Summary Energy has been considered as one of the essential needs of mankind along with air, water, and food and witnessed evolution of civilization since evidence of human life. Managing energy resources is one of the challenging problems being capital intensive. Addressing this involves critical thinking and decision making with all possible aspects, technically known as set of primary and secondary criteria. There exist a number of literature sources addressing applications of multicriteria decision‐making (MCDM) in different energy‐related areas. Some are focusing on energy policy making, few are explaining site selection of solar PV, wind farm, and hydro power plants, and a few are describing applications in load management. Moreover, a few literature in this field elaborates various MCDM methods and their applications. In this article, an extensive and exhaustive study is carried out incorporating almost all possible applications of MCDM in renewable energy area. Various energy‐intensive applications are mapped with MCDM methods along with governing sensitive parameters. Hence, this study facilitates practicing engineers, decision‐makers, academician, and researchers to identify areas and MCDM techniques researched over the past decade in energy sector for planning, managing, selecting renewable resources, etc.
Aim:The objective of this study is to facilitate decision makers' selection of groups of components for isolated microgrid which should not only be economically attractive and efficient but also acceptable from various aspects. The microgrid is designed to serve a rural remote region of Tanzania with an approximate energy demand of 1000 kWh/day. Methods: A comprehensive comparison has been presented using (Hybrid Optimization Model for Electric Renewable) HOMER Pro software and fuzzy analytic hierarchy process (AHP)-based multi-criteria decisionmaking (MCDM) (fuzzy-AHP-MCDM) technique for planning of isolated microgrid systems which is formed by using a group of sources, like photo-voltaic (PV) generator, wind-turbine, micro-hydro, bio-gas based generation and battery storage system. In this study, ten various alternatives comprising a blend of the aforementioned sources have been considered. A group of households having an approximate load demand of 1000 kWh/day located near Arusha in Tanzania has been selected for this study.Results: A levelized cost of energy of 0.0694 $/kWh has been found for the optimized case using HOMER Pro comprising all five aforesaid components. Conclusion:The fuzzy-AHP-MCDM technique also exhibits highest priority for a similar combination when only the economic criteria are considered and all other criteria are being suppressed significantly. On the other side, a different group consisting only PV and wind-based generation is found prioritized when all criteria are taken
The planning stage of any project, could it be for an industry, a commercial or energy supply system, has crucial significance and involves judicious contribution from field experts to decision makers (DM). The objective of this paper is presenting a model for planning of energy sources for microgrid using multi-criteria decision making (MCDM) based on analytic hierarchic process (AHP) approach. For developing a model, an educational institution's electrical energy load demand has been considered as reference. In this assessment, the main-utility grid as the primary source of electricity, alongside conventional sources like diesel generator (DG), gasbased combined heat-and-power (CHP) with absorption chiller to meet cooling demand of facility is taken into account. Moreover, proven and comparatively most environmentally friendly renewable energy sources, such as solar photovoltaic (PV) together with battery energy storage system (BESS) have been taken into account. Moreover, the assessment and evaluation for prioritization of energy sources based on critical criteria or attributes and their associated sub-criteria have been judged to make decision. In this model, most of the critically influencing criteria, such as economic, technical, structural, operational and maintenance, environmental and societal aspects are being focused on. In total, nine alternativescombinations of grid and other energy source(s)-are identified to form the microgrid. The weight score for each combination of sources is computed for each of the 22 criteria and could be presented DMs to enlist priority of alternatives to choose from.
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