Multi-objective optimal design of hybrid renewable energy system under multiple scenarios

被引:67
作者
Wang, Rui [1 ]
Xiong, Jian [2 ]
He, Min-fan [3 ]
Gao, Liang [4 ]
Wang, Ling [5 ]
机构
[1] Natl Univ Def Technol, Coll Syst Engn, Changsha 410073, Peoples R China
[2] Southwestern Univ Finance & Econ, Sch Business Adm, Chengdu 610074, Peoples R China
[3] Foshan Univ, Sch Math & Big Data, Foshan 528000, Peoples R China
[4] Huazhong Univ Sci & Technol, Sch Mech Sci & Engn, Wuhan, Peoples R China
[5] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Optimal design of HRES; NSCA-II; Multiple scenarios; Evolutionary algorithms; Multi-objective optimization; EVOLUTIONARY OPTIMIZATION; DIFFERENTIAL EVOLUTION; GENETIC ALGORITHM; POWER MANAGEMENT; MODEL; UNIT;
D O I
10.1016/j.renene.2019.11.015
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The design of hybrid renewable energy system (HRES) is crucial in terms of providing reliable power by renewable energies. So far, a number of studies have been conducted amongst which a single scenario based design is the mostly studied. However, we argue that handling multiple scenarios in the context of HRES design is more practical since operating conditions of a HRES (e.g., load demand) can be different periodically. For example, when designing HRES for a farmland, the busy season time and slack season time are two representative scenarios that correspond to substantially different load demand. Surprisingly, there is no adequate study of multi-scenario oriented multi-objective optimal HRES design. This study therefore fills in this research gap. A multi-scenario optimization based method is proposed for HRES design. Specifically, taking the PV(photovoltaic)-WT (wind turbines)-Bat(Battery)-DG (Diesel generator) as an example, a two-scenario bi-objective optimization model (minimization of system cost while maximization of system reliability) is proposed. In order to solve the model effectively, a scenariodominance based multi-objective evolutionary algorithm (denoted as s-NSGA-II) is proposed. Lastly, a case study is shown to demonstrate the effectiveness of the proposed method, that is, s-NSGA-II is able to find well-balanced solutions for all scenarios, which therefore leads the s-NSGA-II to be a good alternative for dealing with the optimal design of HRES under multiple scenarios. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码:226 / 237
页数:12
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