[Lecture, Dec 06] Comparative analysis of MCDM methods for ranking renewable energy
time: 2018-11-30

Title:Comparative analysis of MCDM methods for ranking renewable energy

Speaker: Professor Ching-Ter Chang, Chang Gung University

Time: 9:00 am, December 6, 2018

Venue: Room 208, School of Business Administration Office Building, Wushan Campus

Introduction to the Speaker:

Dr. Chang Ching-Ter received his PhD from Chiao Tung University and is currently a professor in Chang Gung University. His research covers various areas including Information Management, Digital Application, Renewable Energy Supply Chain, Operation Management, Innovation Management, and Big Data. His research projects in these areas have received more than ten grants from the Department of Science and Technology. Prof. Chang has published nearly one hundred of academic papers in international journals such as IEEE/ACM Transactions on Networking, IEEE Transactions on Fuzzy Systems, European Journal of Operational Research, Renewable & Sustainable Energy Review, Transportation Research Part A, Transportation Research Part E, OMEGA, Neural Network, Journal of the Operational Research Society, and International Journal of Production Economics, etc. He also serves as editorial board member or referee for more than ten international peer-reviewed journals.


Multi-criteria decision making (MCDM) methods are becoming increasingly popular in solving energy selection problems because these problems involve multiple and often conflicting criteria. This paper presents comparative analysis of ranking renewable energy sources (RES) for electricity generation in Taiwan using four MCDM methods - WSM, VIKOR, TOPSIS, and ELECTRE. The purpose of this study is to rank the priorities of various RES and propose recommendations for Taiwan's RE development. The ranking results show that hydro is the best alternative in Taiwan, followed by solar, wind, biomass and geothermal. Furthermore, sensitivity analysis of the weights was conducted considering the ranking results heavily depend on the criteria weight. The results of sensitivity analysis indicated that when financial or technical aspects are focused upon, hydropower is the best RES because its technology is the most mature and the cost is the lowest in Taiwan. In addition, from an environmental perspective, wind energy is the best choice, and from the social perspective, solar PV is the best choice. The findings of this study can provide useful information to energy decision makers and serve as a reference for Taiwan's energy policy.