Demand Response Model for Residential Appliances and Distributed Generators

Abstract

In the future power system, residential consumers can be seen as an energy resource with decentralized and autonomous decisions in the energy management. Each consumer will possess controllable loads and small generator units in their house. This paper presents a dynamic demand response (DR) model based on a controllable set composed of residential appliances and distributed generators. This DR model provides fine-grained balancing peak demand by hierarchical sorting and combinatorial optimization. This paper first proposes a multiplicative ARIMA load forecasting method based on a combination of longitudinal and lateral time. Secondly, detailed models are established for air-conditioning, water heaters, electric vehicles, and solar photovoltaic systems. Finally, the DR model is built according to the controllability and priority of the controllable set in a single short. Simulation results show that this model reduces load finely.