Multi-criteria decision analysis (MCDA) methods have become increasingly popular in decision-making for sustainable energy because of the multi-dimensionality of the sustainability goal and the complexity of socio-economic and biophysical systems. This article reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation. The criteria of energy supply systems are summarized from technical, economic, environmental and social aspects. The weighting methods of criteria are classified into three categories: subjective weighting, objective weighting and combination weighting methods. Several methods based on weighted sum, priority setting, outranking, fuzzy set methodology and their combinations are employed for energy decision-making. It is observed that the investment cost locates the first place in all evaluation criteria and CO2 emission follows closely because of more focuses on environment protection, equal criteria weights are still the most popular weighting method, analytical hierarchy process is the most popular comprehensive MCDA method, and the aggregation methods are helpful to get the rational result in sustainable energy decision-making.

Review on multi-criteria decision analysis aid in sustainable energy decision-making

Solar and Terrestrial Radiation

Energy is vital for sustainable development of any nation – be it social, economic or environment. In the past decade energy consumption has increased exponentially globally. Energy management is crucial for the future economic prosperity and environmental security. Energy is linked to industrial production, agricultural output, health, access to water, population, education, quality of life, etc. Energy demand management is required for proper allocation of the available resources. During the last decade several new techniques are being used for energy demand management to accurately predict the future energy needs. In this paper an attempt is made to review the various energy demand forecasting models. Traditional methods such as time series, regression, econometric, ARIMA as well as soft computing techniques such as fuzzy logic, genetic algorithm, and neural networks are being extensively used for demand side management. Support vector regression, ant colony and particle swarm optimization are new techniques being adopted for energy demand forecasting. Bottom up models such as MARKAL and LEAP are also being used at the national and regional level for energy demand management.

Energy models for demand forecasting—A review

In the current era of sustainable development, energy planning has become complex due to the involvement of multiple benchmarks like technical, social, economic and environmental. This in turn puts major constraints for decision makers to optimize energy alternatives independently and discretely especially in case of rural communities. In addition, topographical limitations concerning renewable energy systems which are mostly distributed in nature, the energy planning becomes more complicated. In such cases, decision analysis plays a vital role for designing such systems by considering various criteria and objectives even at disintegrated levels of electrification. Multiple criteria decision making (MCDM) is a branch of operational research dealing with finding optimal results in complex scenarios including various indicators, conflicting objectives and criteria. This tool is becoming popular in the field of energy planning due to the flexibility it provides to the decision makers to take decisions while considering all the criteria and objectives simultaneously. This article develops an insight into various MCDM techniques, progress made by considering renewable energy applications over MCDM methods and future prospects in this area. An extensive review in the sphere of sustainable energy has been performed by utilizing MCDM technique.

A review of multi criteria decision making (MCDM) towards sustainable renewable energy development

Multiple criteria decision-making (MCDM) is considered as a complex decision-making (DM) tool involving both quantitative and qualitative factors. In recent years, several MCDM techniques and approaches have been suggested to choosing the optimal probable options. The purpose of this article is to systematically review the applications and methodologies of the MCDM techniques and approaches. This study reviewed a total of 393 articles published from 2000 to 2014 in more than 120 peer reviewed journals (extracted from Web of Science). According to experts’ opinion, these articles were grouped into 15 fields. Furthermore, these articles were categorised based on authors, publication date, name of journals, methods, tools, and type of research (MCDM utilising research, MCDM developing research, and MCDM proposing research). The results of this study indicated that in 2013 scholars have published articles more than in other years. In addition, the analytic hierarchy process (AHP) method in the individual tool...

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Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014

Multi-criteria selection for a wind observation station location using analytic hierarchy process

Energy policies require cheap and continuous energy which is needed in Turkey for further development. Implementation of a successful energy policy requires political and economical institutions to take responsibility and to adopt adapt to changes easily. Energy policy generally consists of institutional structure, in which decisions related to technology, economy and energy are made, and also consists of supply–demand management in short term and planning in long term. Energy demand is closely related to social and economic structure of a society. In the long term development of energy demand, developmental structure of society (economic growth, life style, socio-economic factors), technological development and energy prices play important roles as determining factors. In this study, evaluation of most suitable fuel which can be used for residential heating was made using ANP with group decision-making.

Evaluation of alternative fuels for residential heating in Turkey using analytic network process (ANP) with group decision-making

Determination of optimum insulation thicknesses of the external walls and roof (ceiling) for Turkey's different degree-day regions

This study deals with exergoeconomic analysis of a combined heat and power (CHP) system along its main components installed in Eskisehir City of Turkey. Quantitative exergy cost balance for each component and the whole CHP system is considered, while exergy cost generation within the system is determined. The exergetic efficiency of the CHP system is obtained to be 38.33% with 51 475.90 kW electrical power and the maximum exergy consumption between the components of the CHP system is found to be 51 878.82 kW in the combustion chamber. On the other hand, the exergoeconomic analysis results indicate that the unit exergy cost of electrical power produced by the CHP system accounts for 18.51 US$ GW−1. This study demonstrates that exergoeconomic analysis can provide extra information than exergy analysis, and the results from exergoeconomic analysis provide cost-based information, suggesting potential locations for the CHP system improvement. Copyright © 2007 John Wiley & Sons, Ltd.

Haydar Aras

Papers

Multi-criteria selection for a wind observation station location using analytic hierarchy process

Evaluation of alternative fuels for residential heating in Turkey using analytic network process (ANP) with group decision-making

Determination of optimum insulation thicknesses of the external walls and roof (ceiling) for Turkey's different degree-day regions

Exergoeconomic analysis of a combined heat and power (CHP) system

Estimating the horizontal diffuse solar radiation over the Central Anatolia Region of Turkey