计及多能源柔性负荷调度的微能源网多目标演化博弈

doi:10.12204/j.issn.1000-7229.2020.11.011

电力建设 ›› 2020, Vol. 41 ›› Issue (11): 101-115.doi: 10.12204/j.issn.1000-7229.2020.11.011

计及多能源柔性负荷调度的微能源网多目标演化博弈

耿世平¹^,², 牛东晓¹^,², 郭晓鹏¹, 陈梦¹^,², 谭彩霞¹

1.华北电力大学经济与管理学院,北京市 102206
2.新能源电力与低碳发展研究中心,北京市 102206

收稿日期:2020-06-24 出版日期:2020-11-01 发布日期:2020-11-04
通讯作者: 耿世平
作者简介:牛东晓(1962),男,教授,博士生导师,主要研究方向为电力运营管理、电力负荷预测与规划、电力精准投资、综合能源系统等;|郭晓鹏(1979),男,副教授,主要研究方向为能源管理、供应链管理等;|陈梦(1994),女,硕士研究生,主要研究方向为电力负荷预测、电网投资、综合能源系统;|谭彩霞(1998),女,硕士研究生,主要研究方向为电力负荷预测、综合能源系统。
基金资助:
教育部哲学社会科学重大课题攻关项目“构建清洁低碳、安全高效的能源体系政策与机制研究”(18JZD032);高等学校学科创新引智计划“中国绿色电力发展研究学科创新引智基地”(B18021)

Multi-objective Evolutionary Game of Micro Energy Grid Considering Multi-energy Flexible Load Scheduling

GENG Shiping¹^,², NIU Dongxiao¹^,², GUO Xiaopeng¹, CHEN Meng¹^,², TAN Caixia¹

1. School of Economics and Management, North China Electric Power University, Beijing 102206, China
2. New Energy Power and Low Carbon Development Research Center, Beijing 102206, China

Received:2020-06-24 Online:2020-11-01 Published:2020-11-04
Contact: GENG Shiping
Supported by:
Key Projects of Philosophy and Social Sciences Research, Ministry of Education(18JZD032);Key Projects of Philosophy and Social Sciences Research, Ministry of Education(B18021)

摘要/Abstract

摘要：

文章提出了一种基于柔性负荷调度优化的微能源网与用户多目标演化博弈模型。综合考虑微能源网与用户优化目标要求以及相关约束条件,以微能源网收益最大、能源利用效率最大和用户用能支付成本最小、用能满意度最大为博弈双方目标函数,并利用模糊双目标法针对参与者双方不同量纲的双目标函数进行归一化处理。在博弈过程中用户通过柔性负荷的调度来调整用能策略,微能源网侧再根据用户用能行为调整售能价格,最终达到演化稳定状态。通过建立不同场景进行算例分析,结果表明所提出的考虑柔性负荷参与的微能源网与用户演化博弈模型不仅增强了综合能源系统的灵活调节能力,缓解了用能高峰时期供应紧张问题,而且明显提高了能源系统利用效率和微能源网综合收益,在一定程度上降低了用户支付成本,提升了用户的用能满意度。

关键词: 微能源网, 柔性负荷, 演化博弈, 多目标优化

Abstract:

This paper proposes a multi-objective evolutionary game model between micro energy grid and users on the basis of flexible load scheduling optimization. Comprehensively consider the requirements of the micro energy grid and the user’s optimization goals and related constraints, the objective function of the game is to maximize the profit of micro-energy network, maximize the efficiency of energy utilization, minimize the cost of energy consumption and maximize the satisfaction of energy consumption. And the dual-objective functions of different dimensions of the participants are normalized by means of the modulus and the dual-objective method. In the game process, users adjust the energy consumption strategy through flexible load scheduling, and the micro-energy grid side adjusts the energy sales price according to the user’s energy consumption behavior, and finally reaches the evolutionary stable state. Through the establishment of different scenarios for example analysis, the results show that the proposed micro energy grid and user evolution game model that considers the participation of flexible loads can not only enhance the flexible adjustment capacity of the integrated energy system, but also alleviate the problem of supply shortage during peak energy consumption. Moreover, the utilization efficiency of the energy system and the comprehensive income of the micro energy grid have been significantly improved. To a certain extent, the user’s payment cost has been reduced, and the user satisfaction on energy consumption has been improved.

Key words: micro energy grid, flexible load, evolutionary game, multi-objective optimization

中图分类号:

TM73

耿世平, 牛东晓, 郭晓鹏, 陈梦, 谭彩霞. 计及多能源柔性负荷调度的微能源网多目标演化博弈[J]. 电力建设, 2020, 41(11): 101-115.

GENG Shiping, NIU Dongxiao, GUO Xiaopeng, CHEN Meng, TAN Caixia. Multi-objective Evolutionary Game of Micro Energy Grid Considering Multi-energy Flexible Load Scheduling[J]. ELECTRIC POWER CONSTRUCTION, 2020, 41(11): 101-115.

图/表 20

图1 微能源网-多类型用户交易框架

Fig.1 Transaction framework between micro energy grid and multi-type users

图2 演化博弈思路

Fig.2 Evolutionary game ideas

图3 微能源网目标函数隶属度分布

Fig.3 Membership distribution graph of objective function of micro energy grid

图4 用户能源消费剩余示意图

Fig.4 Schematic diagram of user energy consumption surplus

图5 用户目标函数隶属度分布

Fig.5 Membership degree distribution graph of user objective function

图6 演化博弈求解流程

Fig.6 Flowchart for solving evolutionary game

表1 IES设备运行参数

Table 1 Operating parameters of IES equipment

表2 储能装置设备参数

Table 2 Parameters of energy storage device

表3 电网购电分时电价

Table 3 Time-of-use electricity price

图7 日负荷及风光出力曲线

Fig.7 Daily load and scenery output curve

表4 柔性负荷参数设置

Table 4 Parameter settings of flexible load

图8 微能源网多目标变化曲线

Fig.8 Multi-objective variation curve of micro energy grid

图9 用户多目标变化曲线

Fig.9 User multi-objective variation curve

图10 柔性电负荷分布

Fig.10 Distribution of flexible electrical load

图11 优化后电负荷设备出力

Fig.11 Optimized output of power load equipment

图12 柔性热负荷分布

Fig.12 Distribution of flexible thermal load

图13 优化后热负荷设备出力

Fig.13 Optimized output of heat load equipment

图14 柔性冷负荷分布

Fig.14 Distribution of flexible cooling load

图15 优化后冷负荷设备出力

Fig.15 Optimized output of cooling equipment

表5 不同场景下的博弈结果

Table 5 Game results in different scenarios

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计及多能源柔性负荷调度的微能源网多目标演化博弈

Multi-objective Evolutionary Game of Micro Energy Grid Considering Multi-energy Flexible Load Scheduling

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