operational Time
7 000
12 000
7 000
Hours
Production
160 800
260 000
160 800
MWh
Fuel Input
15 000
18 100
15 000
kg Fuel/h
Sulphur level %
0.06
0.61
0.14
kg S/kg Fuel
S-mass
16
16
16
kg/kmol
SO2-mass
48
480
48
kg/kmol
Calculation
C in Fuel
0.56
6.90
1.33
kmol/h Eq C 1
SO2 emission Fuel
27.00
331.23
63.66
kg SO2/h Eq C 2
kg SO2/MWh
1.18
15.29
2.77 kg SO2/MWh Eq C 3
There are several different parameters used as input data in the computer simulation model
(Table C 7).
Table C 7. List of parameters used as input data.
Incinerator Input Data
Fuel Heating Value [MJ/kg]
Fuel Heating Value [MWh/ton]
Gate Fee [Rmb/ton]
Efficiency Furnace [%]
Mechanical Efficiency [%]
Cost Of Capital [%]
Expected Lifetime [Years]
Investment Price [Rmb/ton Capacity]
CFB Production Cost [Rmb/ton capacity * annually]
CFB Operation Cost [Rmb/ton capacity * annually]
Electricity Production Cost [Rmb/MWh]
Sale Tax [%]
CO2 Emission [kg/MWh electricity]
SO2 Emission [kg/MWh electricity]
Electricity Income [Rmb/kWh]
Heat Income [Rmb/kWh]
Cooling Income [Rmb/kWh]
Fuel Mix in CFB
MSW [%]
Coal [%]
Fuel Mix Heating Value [MJ/kg]
Fuel Mix Heating Value [MWh/ton]
CO2 Emission [kg/MWh electricity]
SO2 Emission [kg/MWh electricity]
Cooling Plant Input Data
COP
Investment Price [Rmb/MW]
57
Maintenance Cost [Rmb/MW * Annually ]
Production Cost [Rmb/kWh]
Pipeline Cost [Rmb/m]
Pipe Line Length [km]
Thermal Storage System
Investment Price [Rmb/m3]
H2O Density [kg/m3]
Cp [J/kg * K]
Temperature Differens [Celsius]
Effciency [%]
Thermal Storage Capacity [kWh/m3]
Coal Power Plant Data
Fuel Heating Value [MJ/kg]
Fuel Heating Value [MWh/ton]
Fuel Cost [Rmb/ton]
Efficiency Furnace [%]
Mechanical Efficiency [%]
Electricity Price [Rmb/kWh]
CO2 Emission [kg/MWh electricity]
SO2 Emission [kg/MWh electricity]
AC Input Data
COP
58