Information gap-based coordination scheme for active distribution network considering charging/discharging optimization for electric vehicles and demand response

Abstract

The power fluctuation of load and distributed generation is a leading cause of load and voltage fluctuations and directly impacts the safe and efficient operation of the active distribution network in recent years due to the growing penetration of electric vehicles and distributed generation in the network. To optimize the load characteristics, a demand response model based on a logistic function is introduced, and the dynamic charging/discharging electricity price of electric vehicles based on the comprehensive load is considered in order to incentivize electric vehicle users to charge/discharge orderly. Then, a coordinated optimal model based on the information gap decision theory is constructed to cope with the uncertainty of distributed generation and ensure the operational economy and robustness of the active distribution network. Additionally, a population-based multi-objective state transition algorithm with a parallel search mechanism and communication mechanism was proposed to solve the demand response model, and second-order cone programming was utilized to solve the coordinated optimal model with complex constraints. Finally, the proposed comprehensive model and algorithm were investigated based on the IEEE 33 test system. The results show that the proposed model not only reduces the peak-to-valley difference in load by 24.38% but also significantly reduces the total operating cost by 13.41%. Simultaneously, the proposed algorithm increases the solving efficiency, verifying the feasibility and effectiveness of the optimal strategy and algorithm, which promotes the economical and reliable operation of the active distribution network.