Optimization of Network-Load Interaction With Multi-Time Period Flexible Random Fuzzy Uncertain Demand Response

This paper represents a network-load interaction optimization framework integrated multi-time period flexible random fuzzy uncertain demand response (DR) model, which involved shifting of loads' operation time and uncertain response to the price signal. The network-load interaction is to optimize load profile and network topology under the guidance of electricity price at the aim of achieving the economic and secure operation of the distribution network and at the same time satisfying the consumers' satisfaction. This framework is a two-level framework, which includes the price-based DR level to minimize the daily load variance and maximize the customers' satisfaction, and the reconfiguration level to minimize the network reconfiguration cost and power unbalancing. Firstly, the price-based DR level determines the price and the load profile subject to the multi-time period flexibility and uncertainties of the DR. Then, the reconfiguration level optimizes the network configuration topology according to the load profile and feeds the results back to the price-based DR level. This network-load interaction optimization model is tackled by the proposed multi-objective self-adaptive particle swarm (SAPSO) optimization algorithm. The proposed network-load interaction optimization model is applied to the IEEE33-bus distribution system and a real system. The results show that this model is efficient to solve the network economic operation and load profile optimization problem simultaneously.