Portfolio Optimization of Photovoltaic/Battery Energy Storage/Electric Vehicle Charging Stations with Sustainability Perspective Based on Cumulative Prospect Theory and MOPSO

被引：14
作者：
Liu, Jicheng [1 ,2 ]
Dai, Qiongjie [1 ,2 ,3 ]
机构：
[1] North China Elect Power Univ, Sch Econ & Management, Beijing 102206, Peoples R China
[2] North China Elect Power Univ, Beijing Key Lab New Energy & Low Carbon Dev, Beijing 102206, Peoples R China
[3] Ordos Inst Technol, Sch Math & Comp Engn, Ordos 017000, Peoples R China
来源：
SUSTAINABILITY | 2020年 / 12卷 / 03期
基金：
中国国家自然科学基金;
关键词：
portfolio optimization; electric vehicle charging station; photovoltaic; energy storage; sustainability; DECISION-MAKING; SITE SELECTION; DESIGN; FEASIBILITY; NETWORK; SYSTEM; MODEL;
D O I：
10.3390/su12030985
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
Recently, an increasing number of photovoltaic/battery energy storage/electric vehicle charging stations (PBES) have been established in many cities around the world. This paper proposes a PBES portfolio optimization model with a sustainability perspective. First, various decision-making criteria are identified from perspectives of economy, society, and environment. Secondly, the performance of alternatives with respect to each criterion is evaluated in the form of trapezoidal intuitionistic fuzzy numbers (TrIFN). Thirdly, the alternatives are ranked based on cumulative prospect theory. Then, a multi-objective optimization model is built and solved by multi-objective particle swarm optimization (MOPSO) algorithm to determine the optimal PBES portfolio. Finally, a case in South China is studied and a scenario analysis is conducted to verify the effectiveness of the proposed model.
引用
收藏
页数：20
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