摘要
随着新型电力系统源荷不确定性及灵活性需求的大幅提升,挖掘负荷侧需求响应(demand response,DR)资源已成为必然需求。针对现有研究缺乏对多元主观用电行为及其耦合-交互影响的考量,导致DR潜力评估不准确的问题,提出一种耦合居民显性与隐性信息的DR潜力评估方法。首先,在显性维度中,采用基于密度的噪声应用空间聚类算法提取典型日负荷曲线,并选取用电波动性指标量化用户基础响应潜力。其次,在隐性维度中,考虑用户响应时段内的主观行为特征,构建禀赋效应与同群效应作用下的响应模型,揭示其隐性潜力分布规律。然后,针对上述双效应交互作用引发的DR决策模糊性问题,通过二元Logistic回归实现显性潜力与隐性潜力的耦合,建立融合双维信息的叠加-交互响应模型以确定最终潜力值。最后仿真分析结果表明:相较于单一用电信息评估方法,该方法实现了用户潜力的多维度量化评估;据此设定邀约申报量参考基准,可有效提升用户侧DR收益水平。
With the significant increase in source-load uncertainty and flexibility requirements of the new power system,tapping into demand response(DR)resources on the load side has become an imperative.To address the issue of inaccurate DR potential assessment in existing research due to insufficient consideration of diverse subjective electricity consumption behaviors and their coupling-interaction effects,this paper proposes a DR potential assessment method that couples residents'manifest and latent information.First,in the manifest dimension,the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)algorithm is employed to extract typical daily load curves,and electricity consumption volatility indicators are selected to quantify users'baseline response potential.Second,in the latent dimension,considering users'subjective behavioral characteristics during response periods,a response model under the influence of endowment and peer effects is constructed to reveal the distribution patterns of latent potential.Furthermore,to resolve the ambiguity in DR decision-making caused by the interaction of these dual effects,binary logistic regression is used to couple manifest and latent potential,establishing a superposition-interaction response model that integrates dual-dimensional information to determine the final potential value.Simulation and experimental results demonstrate that,compared to single-dimensional electricity consumption information assessment methods,this approach achieves multidimensional quantitative assessment of user potential.By setting a reference benchmark for incentive quota declaration based on this assessment,DR revenue on the user side can be effectively enhanced.
作者
江友华
肖丁元
杨金婉
王金超
谢振刚
JIANG Youhua;XIAO Dingyuan;YANG Jinwan;WANG Jinchao;XIE Zhengang(College of Electronics and Information Engineering,Shanghai University of Electric Power,Shanghai 201306,China;Binzhou Power Supply Company of State Grid Shandong Electric Power Company,Binzhou 256610,China;Tianchang Power Supply Company of State Grid Anhui Electric Power Company,Tianchang 239300,China;State Grid Jiangxi Electric Power Co.,Ltd.Ganzhou Ganxian District Power Supply Branch,Ganzhou 341100,China)
出处
《供用电》
北大核心
2025年第9期65-76,共12页
Distribution & Utilization
基金
上海市自然科学基金(25ZR1401144)
海上风电技术教育部工程研究中心(A-2021-24-175)。
关键词
需求响应
家庭负荷
主观用电行为
Logistic耦合
日前邀约调度
demand response
household load
subjective electricity consumption behavior
Logistic coupling
day-ahead invitation to scheduling
