电力系统自动化2025，Vol.49Issue(10)：29-38,10.DOI:10.7500/AEPS20240628002
考虑平均制热需求的集群电采暖负荷可靠调节能力挖掘策略
Reliable Regulation Capability Extraction Strategy for Cluster Electric Heating Load Considering Average Heating Demand
摘要
Abstract
Aiming at the problem that the regulation capability of the cluster electric heating load is difficult to be accurately and reliably extracted due to the strong random fluctuation of the baseline power in the natural aggregation mode,a reliable regulation capability extraction strategy for cluster electric heating load considering average heating demand is proposed.Before the peak load regulation,the load baseline is smoothed based on the correlation law between the average heating demand of electric heating room and the temperature difference between indoor and outdoor,so as to reduce the influence of working condition disturbance on the reliability of regulation capability.When the peak load regulation capability is reported,based on the explored relationship between the regulation power of the electric heating load and the sustainable duration,the regulation power amplitude that the cluster electric heating load can sustainably provide is flexibly set according to the grid demand duration.When the peak regulation instruction is executed,the flexibility of the room temperature within the comfort range of the human body is converted into the flexibility of the real-time operation quantity of the cluster electric heating,so as to correct the influence of the deviation between the real-time working condition and the preset working condition on the peak regulation response.In addition,the effectiveness of the proposed strategy is verified by case studies.关键词
集群电采暖/平均制热需求/调峰/自然聚合/智慧聚合/常态运行/负荷基线Key words
cluster electric heating/average heating demand/peak load regulation/natural aggregation/smart aggregation/normal operation/load baseline引用本文复制引用
严干贵,吕帅帅,穆钢,姜警,张利伟,邢奥岚..考虑平均制热需求的集群电采暖负荷可靠调节能力挖掘策略[J].电力系统自动化,2025,49(10):29-38,10.基金项目
国家自然科学基金重点项目(52337004). This work is supported by National Natural Science Foundation of China(No.52337004). （52337004）
