Bi-Level Multi-Objective Optimization Scheduling for Regional Integrated Energy Systems Based on Quantum Evolutionary Algorithm

被引：8
|
作者：
Fan, Wen [1 ]
Liu, Qing [1 ]
Wang, Mingyu [1 ]
机构：
[1] North China Elect Power Univ Baoding, State Key Lab Alternate Elect Power Syst Renewabl, Baoding 071003, Peoples R China
来源：
ENERGIES | 2021年 / 14卷 / 16期
关键词：
integrated energy system; quantum evolutionary algorithm; multi-objective programming; bi-level model; uncertainty; STRATEGY; POWER;
D O I：
10.3390/en14164740
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
Integrated energy systems have become an important research topic in the pursuit of sustainable energy development. This paper examines regional integrated energy systems, presents the typical architecture of regional integrated energy systems, and builds an integrated energy system model. Two evaluation indexes are proposed: the integrated energy self-sufficiency rate and the expected energy deficiency index. Based on these evaluation indexes and taking into account the uncertainty of wind power generation, a bi-level optimization model based on meta-heuristic algorithms and multi-objective programming is established to solve the problem of regional integrated energy system planning under different load structures and for multi-period and multi-scenario operation modes. A quantum evolutionary algorithm is combined with genetic algorithms to solve the problem.
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收藏
页数：15
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