Mapping residential thermal comfort gap at very
high resolution spatial scale: Implications for
energy policy design
João Pedro Gouveia, P. Palma, J. Seixas, S. Simões
40th Annual IAEE International Conference
June 18-21, 2017 | Singapore
1
Summary
 Problem Introduction
 Case Study
 Objectives
 Methodology
 Results and discussion
 Conclusions
 Future Work
2
Problem Introduction
 Most of the population spends 90% of their time in artificial environments, i.e inside
buildings, particularly in their homes.
 Thermal Comfort is related to the thermal environmental, which depends on the
building’s energy performance.
 In many developed countries the population is unable to afford to keep their homes in
an adequate temperature
Suggesting Fuel Poverty issues.
 Poor thermal comfort conditions have a negative effect on people’s health and wellbeing.
Introduction
Methodology
Results and Discussion
Conclusions
3
Problem Introduction
 Several authors like Jylhäa et al. (2015), Moustris et al. (2015) and Kohler et al.
(2016) estimate heating and cooling energy needs in their studies.
 In the project Stratego (2015) heating and cooling energy needs were estimated
and mapped for several member states of the European Union.
 Lopes (2010) estimated heating and cooling energy needs of Portugal, per region.
 Authors like Giuliano Dall’O et al. (2011) compare energy needs with energy
consumption for heating and cooling.
 Magalhães and Leal (2014) computed the global heating energy gap for Portugal,
using energy certificates and national energy balances.
 In the framework of the ClimaAdapt project, Simões et al. (2016) calculated the
heating and cooling energy gap for 29 municipalities of Portugal.
Introduction
Methodology
Results and Discussion
Conclusions
4
Case Study – Portugal (Europe) I
Size: 92 090 km²
Population: 10 Million
Density: 115,3 capita/km²
GDP per capita = US$ 26 306
Introduction
Methodology
Results and Discussion
Conclusions
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Case Study – Portugal (Europe) II
 In 2015, final energy consumption in the residential sector was about 16.5% of
the country’s total consumption.
 Space heating and cooling represents about 23% and 0.64% of the sector’s
consumption (2013) – energy consumption significantly below EU and countries
with similar climate.
 Projections point to an increase in cooling’s final energy consumption and a
decrease for space heating in southwestern Europe.
 European Union has steered its energy policy towards the reduction of final
energy consumption, increase in energy efficiency and decrease in GHG
emissions.
 Notwithstanding the importance of these energy objectives
thermal comfort should should be considered as a priority.
Introduction
Methodology
Results and Discussion
access to
Conclusions
6
Objectives
Assessment of energy performance gap on thermal comfort of
the occupied households in all 3092 civil parishes of continental
Portugal and islands
i.
Estimate heating and cooling energy needs at very high resolution
spatial scale, for thermal comfort reference conditions established in
the most recent residential building energy performance regulation
ii.
Estimate heating and cooling’s final energy consumption
iii. Compute and map the energy gap, assess its geographical distribution
in the country and identify its causes
iv. Assessment of energy needs’ scenarios effect on the heating and
cooling energy gap
Introduction
Methodology
Results and Discussion
Conclusions
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Methodology - Heating and cooling gap estimation
2º) Estimation of Households’
dataset, per nr of floors and
date of construction
1º) Building’s dataset
(INE, 2011)
5º) Heating and cooling
useful energy needs
H&C equipment
ownership rate and
efficiencies; Typologies’
households and areas
(Lopes, 2010)
4º) Toolkit BldAdaPT for energy
needs estimation
(ClimaAdaPT –
(Simões et al., 2015)
6º) Heating and cooling final
energy needs
“Conservative”
8º) 2 Energy needs
scenarios - ∆
Scenario
of heated/cooled
areas and
equipment’s
operating hours per
“Strict”
climate zone
Scenario
Introduction
3º) Building’s typologies,
per nº of floors and date of
construction
Methodology
7º) Heating and cooling final
energy consumption
Reference
scenario
(DGEG, 2013);
(ICESD, 2011);
(Oliveira, 2016);
typologies’
households and
areas
9º) Heating and cooling Gap
per civil parish
Results and Discussion
Conclusions
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Heating and Cooling Useful Energy Maps
Factors: HDD
(heating) and
external
average
temperature
(cooling)
Figure 1 – Heating and cooling useful energy needs per household and unit of
area (MJ/(m2.year))
Introduction
Methodology
Results e Discussion
Conclusions
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Heating Useful Energy per typology and climate
zone
Newer Buildings
Influence:
Construction
parameters and
climate regions
(I3)
Figure 2 - Heating useful energy needs per household, according to the
building’s typology and climate zone (MJ/(m2.year))
Introduction
Methodology
Results e Discussion
Conclusions
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Cooling Useful Energy per typologies and
climate zone
Newer Buildings
Influence:
climate regions
(V3)
No significant
influence of
construction
parameters in the
first 9 typologies.
Figure 3 – Cooling useful energy needs per household, according to the
building’s typology and climate zone (MJ/(m2.year))
Introduction
Methodology
Results e Discussion
Conclusions
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Heating and Cooling Useful Energy Maps
Factors:
Household
Areas (but not
with significant
changes).
Figure 4 – Heating and cooling useful energy needs per household (MJ/year)
Introduction
Methodology
Results e Discussion
Conclusions
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Heating and Cooling Useful Energy Maps
Factors:
Number of
Buildings
(significant
changes)
Figure 5 - Heating and cooling useful energy needs (TJ/year)
Introduction
Methodology
Results e Discussion
Conclusions
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Heating and Cooling Final Energy Map
Factors:
Equipment
Ownership and
efficiency
Figure 6 – Heating and cooling final energy needs (TJ/year)
Introduction
Methodology
Results e Discussion
Conclusions
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Heating and Cooling final energy consumption
Figure 7 – Heating and cooling final energy consumption (GJ/year)
Introduction
Methodology
Results e Discussion
Conclusions
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Heating and cooling energy gaps – Reference
Scenario
• High Performance
Gaps
• Lowest Heating
63%
• Lowest Cooling
85%
Figure 8 – Heating and cooling energy gaps (%)
Introduction
Methodology
Results e Discussion
Conclusions
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Reference Scenario
Figure 9 – Civil parishes distribution per heating gap (left) and cooling gap (right)

More than 95% of all civil parishes have a heating gap higher than 85%

About 64% of all civil parishes have a cooling gap equal to or greater than 98%

To match the energy needs, national consumption would have to be 11 and 26 times bigger
than 2013’s consumption, for heating and cooling respectively
 The average civil parish’ heating and cooling gap is respectively 93 and 97%
Introduction
Methodology
Results e Discussion
Conclusions
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“Conservative” Scenario
• Changes on
conditioned area
and climatization
schedules by zone
Figure 10 – Heating and cooling energy gaps (%)
Introduction
Methodology
Results e Discussion
Conclusions
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Spatial and
temporal patterns
of indoor
“Conservative” Scenario
Figure 11 – Civil parishes’ distribution per heating gap (left) and cooling gap (right)

Heating gap annulled in 20% of all civil parishes.

More than 60% of all civil parishes cooling gap equal to or greater than 79%.

To match the energy needs, national consumption would have to be 2 and 4 times higher
than 2013’s consumption, for heating and cooling respectively.
 The average civil parish heating and cooling gap is 52% and 76% respectively.
Introduction
Methodology
Results e Discussion
Conclusions
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“Strict” Scenario
• Significant
Changes on
conditioned
area and
climatization
schedules by
zone
Figure 12 – Heating and cooling energy gap (%)
Introduction
Methodology
Results e Discussion
Conclusions
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Remaining parishes with gap
probably linked to fuel poverty
issues
“Strict” Scenario
Figure 13 – Civil parishes’ distribution per heating gap (left) and cooling gap (right)

Heating gap annulled in 75% of all civil parishes.

Cooling gap annulled in 25% of all civil parishes.

To bridge the remaining gaps
heating and cooling.
+ 33% and 52% of 2013’ national consumption for
 The average civil parish’ heating and cooling gap is respectively 11% e 23%.
Introduction
Methodology
Results e Discussion
Conclusions
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“Strict” Scenario
Figure 14 – Relation between civil parishes’ heating and cooling gaps per
climate zone
Introduction
Methodology
Results e Discussion
Conclusions
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Conclusions
 Poor buildings’ energy performance and low heating and cooling final energy
consumption + several indicators of fuel poverty
Thermal Comfort at risk
 In this study, the most critical regions were pinpointed, as well as the causes
behind the gaps of its civil parishes.
 Provides data on the necessary energy consumption that would allow all the
population to have access to thermal comfort conditions in their households
 The results of this study corroborate the assumption that fuel poverty is the most
significant cause for this problem.
 In the Reference scenario, the final energy needs are considerably greater than
the real consumption, in every civil parish, both for heating and for cooling.
 Portugal’s global heating and cooling energy gaps are 92% and 96% respectively.
Introduction
Methodology
Results and Discussion
Conclusions
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Conclusions
 The civil parishes located in the Guarda, Bragança and Vila Real districts are most
critical in the heating season.
 Regarding cooling, the problem is more widespread, affecting several regions of
the country.
 Civil parishes of the Castelo Branco district stand out as the most critical in the
cooling season.
 Civil parishes whose gaps are annulled, the difference between energy needs and
consumption
spatial and temporal climatization pattern set purposely by
the consumers.
 In the Strict scenario, when heating or cooling gaps still persist
fuel poverty of the civil parishes’ population.
Introduction
Methodology
Results and Discussion
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potential
Conclusions
Future Work
• More data needed to better assess the problem
municipal surveys
• Estimate energy needs using dynamic simulation method
• Evaluate the impact of building’s refurbishment measures in the heating and
cooling gap
• Installation of sensors and smart meters when building’s refurbishment takes
place
better understanding of indoor temperature and consumption by
equipment. Complement this work with thermal comfort study based on
PMV/PPD model
• Use results of this work at local policy level – Ex: Intermunicipal plan for
climate change adaptation
Introduction
Methodology
Results and Discussion
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Conclusions
Consumers
Profiles &
Energy
Efficiency
New
Technologies
& Low Carbon
Practices
Energy
Transitions
Policy
Support
Integrative
Energy City
Planning
ENERGY &
CLIMATE
Thank you for
your attention!
João Pedro Gouveia
[email protected]
Climate
Mitigation/
Adaptation
CO2
40th Annual IAEE
International Conference
June 18-21, 2017 |
Singapore
26