Cooperative Operation for Multiple Integrated Energy Systems Considering Wind Power Consumption by Nash Bargaining Convention

doi:10.7652/xjtuxb202203019

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Cooperative Operation for Multiple Integrated Energy Systems Considering Wind Power Consumption by Nash Bargaining Convention

更新时间：2025-07-09

- Cooperative Operation for Multiple Integrated Energy Systems Considering Wind Power Consumption by Nash Bargaining Convention
- Vol. 56, Issue 3, Pages: 187-196(2022)
- 作者机构：
  
  西安交通大学电气工程学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202203019
  CLC： TM73
- Online First：10 March 2022，
  
  Published：2022
- 稿件说明：
移动端阅览
Cooperative Operation for Multiple Integrated Energy Systems Considering Wind Power Consumption by Nash Bargaining Convention[J]. 2022, 56(3): 187-196.
DOI：

Cooperative Operation for Multiple Integrated Energy Systems Considering Wind Power Consumption by Nash Bargaining Convention[J]. 2022, 56(3): 187-196. DOI： 10.7652/xjtuxb202203019.

摘要

为有效提高多个电热综合能源系统(HE-IES)的能源利用率

针对计及风电消纳下多个HE-IES协同运行的成本分摊问题

提出一种基于纳什议价理论的多HE-IES的多目标优化运行模型。构建多HE-IES的框架

针对HE-IES内燃气轮机、热泵、电储能、热储能等设备进行建模

并建立多个HE-IES间、HE-IES与配网间的功率交互模型; 以多HE-IES的运行成本与风电消纳作为指标

通过多目标加权规划法建立多HE-IES的多目标优化模型; 进一步地

通过纳什议价理论建立多个HE-IES的合作博弈模型

通过数学转换将非凸问题转换为两个凸的子问题

实现每个HE-IES均达到帕累托最优

以保证各HE-IES参与合作的积极性。算例仿真表明

相比各HE-IES独立运行

所提模型使得总运行成本和总弃风成本分别减少了660.14与222.03元

使得每个HE-IES的运行成本与弃风成本分别减少了220.05与74.07元

实现了所有HE-IES的帕累托最优。

Abstract

To effectively improve energy efficiency of multiple HE-IESs

aiming at the cost sharing problem of multiple HE-IESs coordinated operation taking wind power consumption into account

a multi-HE-IESs multi-objective optimization operation model with Nash bargaining theory is proposed. The framework of multi-HE-IESs is constructed to model gas turbine

heat pump

electric energy storage

thermal energy storage and the other equipments in HE-IES

and multiple power interaction models among HE-IESs and between HE-IES and distribution network are established. Taking operating costs and wind power consumption of multi-HE-IESs as the indicators

the multi-objective weighted programming method is used to establish a multi-HE-IESs multi-objective optimization model. Furthermore

following Nash bargaining theory

a cooperative game model of multi-HE-IESs is constructed

and the non-convex problem is transformed into two convex sub-problems via mathematical transformation to realize the Pareto optimum for each HE-IES

which ensures the enthusiasm of all HE-IESs to participate in cooperation. A simulation example verifies that the proposed method enables to reduce total operating costs and total wind curtailment costs by 660.14 and 222.03 yuan

respectively

and also to reduce operating costs and wind curtailment costs of each HE-IES by 220.05 and 74.07 yuan

thus the Pareto optimum of overall HE-IESs is achieved.

关键词

Keywords

references

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