基于用户行为预测的分布式光伏智能社区需求响应策略

doi:10.6040/j.issn.1672-3961.0.2022.177

山东大学学报 (工学版) ›› 2022, Vol. 52 ›› Issue (5): 24-34.doi: 10.6040/j.issn.1672-3961.0.2022.177

• • 上一篇

基于用户行为预测的分布式光伏智能社区需求响应策略

刘振¹,孙媛媛^1*,李亚辉¹,许庆燊¹,于涛²,庞延庆³

1.山东大学电气工程学院, 山东济南 250061;2.济南市规划设计研究院, 山东济南 250000;3.山东电工时代能源科技有限公司, 山东济南 250022

发布日期:2022-10-20
作者简介:刘振(1998— ),男,山东青岛人,硕士研究生,主要研究方向为源网荷储协同规划. E-mail:914173263@qq.com. *通信作者简介:孙媛媛(1981— ),女,山东淄博人,教授,博士生导师,主要研究方向为电能质量与直流电力系统等. E-mail:sunyy@sdu.edu.cn
基金资助:
国家自然科学基金面上资助项目(51977123)

Demand response strategy for distributed photovoltaic smart community based on model prediction of user behavior analysis

LIU Zhen¹, SUN Yuanyuan^1*, LI Yahui¹, XU Qingshen¹, YU Tao², PANG Yanqing³

1. School of Electrical Engineering, Shandong University, Jinan 250061, Shandong, China;
2. Jinan City Planning and Design Institute, Jinan 250000, Shandong, China;
3. Shandong Electric Times Energy Technology Co., Ltd., Jinan 250022, Shandong, China

Published:2022-10-20

摘要/Abstract

摘要： 为解决分布式能源接入场景下用户行为不确定性与需求计划的冲突问题,建立一种基于用户行为预测的分布式光伏智能社区响应策略,通过分布式光伏与需求负荷资源的协调配合,协调用户行为的不确定性与需求计划的制定。建立需求资源的数学模型,采用广义回归神经网络和概率神经网络预测用户行为,形成预前调度措施。基于建立的模型与措施形成光伏社区需求响应整体策略,提出用户自主响应算法以提升用户舒适度。基于分时电价、光照辐射、负荷参数等信息,构建智能家居控制系统并进行仿真分析,预测模型的准确性达96.33%,具有较强的适用性,验证了需求响应策略的有效性,解决了用户行为与需求调度的配合问题,有效降低用户用电成本。

关键词: 智能家居, 需求响应, 分布式光伏接入, 用户行为预测, 不确定性分析

中图分类号:

TM73

刘振,孙媛媛,李亚辉,许庆燊,于涛,庞延庆. 基于用户行为预测的分布式光伏智能社区需求响应策略[J]. 山东大学学报 (工学版), 2022, 52(5): 24-34.

LIU Zhen, SUN Yuanyuan, LI Yahui, XU Qingshen, YU Tao, PANG Yanqing. Demand response strategy for distributed photovoltaic smart community based on model prediction of user behavior analysis[J]. Journal of Shandong University(Engineering Science), 2022, 52(5): 24-34.

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基于用户行为预测的分布式光伏智能社区需求响应策略

Demand response strategy for distributed photovoltaic smart community based on model prediction of user behavior analysis

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