A multi-objective decision-making approach for sustainable energy investment planning

被引:71
|
作者
Ervural, Beyzanur Cayir [1 ]
Evren, Ramazan [1 ]
Delen, Dursun [2 ]
机构
[1] Istanbul Tech Univ, Fac Management, Dept Ind Engn, TR-34367 Istanbul, Turkey
[2] Oklahoma State Univ, Dept Management Sci & Informat Syst, Spears Sch Business, Stillwater, OK 74078 USA
关键词
Goal programming; Renewable energy planning; Fuzzy TOPSIS; Analytic Hierarchy Process (AHP); Sensitivity analysis; GOAL PROGRAMMING-MODEL; FUZZY TOPSIS; OPTIMIZATION; LOCATION; SYSTEMS;
D O I
10.1016/j.renene.2018.03.051
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Rapidly growing energy needs require sustainable and efficient utilization of natural resources. Thus, meticulous development of long-term energy strategies and the proper planning of energy resources are critical. In this study, the energy-planning problem is investigated by formulating a multi-objective decision-making model under several realistic constraints. As an illustrative example, an energy company's renewable energy planning model is formulated. Specifically, a multi-objective mathematical model under several constraints (some of which are fuzzy) is developed to attain multiple goals simultaneously. Methodologically, (i) the energy company's plans to invest in renewable energy power plants in specific regions are formulated using a 0-1 goal programming approach, (ii) the social acceptance factor included in the model is obtained using the fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method, and (iii) the goals are weighted by designing and implementing an Analytic Hierarchy Process (AHP) model. According to the results of the developed model, certain renewable energy generation alternatives are superior where the necessary renewable energy resources are efficiently assessed. It is also demonstrated that the proposed integrated analytics approach is capable of providing invaluable insights when the underlying model is systematically evaluated through sensitivity/scenario analyses. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:387 / 402
页数:16
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