Multi-objective Economic Optimization of Microgrid Operation with Electric Vehicles Hybrid Energy Storage System

HUANG Shan; CHENG Qiming; ZHANG Qiang; ZHU Siyuan; YANG Xiaolong

doi:10.13296/j.1001-1609.hva.2017.10.024

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Multi-objective Economic Optimization of Microgrid Operation with Electric Vehicles Hybrid Energy Storage System

更新时间：2025-04-26

- Multi-objective Economic Optimization of Microgrid Operation with Electric Vehicles Hybrid Energy Storage System
- High VoltageApparatus Vol. 53, Issue 10, Pages: 142-149+157(2017)
- 作者机构：
  
  上海电力学院自动化工程学院
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2017.10.024
  CLC： TM732
- Published：2017
- 稿件说明：
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[1]黄山,程启明,张强,褚思远,杨小龙.含电动汽车混合储能系统的微网多目标经济优化运行[J].高压电器,2017,53(10):142-149+157.

HUANG Shan, CHENG Qiming, ZHANG Qiang, et al. Multi-objective Economic Optimization of Microgrid Operation with Electric Vehicles Hybrid Energy Storage System[J]. High voltageapparatus, 2017, 53(10): 142-149+157.
[1]黄山,程启明,张强,褚思远,杨小龙.含电动汽车混合储能系统的微网多目标经济优化运行[J].高压电器,2017,53(10):142-149+157. DOI： 10.13296/j.1001-1609.hva.2017.10.024.

HUANG Shan, CHENG Qiming, ZHANG Qiang, et al. Multi-objective Economic Optimization of Microgrid Operation with Electric Vehicles Hybrid Energy Storage System[J]. High voltageapparatus, 2017, 53(10): 142-149+157. DOI： 10.13296/j.1001-1609.hva.2017.10.024.

摘要

为了实现分布式电源组成的微网能以更为经济、灵活和环保的方式运行

充分发挥分布式电源的发电优势。针对微网优化调度的问题

提出以电动汽车同时作为负荷和发电单元且计及制热收益的微网多目标优化模型

以经济效益最大化、环境成本最小化作为微网多目标优化问题。应用非劣排序遗传算法NSGA-II

进行多目标优化求解

求得Pareto前端解

从而获得微网最优调度策略。通过算例验证了所提模型、策略和算法的有效性。

Abstract

In order to ensure the microgrid with distributed power to operate in a more economical

flexible and environmental way

the superiority of distributed power can be given full play.Optimal scheduling for energy Internet issues

to propose multi-objective optimization function model of microgrid with electric vehicles which is a load and power generation unit at the same time

and economic operated CHP

which aims to maximize the economic benefit and minimize the environmental cost of multi-objective optimization of microgrid.Use the non-objective sorting genetic algorithm NSGA-II

solve the multi-objective optimization problems

obtain the Pareto front-end methods

and get the best dispatch strategy of microgrid.The validity of the proposed model

dispatch strategy and algorithm is proved by the examples.

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Related Author

YANG Xiaolong

ZHU Siyuan

CHENG Yinman

CHENG Qiming

HUANG Shan

ZHOU Wei

CHENG Peng

ZHANG Yitao

Related Institution

College of Automation Engineering,Shanghai University of Electric Power,Shanghai Key Laboratory Power Station Automation Technology Laboratory

College of Electronics and Information Engineering,Tongji University

State Grid Jibei Electric Power Co, Ltd, Langfang Power Supply Company

State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University

College of Electrical Engineering & New Energy, China Three Gorges University

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