Sustainability and Nuclear Energy: Main Concepts
and the Analytic Network Process (ANP) Approach
R. Calabrese
ENEA, Reactor and Fuel Cycle Safety and Security Methods Section,
via Martiri di Monte Sole 4, I-40129 Bologna (Italy), [email protected]
University of Padova, Department of Industrial Engineering,
via Gradenigo 6/A, I-35131 Padova (Italy)
ABSTRACT
The concept of sustainable development addresses the capability to meet present needs
without compromising the ability of future generations to meet their own needs. Sustainability
is therefore a fundamental approach in the definition of future energy systems to accomplish
economical, social, and environmental criteria.
In this frame, nuclear energy is characterized, aiming at tackling human-induced
climate changes, by low greenhouse gas (GHG) emissions while facing drawbacks such as the
shortage of natural uranium resources, the steadily increase of spent nuclear fuel stockpiles as
well as proliferation risks. The demand for electricity generation is growing and the definition
of an energy portfolio capable of meeting needs in a sustainable manner is more and more
urgent given the narrow timeframe left for a transition to a low carbon electricity generation.
In this paper, after the definition a set of indicators used in literature for the evaluation
of sustainability, the composition of energy mix for the generation of electricity was
calculated for three scenarios by means of the Analytic Network Process (ANP) approach.
1
INTRODUCTION
The concept of sustainable development addresses the capability of meeting present
needs without compromising the ability of future generations to meet their own needs. Energy
is fundamental to improve living standards and to support societal development. The use of
fossil energy sources, accounting for about 80% of the global primary energy needs, leads to
phenomena of increasing concern like urban air pollution, regional acidification and
human−induced climate change [1].
Nuclear energy is capable of tackling GHG emissions at competitive costs [2]. If, on the
one hand, this latter aspect is assumed as a fundamental driver for its development, on the
other hand nuclear energy faces drawbacks such as the management of radioactive waste and
their proliferation risks. Moreover, safety is a crucial factor for the development of nuclear
energy as confirmed by the Fukushima−Daiichi accident that raised new questions in the
public opinion forcing countries to the decision to phase−out or to abandon any plan to enter
nuclear business. Nevertheless, main reasons promoting the so-called nuclear renaissance
seen in the last decade are still valid. This statement is consistent with the projections that,
even though to a smaller extent, confirm an increase in the deployment of nuclear energy [3].
The paper presents a study on the role of nuclear energy in the electricity sector where other
1302.1
1302.2
energy sources are competing in the frame of a sustainable development. The method used for
the analysis is the ANP whereas the list of indicators was defined according to the literature
dealing with the sustainability of the electricity sector.
2
SUSTAIINABILITY ISSUES
Climate change concern has become one of the most challenging issues for the new
century. The level of CO2 is moving steadily towards the limits of 450 ppm a value leading to
an increase of the average global temperature by 2 °C [4]; see Fig. 1. New trade−offs are
necessary especially in the developing countries, to account for the demographic increase,
energy resources scarcity and improving of living standards.
400
CO2 concentration (ppm)
390
380
370
360
350
340
330
1980
1985
1990
1995
2000
2005
2010
2015
Year
Figure 1: CO2 concentration in the atmosphere (globally averaged marine surface
annual mean data) source: U.S. Dep. of Commerce/National Oceanic & Atmospheric
Administration/NOAA Research
The total primary energy supply (TPES) moved from 6107 Mtoe in 1973 to 12717 in
2010; the electricity generation raised, in the same period, from 6115 TWh to 21431 TWh
showing a nearly four−fold increase [5]. In 2010, the production of electricity from fossil fuel
was 67.4% with a slight reduction from the value of 75.1% in 1973 [5]. New electricity
generating plants are foreseen to be installed during the coming two decades with a projected
total capacity of the same order of that installed in the past century [6].
The share of nuclear electricity increased from 3.3% to 12.9% as well as natural gas
share moved from the 12.1% in 1973 to 22.2% in 2010 [5]. Thanks to its capability in tackling
GHG emissions, in the BLUE MAP scenario nuclear energy is accounted to reach about 1200
GWe by the middle of the century [3]. The concept of sustainability addresses, besides
environmental, other dimensions, social and economic. The planning of a sustainable energy
mix needs therefore a deeper analysis through a multi−parametric approach [7]. For this
purpose, a brief review of indicators used in sustainability evaluations is presented in the
following paragraphs.
The case study of Turkey was presented in [8], where, by using the ANP approach, nine
energy alternatives were investigated. The model considered four sub−networks addressing
1302.3
different indicators for cost, environmental issues, health hazard, energy security and
technology. The evaluations of technologies were qualitative and based on expert judgements
while for the other parameters quantitative values were applied. Two scenarios were studied,
in one, environment had the prominent importance, in the other, energy security had the
highest priority [8]. The share of nuclear energy was in the range of 8.12–10.21%
highlighting that the introduction of nuclear energy markedly improved the security of the
energy system [8].
In the study [9], by using the Analytic Hierarchy Process (AHP), the sustainability of
ten plants was evaluated through a list of eight indicators grouped in two sets: Economic (4),
Technology and Sustainability (4). Four scenarios were analysed, with different weights given
to the main criteria. The grouping was based on the assumption that a plant with a
well−performing technology is also more sustainable [9]. In this analysis, assuming that
sustainability and technology are more important than the economic criteria, nuclear plants
proved a better performance than all fossil fuel-based plants ranking in the sixth position with
a share of 6.98%. Its main advantages were the low fuel cost, the high availability and
capacity, the relatively low external costs [9]. Sustainability evaluations of Swiss utilities
were presented in [10]; economic, social and environmental performance of eighteen different
technologies in the 2030 time horizon were investigated. A list of 75 indicators, defined using
different methodologies, e.g., the life cycle assessment (LCA), were combined by means of
the multi criteria decision analysis (MCDA) to determine a sustainability index for each
alternative [10]. Technologies were classified through not only their energy source but also
taking into account plant capacity, e.g., large centralized plants or small distributed [10]. The
impact of reference profiles, representing different stakeholders, proved to have a significant
effect on the ranking of nuclear energy [10]. In the study [11], the sustainability of eight
alternative energy sources were evaluated according to the 3A principle (Accessibility,
Availability and Acceptability) through a qualitative measurement of eight criteria. Nuclear
energy achieved, in this analysis, the second position in the ranking after wind turning out to
be a sustainable technology comparable to renewables [11].
While the just presented studies were published before the Fukushima accident, in [12]
and [13] the analysis was carried out in the light of this key event for the perspectives of
nuclear energy. In [12], the energy options of Japan were investigated. Based on the selection
of ten criteria covering economic, social and environmental areas, four scenarios extending to
2030 were analyzed aiming at evaluating their sustainability [12]. The energy scenarios were
defined through different mix of four sources: nuclear, renewables, fossil and others. In the
studied scenarios, nuclear energy accounts for a share of 0%, 15%, 20% and 35%. The
analysis was performed by means of the Multi−criteria decision-making analysis (MCDMA)
[12]. The study showed the good performance of a high nuclear energy penetration even with
the selection of weights according to a “anti−nuclear” position [12]. The need for a substantial
backup power supply was judged a strong limit in the performance of the nuclear−free option
[12]. According to the conclusions drawn in this study, the most limiting factor in the
development of nuclear energy turned out to be the trust of public opinion, markedly low after
the Fukushima accident [12]. Similar results were resented in [13]. The study proposed a
careful analysis of the current electricity needs of South Korea through an hourly description
of the demand and a detailed verification of the physical limits in the introduction of
renewables [13]. Eight scenarios were analyzed assessing their impact on the sustainability by
means of the MCDMA applied to ten criteria for the economic, environmental, social
dimensions [13]. Nuclear power scenario (maximum penetration of nuclear energy) proved to
achieve the lowest impact on sustainability [13].
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Aiming at studying the sustainability of a portfolio of energy sources through a
multi−criteria approach, a model based on the ANP approach was prepared. The capability of
this method to describe feedbacks and complex interactions between the elements of the
system was of great interest for the objective.
3
THE ANALYTIC NETWORK APPROACH
The Analytic Network Process is a theory that extends the Analytic Hierarchy Process
to cases of dependence and feedbacks through the use of the concept of supermatrix [14]. The
ANP provides a framework to include clusters of elements connected in any desired way to
investigate the process and deriving the adopted priorities from the distribution of influence
among elements and among clusters. This method permits to describe the dependence among
components as well as feedbacks, outer and inner dependence respectively. A supermatrix, W,
is a complete system matrix of components, {Ca, Cb, Cc,..., Cn}, and their linkages, Wij. The
supermatrix represents the impact of all model elements relative to the complete set of
elements. The actual elements that make up the columns (Wij) of the supermatrix are the
eigenvector solutions within the components. The final priority weights are calculated by
multiplying the supermatrix by itself until the columns stabilize (limiting matrix). The
analysis presented in the paper was performed by means of the Super Decisions 2.2 code [15].
4
SUSTAINABILITY INDICATORS AND MODELLING
The paper presents an assessment of a sustainable energy mix, where nine alternatives
are given, based on twelve indicators grouped in economic (3), environmental (7) and social
(3); see Tables 1 and 2. Table 1 presents the status, in 2010, of the electricity generation
sector by fuel (Reference column) [5]. Values used in the analysis for total cost, loss of
expected life, CO2 and SO2.are in agreement with [8]. The values of efficiency, availability,
fuel cost, Reserves-to-Production (R/P) ratio and external cost criteria were defined according
to [9]. Finally, the data available in [12] was used for the evaluation of priorities for the water
consumption, heated water and land use criteria.
Table 1: Economic and social indicators
Reference
Share by
fuel*
(%)
Total cost
Fuel cost**
Availability
($/MWh)
(cent/kWh)
(%)
Natural Gas
22.2
38.2
2.34
91
Hydropower
16.0
35.5
−
50
0.56
9.2
Coal
40.6
30.9
1.31
85.4
8.4
165.5
Oil
4.6
58.2
1.84
92
6.75
165.5
Nuclear
12.9
26
0.27
96
0.49
11.9
Biomass
1.0
21.6
2.05
80
2.65
45
Geothermal
1.0
25.4
−
95
0.2
34.4
Wind
1.0
41.8
−
38
0.16
9.5
Alternatives
Economic
Social
External
Loss of life
cost**
(cent/kWh) (year/TWh)
1.33
46.1
0.7
125.8
−
20
0.24
* The share of each renewable source was defined to accomplish the total value of 3.7% in [5].
** The complete unit of measure is cents of € per kWh.
Solar
74
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The energy system was modelled through a top−level network (no sub−networks). The
model consists of four clusters (Alternatives, Economic, Environmental, Social) connected by
bidirectional links. The cluster Alternatives contains nine nodes for the description of the
different energy sources taken into account. The other clusters contain the nodes representing
the corresponding criteria selected for the analysis. An inner dependence was introduced
between the nodes of the Alternatives cluster to take into account the status of electricity
sector (Reference) assuming that the share of competitors has an effect on the development of
each energy source.
The values of criteria presented in Tab. 1 and 2 were applied through pairwise
comparisons of elements when the energy sources acted as children and the indicator as
parent. In the opposite direction, when the energy source was the parent and the criteria the
children, the inverse of ranking achieved by the alternative for each criteria was applied. No
inter−relationship were created between the assumed criteria. Figure 2 shows a simplified
scheme of the network.
Table 2: Environmental indicators
Efficiency
R/P ratio
CO2
SO2
Water use
Water h.
Land use
(%)
(years)
(g/kWh)
(g/kWh)
(kl/MWh)
(kl/MWh)
(km2/ GW)
Natural Gas
54.8
66.7
386
0.125
−
52.8
1
Hydropower
80
−
32
0.055
68
−
36.93
Coal
39.4
164
838
0.351
−
132.3
2
Oil
37.5
40.5
760
0.314
−
42.3
1
Nuclear
33.5
70
17
0.072
−
161.5
1
Biomass
28
−
−
0.087
1.75
0.05
1.5
Geothermal
6
−
21
−
3.41
3.78
148
Wind
35
−
38
0.071
−
−
10
Solar
9.4
−
319
0.494
0.08
−
10
Alternatives
Social
feedback
Alternatives
Economic
Environmental
bidirectional links
Figure 2: ANP approach: scheme of the network for the analysis
A preliminary analysis was performed aiming at reproducing the status of the electricity
sector assigning, in the comparison, nearly all the priority to the Alternatives cluster; see Fig.
3. Assuming that a share of 25% is given to the Alternatives cluster, three scenarios were
1302.6
analyzed. The scenario Economic assigned 50% of priority to the Economic cluster and
12.5% to the Environmental and Social clusters. The Environmental and Social scenarios
were defined swapping properly these values; see Fig. 4. Finally, the impact of the
Alternatives priority on the results was tested for the Environmental scenario, see Fig. 5.
5
RESULTS AND DISCUSSION
The results shown in Fig. 3 are in reasonable agreement with the Reference energy mix,
with a general overestimation of all alternatives but coal that is underestimated. The current
ranking of the energy sources was well predicted by the code. Figure 4 presents the
composition of the energy portfolios calculated for the studied scenarios in comparison with
the status in 2010. The model confirms that the current energy mix is not sustainable
highlighting the well−assessed need for a transition to a low carbon energy system.
Solar
prediction
reference (2010)
Wind
Alternatives
Geothermal
Biomass
Nuclear
Oil
Coal
Hydropower
Natural Gas
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
Share (/)
Figure 3: Prediction of the status of the electricity sector (Reference)
Solar
Social
Environment
Economic
Reference
Wind
Alternatives
Geothermal
Biomass
Nuclear
Oil
Coal
Hydropower
Natural Gas
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
Share (/)
Figure 4: Comparison of scenarios with Reference data
1302.7
Nuclear energy, in agreement with the results presented in § 2, confirmed to be a
sustainable energy source whose share was maintained at the same level, as for hydropower,
moving from Reference to a sustainable energy mix. The share of nuclear energy in the
analyzed scenarios, lied in the range 10.8−13.3% with a fifth position in the ranking increased
to the third position in the Social scenario. Amongst renewables, wind proved good
performance in the Social scenario while biomass suffered in the Economic and Social but
was well−performing in the Environmental scenario. The scattering of results for each
alternative is due to the performance in the different dimensions of sustainability and in turn
on the numerical values assumed for the criteria.
The test performed on the Alternatives cluster priority, suggested that, maintaining the
relative importance of the criteria clusters, the results in the Environmental scenario showed
small deviations with, in general, opposite effect on fossil and non−fossil alternatives.
Solar
Wind
Alternatives
Geothermal
Biomass
Nuclear
Oil
1% Alternatives
25% Alternatives
Coal
Hydropower
Natural Gas
0.00
0.05
0.10
0.15
0.20
0.25
0.30
Share (/)
Figure 5: Impact of the Alternatives cluster priority (Environmental scenario)
6
CONCLUSIONS
Economic, social and environmental criteria are fundamental for the evaluation of the
sustainability of an energy mix. Multi−parametric approach is therefore mandatory for the
investigations of new trade−offs between growing energy demand, improving of living
standards and environment.
The paper focuses on the electricity generation sector presenting sustainability
evaluations based on twelve criteria by means of the Analytic Network Process. Consistent
predictions were obtained in reproducing the status of the sector highlighting, in the results of
scenarios, the need for a transition to low carbon technologies. In this frame, nuclear energy
proved to be, in agreement with the conclusions of presented literature, a sustainable source of
energy.
Further investigations on the selection and values of criteria, a more detailed description
of the dependencies between the elements of the system and the use of more complex network
topologies will be carried out in future works.
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ACKNOWLEDGEMENTS
I wish to thank Prof. L. Rossetto (UNIPD) and Prof. A. Lorenzoni (UNIPD) for the
financial support granted to this study (funds of the Doctoral School of Industrial
Engineering, University of Padova).
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