An Optimal Framework for Residential Load Aggregator

—Due to the development of intelligent demand-side management with automatic control, distributed populations of large residential loads, such as air conditioners (ACs) and electrical water heaters (EWHs), have the opportunities to provide effective demand-side ancillary services for load serving entities (LSEs) to reduce the emissions and network operating costs. Most present approaches are restricted to 1) the scenarios involving with efficiently scheduling the large number of appliances in real time; 2) the issues about evaluating the individual residents' contributions towards participating demand response (DR) program, and fairly distributing the rewards; and 3) the concerns on preforming cost-effective LSEs' demand reduction request (DRR) with minimal rewards costs while not effecting residents' living comfortableness. Therefore, this paper presents an optimal framework for residential load aggregators (RLAs) which helps solve the problems mentioned above. Under this framework, RLAs are able to realize the DRR for LSEs to generate optimal control strategies over residential appliances quickly and efficiently. To residents, the framework is designed with probabilistic model of comfortableness, which minimizes the impact of DR program to their daily life. To LSEs, the framework helps minimize the total reward costs of performing DRRs. Moreover, the framework fairly and strategically distributes the financial rewards to residents, which may stimulate the potential capability of loads optimized and controlled by RLAs in demand side management. The proposed framework has been validated on several numerical case studies. NOMENCLATURE n Number of households under one RLA. R1 Level 1 reward rate, cents/(kW • 5min). R2 Level 2 reward rate, cents/(kW • 5min). R3 Level 3 reward rate, cents/(kW • 5min). Copi Whether resident i is willing to compromise the appliances operating beyond their comfortable interval, ON/OFF. CMi Comfortable margin for resident i. TAi Ambient temperature for resident i. TDR Total demand secluded to reduce, kW. D Amount of demand reduction required, kW. δ Parameter associated with demand reduction accuracy relaxation. RWi Total financial rewards for resident i, $.