A multiple objective decision making model for energy generation portfolio under fuzzy uncertainty: Case study of large scale investor-owned utilities in Florida

作     者：Zeng, Ziqiang Nasri, Ehsan Chini, Abdol Ries, Robert Xu, Jiuping 

作者机构：Sichuan Univ Uncertainty Decis Making Lab Chengdu 610064 Peoples R China Univ Florida Rinker Sch Construct Management Gainesville FL 32611 USA Univ Florida Coll Design Construct & Planning Gainesville FL 32611 USA 

出 版 物：《RENEWABLE ENERGY》 (再生能源)

年 卷 期：2015年第75卷

页      面：224-242页

核心收录：

学科分类：0820[工学-石油与天然气工程] 080703[工学-动力机械及工程] 08[工学] 0807[工学-动力工程及工程热物理] 

基　　金：University of Florida China Scholarship Council (CSC) 

主　　题：Solar PV Energy generation portfolio Investor-owned utilities Failure mode and effects analysis Multiple objective particle swarm optimization 

摘      要：The objective of this paper is to present a methodology to evaluate the viability of developing solar photovoltaic projects for large investor-owned utilities. By taking into account the trade-off between the cost per kWh of electricity generation and total risk for an investor-owned utility, a multi-objective model of the energy generation portfolios is developed. The decision making model can determine the proportion of different energy generation sources in an investor-owned utility portfolio that reduces risk while providing the lowest cost per kWh of electricity generation possible. In order to measure the risk of the investor-owned utility for energy portfolio selection, an investigation of possible dangers and failures of energy generation portfolios is made and 9 main failure modes are identified. The failure mode and effects analysis is employed to calculate the risk priority numbers for each risk. To deal with the uncertainties of the levelized cost of electricity and risk levels of failure modes, the fuzzy method is introduced and an equivalent crisp model is derived which is then solved by employing a multiple objective particle swarm optimization algorithm. The analysis for four large scale investor-owned utilities in Florida is presented to highlight the performance of the developed optimization method. (C) 2014 Elsevier Ltd. All rights reserved.