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浙江大学学报(工学版)
浙江大学学报(工学版)  2024, Vol. 58 Issue (4): 790-798    DOI: 10.3785/j.issn.1008-973X.2024.04.014
机械工程、能源工程     
家庭智能电器负荷调度和能量分配优化算法
刘迪迪1,2(),杨文宇1,廖志贤2,张泉景3,*(),胡聪4
1. 广西师范大学 电子与信息工程学院，广西 桂林 541004
2. 广西师范大学 广西类脑计算与智能芯片重点实验室，广西 桂林 541004
3. 西华师范大学 教育信息技术中心，四川 南充 637009
4. 桂林电子科技大学 广西自动检测技术与仪器重点实验室，广西 桂林 541004
Load scheduling and energy allocation optimization algorithm for intelligent home appliances
Didi LIU1,2(),Wenyu YANG1,Zhixian LIAO2,Quanjing ZHANG3,*(),Cong HU4
1. School of Electronic and Information Engineering, Guangxi Normal University, Guilin 541004, China
2. Guangxi Key Laboratory of Brain-inspired Computing and Intelligent Chips, Guangxi Normal University, Guilin 541004, China
3. Education Information Technology Center, China West Normal University, Nanchong 637009, China
4. Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin University of Electronic Technology, Guilin 541004, China
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摘要：

为了解决家庭用电高额能耗问题和提高用户供用电收益，针对家庭中具有用电差异性的负荷进行能量调度. 根据可转移属性，将家庭用电负荷分为2个类别：弹性负荷和非弹性负荷. 联合分布式可再生能源和储能设备构建智能电器用电负荷调度优化模型，基于李雅普诺夫优化理论提出时变电价下的家庭用户多电器能量分配算法. 所提算法充分考虑了不同智能电器的用电负荷响应及调度优化问题. 理论性能分析证明，所提算法能够在不需要系统的先验统计信息的情况下使优化目标渐近最优. 对所提算法的用户收益提升能力进行仿真验证，结果表明，相较于未考虑各家用智能电器实际需求和可容忍时延的分配算法，所提算法可将用户收益提高11.2%.
关键词： 智能电器;  调度优化;  李雅普诺夫优化;  能量分配;  需求响应    
Abstract:

To address the problem of high energy consumption in household electricity usage and to improve the user revenue from electricity supply and use, an energy scheduling approach was proposed for loads with electrical differences in households. Firstly, the household electrical loads were divided into elastic loads and non-elastic loads based on the transferable attributes. Then, an optimization model for load scheduling of intellectualized electrical apparatus was proposed by jointly considering distributed renewable energy resources and energy storage devices. Based on the Lyapunov optimization theory, an algorithm for time-varying electricity pricing was designed to allocate energy for multiple home appliances. The algorithm fully considered the load response and the scheduling optimization of different intelligent appliances. Theoretical performance analysis demonstrates that the proposed algorithm achieves asymptotic optimality without requiring any priori statistical information of the system. Finally, simulations were conducted to validated the user revenue improvement capability of the proposed algorithm. Compared to the allocation algorithm that did not take into account the actual needs of various home appliances and tolerable delay, the proposed algorithm can increase the user revenue by 11.2%.
Key words: intelligent appliances    schedule optimization    Lyapunov optimization    energy allocation    demand response
收稿日期: 2023-08-14 出版日期: 2024-03-27
CLC:  TM 734  
基金资助: 国家自然科学基金资助项目（62061006）；广西自动检测技术与仪器重点实验室基金资助项目（YQ23203）；广西类脑计算与智能芯片重点实验室基金资助项目（BCIC-23-Z7）；青年教师科研资助项目（23kq004）.
通讯作者: 张泉景     E-mail: ldd866@gxnu.edu.cn;quanjing_zhang@163.com
作者简介: 刘迪迪（1980—），女，教授，从事电力系统控制、随机网络优化研究. orcid.org/0000-0002-4248-0669. E-mail：ldd866@gxnu.edu.cn
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引用本文:

刘迪迪,杨文宇,廖志贤,张泉景,胡聪. 家庭智能电器负荷调度和能量分配优化算法[J]. 浙江大学学报(工学版), 2024, 58(4): 790-798.

Didi LIU,Wenyu YANG,Zhixian LIAO,Quanjing ZHANG,Cong HU. Load scheduling and energy allocation optimization algorithm for intelligent home appliances. Journal of ZheJiang University (Engineering Science), 2024, 58(4): 790-798.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2024.04.014    或    https://www.zjujournals.com/eng/CN/Y2024/V58/I4/790

图 1  家庭智能用电管理系统示意图
图 2  家庭能源管理系统的能量流
图 3  不同算法的用户百天累计收益对比
图 4  不同算法的时延对比
图 5  不同模型的用户百天收益对比
图 6  不同模型的用户百天平均时延对比
图 7  储能设备充放电特性
图 8  不同电器分配的能量与队列积压的关系
图 9  不同场景下用户百天累计收益对比
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