基于虚拟电厂的多社区温控负荷协同优化策略研究OA

Against the backdrop of high renewable energy penetration and growing residential electricity demand,large-scale regulation of thermostatically controlled loads faces challenges,including dispersed,multi-community loads and significant power fluctuations.To address these issues,this paper proposes a multi-community collaborative optimization framework based on a virtual power plant.First,a three-layer scheduling model of"distribution network operator-community aggregator-end user"is constructed,which achieves coordinated dispatch of multi-community loads through hierarchical optimization and cross-community resource mutual aid.Second,a unified Temperature State Priority Queue(TSPL)mechanism is designed,mapping the temperature deviations of air conditioners and electric water heaters into priority indices to support the coordinated response of heterogeneous thermostatically controlled loads.Furthermore,a TSPL-grouping-based thermal-inertia buffering control strategy is proposed,which effectively suppresses power dips by dispersing load action sequences.Simulation results demonstrate that the proposed strategy not only ensures user comfort but also significantly enhances peak-shaving performance and smoothens power fluctuations,providing technical support for the cooperative scheduling of multi-community thermostatically controlled loads.