基于分时电价和激励补贴机制的家庭能量双层优化模型

doi:10.12204/j.issn.1000-7229.2021.11.012

电力建设 ›› 2021, Vol. 42 ›› Issue (11): 108-116.doi: 10.12204/j.issn.1000-7229.2021.11.012

基于分时电价和激励补贴机制的家庭能量双层优化模型

傅质馨¹^,², 李紫嫣¹^,²(), 李寒兵³, 朱俊澎¹^,², 袁越¹^,²

1.河海大学能源与电气学院,南京市 211100
2.河海大学可再生能源发电技术教育部工程研究中心,南京市 211100
3.国网江苏省电力有限公司,南京市 210000

收稿日期:2021-04-29 出版日期:2021-11-01 发布日期:2021-11-02
通讯作者: 李紫嫣 E-mail:704315319@qq.com
作者简介:傅质馨(1983),女,博士,副教授,主要研究方向为可再生能源发电技术、物联网技术;
李寒兵(1987),男,硕士,工程师,主要研究方向为中压配电网电力电缆运行与抢修,电力设备状态检修等;
朱俊澎(1990),男,博士,讲师,主要研究方向为主动配电网规划、运行与控制;
袁越(1966),男,博士,教授,博士生导师,主要研究方向为电力系统运行与分析、可再生能源发电技术等。
基金资助:
国家自然科学基金青年项目“基于双向辅助服务的主动配电网与微电网互动优化运行”(51807051);江苏省自然科学基金青年项目“电力市场环境下主动配电网与微电网联合优化运行”(BK20180507)

Two-Tier Optimization Model of Home Energy Considering Time-of-Use Electricity Price and Incentive Subsidy Mechanism

FU Zhixin¹^,², LI Ziyan¹^,²(), LI Hanbing³, ZHU Junpeng¹^,², YUAN Yue¹^,²

1. College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
2. Research Center for Renewable Energy Generation Engineering of Ministry of Education, Hohai University, Nanjing 211100, China
3. State Grid Jiangsu Electric Power, Co., Ltd., Nanjing 210000, China

Received:2021-04-29 Online:2021-11-01 Published:2021-11-02
Contact: LI Ziyan E-mail:704315319@qq.com
Supported by:
National Natural Science Foundation of China(51807051);Natural Science Foundation of Jiangsu Province(BK20180507)

摘要/Abstract

摘要：

为了降低居民日负荷曲线峰谷差,提高居民参与电网需求响应的积极性之前,文章基于分时电价和激励机制,提出双层模型实现家庭能量的优化调度。该模型以需求侧响应为手段,以家庭能量优化为策略,实现供电端与用电端的互动,刻画出电价、激励机制与用户用电行为之间的交互关系。外层模型在分时电价的环境下,采用模糊C-均值聚类算法(fuzzy C-means algorithm, FCM)对用户用电情况进行分析,以日负荷曲线削峰填谷为目标,设计包含激励补贴和峰谷系数的电力套餐。内层模型基于电力套餐实现家用电器的智能管理,模拟实施套餐前后的居民日负荷曲线,实时调整用电计划,使用户日负荷曲线满足电力套餐中的峰谷系数。通过仿真验证双层优化模型有效降低了用户日负荷曲线的峰谷差,且设计的电力套餐在用户侧有一定的实用性,有利于用户更加积极地参与电网的优化调度,满足电网削峰填谷的要求。

关键词: 双层优化模型, 分时电价, 激励机制, 日负荷曲线, 智能家居用电优化调度, FCM聚类算法

Abstract:

A two-tier model is proposed to control the peak-valley difference of daily load curve of users and to optimize electricity consumption for smart home. This model takes demand-side response as the means and household energy optimization as the strategy to realize the interaction between the power supply end and the power consumption end, and describes the interactive relationship among the price of electricity, incentive mechanism and users’ power consumption behavior. In the environment of time-of-use (TOU) price, the outer model adopts FCM algorithm to analyze the power consumption of users, and designs the power package including incentive subsidy and peak-valley coefficient with the goal of peak-valley load curve clipping. The inner layer model realizes the intelligent management of household appliances applying the power package, simulates the daily load curve of residents before and after the implementation of the power package, adjusts the electricity consumption plan in real time, and enables the daily load curve of users to meet the peak-valley coefficient of the power package. Through simulation, it is verified that the two-tier optimization model proposed in this paper can effectively reduce the peak-valley difference of the daily load curve of users, and the designed power package is practical to a certain extent on the user side, which is beneficial for users to participate more actively in the optimization scheduling of the power grid and meet the requirements of peak load reduction and valley filling of the power grid.

Key words: two-tier optimization model, time-of-use electricity price, incentive mechanism, daily load curve, smart home power optimization scheduling, FCM clustering algorithm

中图分类号:

TM73

傅质馨, 李紫嫣, 李寒兵, 朱俊澎, 袁越. 基于分时电价和激励补贴机制的家庭能量双层优化模型[J]. 电力建设, 2021, 42(11): 108-116.

FU Zhixin, LI Ziyan, LI Hanbing, ZHU Junpeng, YUAN Yue. Two-Tier Optimization Model of Home Energy Considering Time-of-Use Electricity Price and Incentive Subsidy Mechanism[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(11): 108-116.

图/表 12

表1 负荷曲线的特征指标

Table 1 Characteristic indices of load curve

图1 联合供用电端优化日负荷曲线合理调度用户用电的总体思路图

Fig.1 General idea chart of optimizing daily load curve and rationally scheduling power consumption for the combined power supply and consumption

图2 联合供用电端优化日负荷曲线合理调度用户用电流程

Fig.2 Flow chart of optimizing daily load curve and rationally scheduling power consumption for the combined power supply and consumption

表2 分时电价

Table 2 Time-of-use price

表3 聚类质量分析

Table 3 Cluster quality analysis

图3 基于模糊C聚类算法的日负荷曲线聚类结果

Fig.3 Clustering results of daily load curve from FCM algorithm

表4 最优电力套餐

Table 4 Optimal power plan

表5 居民使用电力套餐后对电费支出和对电网响应程度的满意度

Table 5 Residents’ satisfaction with electricity bills and response to the grid after using electricity plans

表6 可调度设备的用电信息

Table 6 Power consumption information of the dispatching equipment

图4 实施电力套餐前后的负荷曲线

Fig.4 Load curve before and after implementation of power package

图5 计划外家电运行情况

Fig.5 Unplanned operation of home appliances

图6 考虑动态优先级和满足峰谷系数标准值的家电运行

Fig.6 Home appliance operation considering the dynamic priority and meeting the peak-valley coefficient of the standard value

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基于分时电价和激励补贴机制的家庭能量双层优化模型

Two-Tier Optimization Model of Home Energy Considering Time-of-Use Electricity Price and Incentive Subsidy Mechanism

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