基于社交网上演化博弈的光伏台区用户需求响应特性研究

doi:10.12204/j.issn.1000-7229.2022.08.015

电力建设 ›› 2022, Vol. 43 ›› Issue (8): 150-158.doi: 10.12204/j.issn.1000-7229.2022.08.015

• 电力经济研究 • 上一篇

基于社交网上演化博弈的光伏台区用户需求响应特性研究

范辉¹(), 罗蓬²(), 王弘利³(), 梁纪峰²(), 李乾⁴(), 杨军³(), 吴赋章³()

1.国网河北省电力有限公司,石家庄市 050021
2.国网河北省电力有限公司电力科学研究院,石家庄市 050021
3.武汉大学电气与自动化学院,武汉市 430072
4.国网河北省电力有限公司石家庄供电分公司,石家庄市 050000

收稿日期:2021-12-22 出版日期:2022-08-01 发布日期:2022-08-05
通讯作者: 梁纪峰 E-mail:hbdysfh@126.com;15131116222@163.com;294395396@qq.com;ljifeng@126.com;shmily@vip.163.com;JYang@whu.edu.cn;wufuzhangwfz@163.com
作者简介:范辉(1969),男,硕士,教授级高级工程师,主要从事分布式能源并网与微电网技术、电网仿真建模等研究工作,E-mail: hbdysfh@126.com
罗蓬(1984),男,博士,高级工程师,主要从事电力系统继电保护、电子通信技术的研究工作,E-mail: 15131116222@163.com
王弘利(1999),男,硕士研究生,主要研究方向为电力系统经济运行,E-mail: 294395396@qq.com
李乾(1984),男,高级工程师,主要从事电力电缆智能化运检和人工智能技术研究工作,E-mail: shmily@vip.163.com
杨军(1977),男,博士,教授,博士生导师,主要研究方向为电动汽车与电网互动、人工智能与电网安全运行等,E-mail: JYang@whu.edu.cn
吴赋章(1991),男,博士,主要研究方向为新能源接入、电动汽车运行调度,E-mail: wufuzhangwfz@163.com
基金资助:
河北省省级科技计划资助(20314301D)

Study on Demand Response of Users in Photovoltaic Station Area Applying Evolutionary Game Model in Social Network

FAN Hui¹(), LUO Peng²(), WANG Hongli³(), LIANG Jifeng²(), LI Qian⁴(), YANG Jun³(), WU Fuzhang³()

1. State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050021, China
2. Electric Power Research Institute, State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050021, China
3. School of Electrical and Automation, Wuhan University, Wuhan 430072, China
4. Shijiazhuang Power Supply Branch, State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050000, China

Received:2021-12-22 Online:2022-08-01 Published:2022-08-05
Contact: LIANG Jifeng E-mail:hbdysfh@126.com;15131116222@163.com;294395396@qq.com;ljifeng@126.com;shmily@vip.163.com;JYang@whu.edu.cn;wufuzhangwfz@163.com
Supported by:
Science and Technology Program of Hebei(20314301D)

摘要/Abstract

摘要：

“双碳”背景下,通过实施需求侧响应实现新型电力系统的协调运行是解决新能源出力不确定性的主要手段。然而,现实中的用户具有有限理性,其对电价或激励措施的响应呈现出异质性和不确定性。针对此,文章计及有限理性用户对电价或激励措施响应过程中的信息交互以及策略学习特征,提出了一种基于社交网上演化博弈模型的用户需求响应分析模型。首先,考虑到现实经济人在决策中存在信息交互以及策略学习与更新,且该信息交互背后为复杂社群系统,通过构建社交网刻画了用户之间的信息交互关系;其次,根据电价理论和电力供需平衡关系,单个用户的响应决策将会影响其他用户利益,采用博弈模型描述了群体用户的决策过程;最后,考虑到用户对所获取信息处理的有限理性特征,基于社交网上演化博弈模型来描述用户对电价和激励措施的响应过程。仿真分析了不同社交网络结构以及电价或激励措施对用户响应的影响。结果表明,用户社交网小世界属性的增强将会提高用户的响应,价格系数的提高会降低用户的用电意愿。

关键词: 有限理性, 需求响应, 社交网, 新型电力系统, 演化博弈

Abstract:

In the "double carbon target" background, the coordinated operation of the new power system by implementing demand-side response is the main means to solve the uncertainty of new energy output. However, in reality, customers have bounded rationality, and their response to tariffs or incentives is heterogeneous and uncertain. In view of this, considering the information interaction and strategy learning characteristics of bounded rational users in the response process of electricity price or incentive measures, this paper proposes a user-side demand response analysis model based on evolutionary game model in social network. Firstly, considering that the real economic man has information interaction and strategy learning and updating in decision-making, and that the information interaction is a complex community system, the information interaction relationship between users is described by constructing a social network. Secondly, according to the electricity price theory and the balance between power supply and demand, the response decision of a single user will affect the interests of other users. The game model is used to describe the decision-making process of group users. Finally, considering the bounded rationality of users’ information processing, the evolutionary game model in social network is used to describe the response process of users to electricity price or incentive measures. The effects of different social network structures and electricity prices or incentives on user response are simulated and analyzed. The results show that the enhancement of the small world attribute of users’ social network will improve users’ response, and the increase of price coefficient will reduce users’ willingness to use electricity.

Key words: bounded rationality, demand response, social network, new power system, evolutionary game

中图分类号:

TM769

范辉, 罗蓬, 王弘利, 梁纪峰, 李乾, 杨军, 吴赋章. 基于社交网上演化博弈的光伏台区用户需求响应特性研究[J]. 电力建设, 2022, 43(8): 150-158.

FAN Hui, LUO Peng, WANG Hongli, LIANG Jifeng, LI Qian, YANG Jun, WU Fuzhang. Study on Demand Response of Users in Photovoltaic Station Area Applying Evolutionary Game Model in Social Network[J]. ELECTRIC POWER CONSTRUCTION, 2022, 43(8): 150-158.

图/表 11

图1 需求改变对市场均衡与价格的影响

Fig.1 The impact of changes in demand on market equilibrium and prices

图2 社交网上的演化博弈模型求解算法

Fig.2 Algorithm for solving evolutionary game models on social networks

图3 光伏台区社交网络结构拓扑

Fig.3 Topology of social network structure in photovoltaic station area

图4 不同用电程度用户所占比例的收敛过程

Fig.4 Convergence process of the proportion of users with different participation

图5 光伏台区平均用电程度收敛过程

Fig.5 Convergence process of average participation in photovoltaic station area

图6 社交网上的策略演化流程

Fig.6 Strategy evolution process on social networks

图7 10节点策略演化流程

Fig.7 Evolution process of 10-node strategy

图8 不同集聚系数的平均用电程度收敛过程

Fig.8 Convergence process of average power consumption with different clustering coefficients

表1 不同电价制定策略

Table 1 Different electricity-price setting strategies

图9 不同参数组合下的平均用电程度收敛过程

Fig.9 Convergence process of average power consumption under different parameter combinations

图10 本文模型与其他方法仿真结果对比

Fig.10 Comparison of simulation results between the model in this paper and the other methods

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基于社交网上演化博弈的光伏台区用户需求响应特性研究

Study on Demand Response of Users in Photovoltaic Station Area Applying Evolutionary Game Model in Social Network

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