Energy Planning

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Loken (2007) indicates that the decision making process in the energy sector requires that the various conflicting objectives involved to be considered. To Loken (2007), “multiple criterion decision analysis (MCDA) describes various methods developed for aiding decision makers in reaching better decisions” (pg. 1584). It is opined that the problems of energy planning are absolutely complicated and require multiple criteria and many decision makes for them to be resolved. On that regard, multiple criterion decision analysis is recommended for the resolution of the energy plans. Considering that the multiple criteria decision analysis methods exists, it would very easy to resolve any issues that exist in the energy planning processes. Loken (2007, 1584) notes that, “these methods can be divided into in three main groups; value measurement models, goal, aspiration and reference level models, and outranking models”.

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Loken’s article used the MCDA criteria methods to address the energy planning problems such as optional electricity transmission strategies. This article notes that the various MCDA criteria methods cannot be ruled in as totally reliable as they have strengths as well as drawbacks. The article used the MCDA criteria methods as the independent variable and energy planning decision making as the dependent variable. The article notes that the energy planning has been mostly been evaluated using a single energy carrier, which limits the resolution of the planning problems. It is concluded that advanced energy systems should be used to ensure that the energy planning problem however complex it is, is resolved. The article further indicates that the energy planning is complex and has conflicting criteria, which requires the use of advanced MCDA optimization methods.

Another article by Pohekar and Ramachandran (2004) postulates that sustainable energy planning could only be achieved through the utilization of multi-criteria decision making (MCDM). This study notes that the management of sustainable energy is gaining popularity and significance globally and could be achieved through the use of mixed decision making criteria. To Pohekar and Ramachandran (2004), energy planning involves multiple and conflicting objectives, which makes it hard to solve the underlying problems. This article was based on the review of previous published articles dealing with energy planning and used energy planning as the dependent variable and MCDM as the independent variable.

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The study by Pohekar and Ramachandran (2004) noted that fuzzy principles, outranking, priority setting, and weighted averages are quite crucial when combined for use in the energy planning process. The article found out that the Analytical Hierarchy Process was the most used technique in the resolution of the energy planning problems. Multiple method results’ validation, fuzzy methods applications, and the evolution of the synergistic decision support systems remains the best combination of MCDMs in the resolution of energy planning data uncertainties. Based on this study, it is concluded that the energy planning problem could only be resolved through the application and the adoption of multi criteria decision making methods, which allow for the elimination of the conflicting objectives that are present in the energy planning processes. The outranking techniques of making decisions were also found to be quite iterative in the multi-criteria decision making in the energy sector.

Wang, Jing, Zhang, and Zhao (2009) reiterate the importance of multi-criteria decision analysis (MCDA) on making decision inclined to the sustainable energy planning. This study notes that the biophysical and socioeconomic systems are complex while the sustainability goal is multidimensional, which makes it easier for the adoption of the MCDA methods required in the solution of problems involved in the energy planning process. This study looked into the methods compatible with the MCDA including final aggregation, evaluation, critical weighting and selection. Energy supply should be based on the social, environmental, economic, and technical aspects inasmuch as criteria selection is concerned.

To Wang, Jing, Zhang, and Zhao (2009), the different forms of weighting criteria exist and they are either subjective, objective, or combined. Energy decision making is implemented through the combination of various methods that are arrived at by leveraging on fuzzy set methodology, outranking, priority setting, and weighted sum. In the evaluation criteria, the investment cost is prioritized in the decision making, which is followed by the emission of the carbon dioxide. It is indicated that the environment protection and the cost of investing are the most weighted criteria and are very crucial in the energy planning process. This study also concluded that the analytical hierarchy process remains the most viable MCDA in the energy decision making. However, it is also important to note that to get rational result in the sustainability of energy aggregation methods are required.

Velasquez and Hester (2013) did an analysis on the MCDM methods and indicated that they have been revolutionized to fit in their responsibility of solving the managerial and planning problems.  The methods of criteria decision making have their advantages and disadvantages, which explains why they have to be combined so that they can perform effectively. Although this study was not aligned to the energy sector, it provides a platform for the analysis of which MCDM method to use in the energy planning processes. Velasquez and Hester (2013) note that the various multi-criteria decision making methods should be well analyzed before they are utilized for particular situational problem solution.

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This study did not have a particular methodological approach neither did it have particular variables but leveraged on a literature review of the different MCDM methods. Velasquez and Hester (2013) did not recommend any decision making method as being the best though they provided a resourceful analysis of the available techniques. However, for the purposes of this paper, “multi-attribute theory, analytic hierarchy process, simple multi-attribute rating technique, goal programming, ELECTRE, PROMETHEE, and simple additive weighting” were identifies as the most useful MCDM methods for use in the energy planning process (Velasquez & Hester, 2013, 63-64). The decision making methods provided in this study were found to be very effective in the improvement and evolution processes of solving problems. In line with that argument, the identified decision making methods remain a very vital part of the energy planning process.

Kaya and Kahraman (2011) agree that the energy planning process is quite complicated since it involves the social, environmental, economic, and technical aspects for an enhanced problem solution process.  Their article indicates that selecting the most complete energy technology encapsulates the thoughtful decision over the infringing qualitative and quantitative evaluation criteria (Kaya & Kahraman, 2011). The article indicates that decision makers have to be certain for them to be able to give the correct numerical values connected to the energy planning process. The study recommends the use of fuzzy set theory too deal with the looming uncertainties whenever information related to the energy planning process turns out to be vague and incomplete. Through the use of linguistic terms, as recommended in this study, fuzzy theory can be very effective in energy planning processes.

Kaya and Kahraman (2011) note that, the use of fuzzy TOPSIS methodology is very crucial when dealing with the choice of an alternative technology to be used in the energy planning processes. TOPSIS methodology allows energy planners to decide on the best alternative whenever a choice over technology has to be made. The article, further, notes that the methodology calculates the positive and negative distance of an alternative based on the scores provided by a panel of energy experts. The fuzzy pairwise comparison matrix is used to determine the selection criteria weights. By calculating the selection criteria weights, the energy experts are able to make decisions regarding the alternative technologies. It was concluded that the fuzzy methodology was an iterative tool in solving the energy planning puzzle.

Tsoutsos, Drandaki, Frantzeskaki, Iosifidis, and Kiosses (2009) did a study on the sustainable energy planning by leveraging on the case study of Crete Island in Greece. In this study a number of energy planning issues were raised. The authors found out that for sustainability in the energy sector, the management of social, environmental, economic, and technological information was crucial in the development of a sustainable energy sector. The study found out that the traditional evaluation methods were insufficient in the development of a sustainable energy plan. Based on that argument multi-criteria methods are required for the development a sufficient and sustainable energy plan. The research noted that the multiple criteria methods are iterative in the development of a sustainable energy plan as they allow for the handling and assemblage of an extensive range of variables to effect valid decision supports.

In its evaluation of the Crete’s sustainable energy plan, the study found out that the multiple criteria methodology allowed for the development of a sufficiently sustainable energy plan. Through the utilization of the tool, Crete Island was able to assess its implementation of the renewable energy sources against the criteria variables that are found in the energy planning field. It was concluded that the multiple criteria methodology was sufficient in the development of alternatives necessary for the development of a sustainable energy plan. The multiple criteria methodology is effective in the exploration of alternatives that would support a smooth energy planning process.

Kahraman and Kaya (2010) indicated that coming up with the correct energy policy is an overly important decision since it affects the environment and economic development. The correct energy policy selection allows the economic development to take shape while also ensuring that the environment is conserved and maintained to sustainable standards. Their study found out that the recently conducted studies have been consistently looking for the selection of the most effective energy policy while also calculating the most imperative energy alternatives. The study also indicated that the studies mostly use the fuzzy and multi-criteria approaches to come up with their conclusion. On that basis, Kahraman and Kaya (2010) found out that the fuzzy set theory is one of the most iterative approach used to deal with uncertainties in the energy planning processes, especially whenever the information provided to a panel of experts is vague and incomplete.

To Kahraman and Kaya (2010), “a fuzzy multi-criteria decision making methodology is suggested for the selection among energy policies” (pg.6270). Their study concluded that the recommended approach is allows for fuzziness in the analytic hierarchy process. This indicates that it allows for the scores provided by experts to be evaluated into crisp numbers and linguistic expression. In this case, the decision regarding the selection of an energy policy is made quite easy and fast. The easy determination of an energy policy using this methodological approach allows the fuzzy multi-criteria decision making to be very crucial in the energy planning process. The application of the fuzzy approach allows for the determination of the best energy policy in any given economy.

Kowalski, Stagl, Madlener, and Oman (2009) looked into the methodological approaches that would arise whenever participatory multi-criteria analysis (PMCA) was combined with scenario in the development of a sustainable energy plan. The study, which was aligned to renewable energy, indicated that scenarios’ analyses have been overly used whenever experts were making long term projections regarding the future energy pathway. The study also argued that the multi-criteria analysis has been very iterative in the appraisal and assessing of different options based on the rankings and a criteria framework.  The study used the case of Austria in which case five scenarios were given an appraisal against seventeen sustainability criteria. The study noted that the scenario development was divided into exploratory and modeling stages, which encapsulated forecasting.

The study found out that the scenario development which was partly narrative and partly modeled also involved the stakeholder’s preferences, which were participatory in nature. The study did an analysis of using this methodology in the development of the energy plans and found out that an assessment of scenarios using the PMCA was resource intensive. However, irrespective of the resource intensive challenge, the approach of assessing scenarios with PMCA was successful in the capturing technology realignment. The methodology also gives room for the most robust and democratic decision making process, which is very crucial in the energy planning process. To enhance its efficiency, this methodological approach deals with uncertainties while also improving the social learning during the procedure (Kowalski, Stagl, Madlener & Omann, 2009).

Mourmouris and Potolias (2013) did an analysis on the effectiveness of the multi-criteria methodological approach in the energy planning by leveraging on a renewable energy development project in Thassos, Greece. The paper reiterated the importance of rational planning in the wake of economic and environmental pressure. The study allowed proposed the use of an evaluational framework as a way of enhancing the energy planning for the development of renewable sources projects. The study found out that the development of such a plan cannot be achieved without the adoption of the multi-criteria decision analysis, which allowed for the evaluation of renewable energy sources. The people aimed at analysis the multi-level decision making using multiple criteria energy planning.

The framework of the study was based on the evaluation of the project using a multi-criteria methodological approach to support any energy planning process in the identified sector. However, the study also had another aim in which it evaluated the total amount of energy that could be produced in the identified region with a view of improving the energy mix. Through the combination of an evaluational framework and the multi-criteria decision analysis, the study was able to evaluate the total energy that could be produced in Thassos using renewable sources. The results are a clear revelation that multi-criteria decision analysis allows for the optimization of the energy planning process. The study concluded that environmental-friendly renewable sources had to be adopted for the optimal renewable energy to be realized.

San Cristóbal (2011) introduces a relatively new multi-criteria decision making method in the selection of a renewable energy project in Spain. The study notes that Spain had a shortage in terms of its energy sources and the government needed to move in fast and plan for a renewable energy production project to cater for the shortage. In this case, the energy planning had to be done in such a way that it put into consideration all the conflicting objectives due to the presence of environmental, technological, social, and economic factors. The article notes that the erst single-criterion decision-making in the energy planning may not be able to deal with the current challenges, which makes VIKOR or compromise ranking method as one the most iterative multi-criteria optimization tools to deal with the challenge.

The VIKOR method allows for multi-criteria decision making through measuring of whether a specific solution is close to being ideal. In this case study, VIKOR is combined with the analytic hierarchy process to enhance the weighting of the different criteria involved in the decision making. Through the combination and the use of the two multi-criteria decision making tools, the study was able to find out that a biomass plant option was the best for increasing power production in Spain (San Cristóbal, 2011). The study’s conclusion is a clear indication that the multi-criteria decision making decision tools were vital in ensuring that the energy planning processes were smooth and effective.

Stein (2013) did a research that would be used by the decision makers in the ranking of various electricity production technologies by leveraging on multiple criteria. The study developed a model that would rank both the renewable and non-renewable electricity production methods with a consideration to the objective factors; socio-economic-political, environmental, technical, and economic. To enhance the development of this multi criteria optimization model, the researcher used the analytic hierarchy process while using the empirical data that was available in the academic and government sources (Stein, 2013). The study found out that the geothermal, hydropower, solar and wind as the energy sources that provided the most benefits. The ranking remained the same even when the sensitivity analysis was used to adjust the primary criteria clusters’ weights.

The study, further, indicated that based on the multi-criteria ranking model the only non-renewable sources that were found to provide benefits were gas and oil. The results were found to have a relative implication the decisions made by experts regarding the energy policies. Based on this research, it was recommended that the financial funding for renewable sources of energy projects to be increased significantly while that of non-renewable sources to be slashed. However, the study indicates that it provided a room for an expansion to the sensitivity analyses as a way of ensuring that an optimal mix of production technologies is arrived at. This study is an epitome of the importance of using the multi-criteria decision making analysis in the solution of challenges related to energy planning processes.

Buchholz, Rametsteiner, Volk, and Luzadis (2009) did a research on how multi-criteria analysis was imperative in the assessment of bioenergy assessments. Their study indicated that sustainable energy systems were encapsulated in the environmental, economic, and social aspects as well as requiring the input of multi-variate stakeholders, which made their planning a complicated issue. The complexity of planning the projects provided a great barrier in their implementation. Their study aimed at analyzing how multi-criteria analysis (MCA) played a role in ensuring that the design and implementation of bioenergy projects was successful. Four MCA tools were reviewed to evaluate their effectiveness in assessing whether multi-stakeholder bioenergy projects in Uganda were sustainable.

The study found out that in as much as the MCA tools were crucial in enhancing the decision making processes, they were also vital in limiting and reducing any projects’ implementation barriers (Buchholz, Rametsteiner, Volk & Luzadis, 2009). That analysis tools were able to structure the existing problem, identify the robust and uncertain bioenergy systems components, and including the multi stakeholders in the process of making decisions. However, the study noted that the different tools providing varying outcomes since they applied disparate approaches. Nonetheless, the study concluded that the multi criteria analysis tools were vital in ensuring that the decision made during the energy planning processes were quite critical in the optimization of projects. The study, therefore, recommends that for a successful implementation of a sustainable multi-stakeholder bioenergy system project, multi-criteria analysis tools have to be used to delimit the implementation challenges.

In still another study, Scott, Ho, and Dey (2012) defined bioenergy technology as a complex and multifaceted scheme that was rocked by challenges of having multi-variate raw materials, technical options, conflicting opinions from the different stakeholders. The research indicated that the implementation of a successful bioenergy scheme required the satisfaction and consideration of a variety of requirements. To achieve its objective, the study reviewed previous scholarly works that had concentrated on using multi-criteria decision-making methods that had been used in dealing with the challenge of setting up bioenergy schemes. The study notes that the MCDM methods are not only related to bioenergy but could also apply to other energy production technologies. This is a clear indication that multi-criteria decision-making tools were vital in ensuring that the energy planning processes were optimized and made smooth.

The study reviewed journals submitted between 2000 and 2010 to gather and review information related to the MCDM methods. The study sought to find out which methods are mostly used and the energy planning problems that were mostly addressed by researchers. The paper concluded that most multiple criteria optimization methods concentrated on choosing a technique that dealt with the identification of few energy alternatives (Scott, Ho & Dey, 2012). A few of the reviewed papers showed attention of optimization methods that were used in choosing between lots of energy alternatives. The review found out that most journals sought to address the problem of the technology to be used during the energy planning process. Policy decisions were also found to be a major issue that researchers of energy optimization dealt with in the course of their studies. This indicates that the multi-criteria energy optimization method remains an iterative tool in solving the energy planning puzzle.

Zeng et al. (2011) conducted a research on the optimization of modeling of energy systems planning and GGH emission mitigation under uncertainty. Notably, the researcher sought to solve the issue of energy resources being consumed whilst the issues of sustainability are not being addressed amongst other problems as well. The goal of the research was to come up with solutions that would help planners and the decision makers to make strategic plans on how to handle energy management systems when dealing with GHG emissions mitigation (Zeng et al., 2011). More so, the researcher targets environmental professionals and other energy-related professionals.

The researcher uses integer and continuous variables in their description of the energy demands. These variables represent the energy flows as well as discrete energy technologies as well (Zeng et al., 2011). These are the main decision variables in the research study. The study optimizes fuzzy objective functions which are delimited by certain constraints especially those that have a fuzzy coefficient. The researchers analyzes a number of methodologies in the study: the optimization modeling of the mitigation of GHG emission, optimization modeling of those energy systems plans that are under uncertainty, and the examination of the model-based decision support tools.

Zeng et al. (2011) discusses the many potential alternatives that can be used in decision making when planning energy. The author goes ahead to note that it is critical that expert systems and decision support tools be used to facilitate the decision-making process. Examples of how multi-criteria have been employed in the past are also given. For instance a decision support system (DSS) for operation planning was developed in the past in order to assist decision makers plan the management of multi-scale energy systems.

The findings of the study show that the main solution to the issue at hand is for the decision makers to systematically evaluate the economic and environmental performance of the energy technologies (Zeng et al., 2011). They should also consider the services, technologies and make a strategic choice when it comes to the desired plans for the EMSs. It is recommended that expert systems together with decision support systems be employed (Zeng et al., 2011). Notably, these tools should be based on scientific modeling.

In the study carried out by Polatidis et al. (2003), the issues of environmental problems that are associated with nuclear and fossil power utilization and production are discussed. Apparently, these problems have become a menace in the world as it is. The goals of the research by Polatidis et al. (2003) is to come up with solution with the development of a renewable energy sources as the main solution. Notably, the solution needed has to present a sustainable approach to the utilization of the fossil and nuclear energies. It is noted in the study that a combination of an Integrated Assessment (IA), Multi-Criteria Analysis (MCA), and Transition Management (TM) in a planning framework could lead to a more sustainable energy system that has a significant RES contribution.

As noted by Polatidis et al. (2003), the Multiple Criteria Analysis Techniques provides a sound methodological framework that can be used to evaluate and appraise renewable energy. In this analysis, the researcher’s goals were to employ a decision-making framework that is multi-criteria. Such a framework would provide a powerful instrument that would be used to define evaluation criteria and alternatives to the issues. System changes are recommended in the study which includes system optimization that involves the incremental change in the energy efficiency.

Polatidis et al. (2003) discusses three conceptual frameworks which can be combined to form a new approach that is contemporary when planning energy management. These frameworks are Integrated Assessment, Multi-Criteria Analysis and Transition Management. Apparently, this integrated form of assessment is considered to be structured to allow the handling of complex issues in energy management. Furthermore, Polatidis et al. (2003) notes that this ideology allows for the testing of the level of effectiveness of the different policies on energy management that have been put in place.

Conclusively, the researcher determines that the decision making frameworks and the MCA are critical towards the provision of a function that will help with the energy planning. Notably, these provide a function that provides a framework that is coherent and consistent. This framework can be used to gather and analyze information before making decisions. On the other hand, these offer an opportunity for the quantification of the social changes that are related to the energy shift.

According to Wagh and Kulkarni (2016), the living standard in the world have changed with the changing economies. As a result, there is more pressure on the energy requirements in the whole world.  In search for a solution to the issues, many countries have opted to go the renewable and sustainable energy route. However, there is an issue with how these countries are managing their energy. The researcher carried out a study to determine the best course of action and how to best solve the issue at hand. It is proposed in the study that forecasts should be done on the energy sources. The information that would then be collected from such forecasts could be used in the decision making process on how to manage the energy sources.

The study employs multi-objective models. This method seeks to determine the best method that can lead to the optimal hybrid system that will then be used for the management of the energy systems (Wagh & Kulkarni, 2016). Notably, spartia and routing functions are critical in this method. The energetics as well as contradicting elements are integrated into one in order to present a system that will account for the different spatial levels. In conclusion, the researcher proposed the application of energy management systems that will employ decision making in s strategic way. Such a system will facilitate the strategic management of the energy sources. More so, the multi criteria analysis provides a sound methodological approach towards the solution of the issue at hand.

The study brings out the fact that various forecasting models are used on energy planning. These models include MARKAL simulations, LEAP (Long range Energy Alternatives Planning System) and regression analysis are the most common tools that are being used by most researchers. The researcher also notes that gross income, GNP, GDP, per capita income, energy security and energy production are key factors that are considered in the modeling with the intention of forecasting for energy planning. However, it is noted that these methods are not sufficient in the energy planning. Nonetheless, different models have been implemented in the recent past with the intention of assisting with the energy planning. Some of these models are short term, others are long-term.

The main purpose of the research carried out by Mardani et al. (2015), is to present a review of the MCDM techniques and approaches that can be used in the solving of problems with renewable and sustainable energy system. The researches goal is to advocate for the use of decision making analysis systems with the goal of making strategic decisions. This research study sought to determine the effect of the application of certain methods in the management of renewable and sustainable energy. The study proposed that different MCDM approaches should be used together.

The study reviews papers that used a variety of methods. These include AHP, F-AHP, ANP, and TOPSIS. Other paper also included integrated methods.  Notably, the MCDM methods such as MCDA (multiple criteria decision making analysis) are used in the study. Notably, those energy issues that apply the decision making (DM) methods are noted to include selection and planning (Mardani et al., 2015). Multiple Criteria Complex Proportional Assessment method (COPRAS) is also noted to be among other methods that are critical towards the solving of MCDM issues. More so, it has been proposed that complete aggregation should be carried out.

The findings of the study indicate that MCDM techniques and approaches are suitable for energy systems.  Mardani et al. (2015) notes that there are a variety of MCDM techniques that can be used to solve issue with energy renewable and sustainable energy systems. It is noted that there might be some drawback to these approaches but the overall effect is that the systems will be managed in a better way. The systems field will be better with the incorporation of the proposed methods.

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  1. Buchholz, T., Rametsteiner, E., Volk, T., & Luzadis, V. (2009). Multi Criteria Analysis for bioenergy systems assessments. Energy Policy37(2), 484-495.
  2. Kahraman, C., & Kaya, İ. (2010). A fuzzy multicriteria methodology for selection among energy alternatives. Expert Systems With Applications37(9), 6270-6281.
  3. Kaya, T., & Kahraman, C. (2011). Multicriteria decision making in energy planning using a modified fuzzy TOPSIS methodology. Expert Systems With Applications38(6), 6577-6585.
  4. Kowalski, K., Stagl, S., Madlener, R., & Omann, I. (2009). Sustainable energy futures: Methodological challenges in combining scenarios and participatory multi-criteria analysis. European Journal Of Operational Research197(3), 1063-1074.
  5. LOKEN, E. (2007). Use of multicriteria decision analysis methods for energy planning problems. Renewable And Sustainable Energy Reviews11(7), 1584-1595.
  6. Mardani, A., Jusoh, A., Zavadskas, E. K., Cavallaro, F., & Khalifah, Z. (2015). Sustainable and renewable energy: An overview of the application of multiple criteria decision making techniques and approaches. Sustainability7(10), 13947-13984.
  7. Mourmouris, J., & Potolias, C. (2013). A multi-criteria methodology for energy planning and developing renewable energy sources at a regional level: A case study Thassos, Greece. Energy Policy52, 522-530.
  8. Pohekar, S., & Ramachandran, M. (2004). Application of multi-criteria decision making to sustainable energy planning—A review. Renewable And Sustainable Energy Reviews8(4), 365-381.
  9. Polatidis, H., Haralambopoulos, D. A., Kemp, R., & Rothman, D. (2003). Creating an energy system that we want but don’t know yet, using integrated assessment, transition management and multi-criteria analysis. Integrated Assessment4(3), 205-213.
  10. San Cristóbal, J. (2011). Multi-criteria decision-making in the selection of a renewable energy project in spain: The Vikor method. Renewable Energy36(2), 498-502.
  11. Scott, J., Ho, W., & Dey, P. (2012). A review of multi-criteria decision-making methods for bioenergy systems. Energy42(1), 146-156.
  12. Stein, E. (2013). A comprehensive multi-criteria model to rank electric energy production technologies. Renewable And Sustainable Energy Reviews22, 640-654.
  13. Tsoutsos, T., Drandaki, M., Frantzeskaki, N., Iosifidis, E., & Kiosses, I. (2009). Sustainable energy planning by using multi-criteria analysis application in the island of Crete. Energy Policy37(5), 1587-1600.
  14. Velasquez, M., & Hester, P. (2013). An Analysis of Multi-Criteria Decision Making Methods. International Journal Of Operations Research10(2), 56-66.
  15. Wagh, M. M., & Kulkarni, V. V. (2016). Modeling and Optimization of Integration of Renewable Energy Resources (RER) for Minimum Energy Cost, Minimum CO2 Emissions and Sustainable Development, in Recent Years: A.
  16. Wang, J., Jing, Y., Zhang, C., & Zhao, J. (2009). Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renewable And Sustainable Energy Reviews13(9), 2263-2278.
  17. Zeng, Y., Cai, Y., Huang, G., & Dai, J. (2011). A review on optimization modeling of energy systems planning and GHG emission mitigation under uncertainty. Energies4(10), 1624-1656.
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