Review on multi-criteria decision analysis aid in sustainable energy decision-making
Introduction
Energy including renewable energy and geologic storages is an essential input to all forms of economic and social activities as shown in Fig. 1. Energy system plays an important role in the economic and social development of a country and the living quality of people [1], [2]. The major energy demand of fossil fuels has major consequences around the world. A main environmental problem is the emission of toxic chemical pollutants, greenhouse gases like CO2 and other air pollutants [3], [4]. These cause climate change and environmental pollution of air, land and water, which has a negative impact on the health and the living quality of humans [5]. Contrarily, global environmental issues could significantly affect patterns of energy use around the world [6]. Some new governmental policies have been adopted to encourage the introduction of energy efficiency measures, the technical changes, and the renewable and sustainable energy [3], [7], [8].
The sustainable development has been the subject of wide-ranging discussion and debate within government, non-government and academic circles, being a major focus of national and international economic, social and environmental agendas [3], [4], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18]. Sustainable development means the satisfaction of present needs without compromising the ability of future generations to meet their own needs [19]. Sustainability can be seen as the final goal: a balance of social and economic activities and the environment [9]. A sustainable energy sector has a balance of energy production and consumption and has no, or minimal, negative impact on the environment (within the environmental tolerance limits), but gives the opportunity for a country to employ its social and economic activities.
The rational decision-making (DM) in energy supply system options, planning, management and economy is helpful to the sustainable development. However, the complex interactions shown in Fig. 1 make DM more difficult. Sustainable energy decision-making using multi-criteria decision analysis (MCDA) just provides a method to eliminate the difficulty and it has attracted the attention of decision makers for a long time. MCDA is a form of integrated sustainability evaluation. It is an operational evaluation and decision support approach that is suitable for addressing complex problems featuring high uncertainty, conflicting objectives, different forms of data and information, multi interests and perspectives, and the accounting for complex and evolving biophysical and socio-economic systems. The methods can provide solutions to increase complex energy management problems. Traditional single criteria approach is normally aimed at identifying the most efficient options at a low cost. Growing environmental awareness in the 1980s has slightly modified the single criteria decision framework. Nowadays, the focus on global environmental protection drives MCDA aid in energy systems. The MCDA methods have been widely applied to social, economic, agricultural, industrial, ecological and biological systems in addition to energy systems [20], [21], [22], [23], [24], [25], [26], [27]. Compared to single criteria approach, the distinctive advantage of MCDA methods is to employ multi-criteria or attributes to obtain an integrated DM result.
Generally, the MCDA problem for sustainable energy DM involves m alternatives evaluated on n criteria. The grouped decision matrix can be expressed as follows:where xij is the performance of j-th criteria of i-th alternative, is the weight of criteria j, n is the number of criteria and m is the number of alternatives (these nomenclatures are just the same in this article).
It can be found that the DM problem involves alternatives, criteria, criteria weights and the evaluating result from Eq. (1). The corresponding DM process can be formed to Fig. 2 [28], [29]. It usually includes four main stages: alternatives’ formulation and criteria selection, criteria weighting, evaluation, and final treatment and aggregation. The preliminary step in MCDA is to formulate the alternatives for sustainable energy DM problem from a set of selected criteria and to normalize the original data of criteria. Secondly, criteria weights are determined to show the relative importance of criteria in MCDA. Then, the acceptable alternatives are ranked by MCDA methods with criteria weights. Finally, the alternatives’ ranking is ordered. If all alternatives’ ranking orders in different MCDA methods are just the same, the DM process is ended. Otherwise, the ranking results are aggregated again and the best scheme is selected. The four main sections in MCDA are presented and reviewed in Sections 2–5 respectively.
Section snippets
Literature review on criteria in energy DM
The energy issues applying MCDA includes energy planning and selection [11], [12], [13], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], energy resource allocation [48], [49], [50], [51], [52], [53], [54], energy exploitation [55], [56], energy policy [57], [58], [59], building energy management [60], [61], [62], [63], [64], [65], [66], [67], transportation energy systems [68], [69] and others [70], [71], [72], [73], [74], [75]. The
Weighting methods
All factors have their internal impact reclassified to a common scale so that it is necessary to determine each criteria's relative impact in the sustainable energy DM problem. Weight is assigned to the criteria to indicate its relative importance. Different weights influence directly the DM results of energy systems’ alternatives. Consequently, it is necessary to obtain the rationality and veracity of criteria weights. Three factors are usually considered to obtain the weights: the variance
Multi-criteria decision analysis methods
It is the turn to determine the preference orders of alternative after determining the criteria weights so that MCAD methods are employed to get the ranking order in Eq. (1). In the referred literatures, the listed MCDA methods in Table 5 were mainly applied in all kinds of sustainable energy DM problems [11], [13], [29], [30], [32], [33], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [49], [50], [52], [54], [55], [57], [60], [65], [66], [71], [72], [73], [74],
Aggregation methods
Usually, the decision maker selects the best alternative based on the ranking orders after the calculation in a selected MCDA method. However, the creditability of DM is necessarily verified so that the results of the ranking orders are computed by a few MCDA methods sometimes. The application of various MCDA methods of calculation may yield different results (preference ranking order). The question “Which method is most suitable to solve the problem?” is most important, but difficult to
Conclusion
A review of the published literature on sustainable energy decision-making presented here indicates greater applicability of MCDA methods in changed socio-economic scenario and leads to the following conclusions:
- (1)
Multi-attributes considered in the sustainable energy decision-making gains increasing popularity. It can be observed that efficiency, investment cost, CO2 emission and job creation are the most common criteria in the technical, economic, environmental and social attributes
Acknowledgement
This research has been supported by the Key Laboratory of Condition Monitoring and Control for Power Plant Equipment of Ministry of Education, China.
References (139)
- et al.
Energy consumption and economic growth: evidence from China at both aggregated and disaggregated levels
Energy Economics
(2008) - et al.
Energy consumption and income in G-7 countries
Journal of Policy Modeling
(2006) - et al.
Global warming and renewable energy sources for sustainable development: a case study in Turkey
Renewable and Sustainable Energy Reviews
(2008) - et al.
environment and sustainable development
Renewable and Sustainable Energy Reviews
(2008) - et al.
Impact of urban temperature on energy consumption of Hong Kong
Energy
(2006) Energy efficiency and renewable technologies: the way to sustainable energy future
Desalination
(2007)- et al.
The promotion of sustainable development in China through the optimization of a tax/subsidy plan among HFC and power generation CDM projects
Energy Policy
(2007) - et al.
Canada's energy perspectives and policies for sustainable development
Applied Energy
(2009) - et al.
Energy in Brazil: toward sustainable development?
Energy Policy
(2008) - et al.
Sustainable development of the Belgrade energy system
Energy
(2009)