Joint planning and optimal operation of AC / DC hybrid distribution network considering distributed generation and EV charging station

Abstract

With the continuous increase in the penetration rate of renewable energy and electric vehicles under the dual carbon goal, the location and capacity of distributed power generation and electric vehicle charging stations have become the key of power grid planning. This paper proposes a joint planning and optimal optimization method for the AC-DC hybrid distribution network with distributed generation and electric vehicle charging station. Firstly, based on the BP artificial neural network prediction algorithm, a prediction model is constructed for the historical data such as wind speed, light intensity, temperature, humidity and air pressure in the region, and the typical daily output characteristics of renewable energy could be obtained. Then according to the driving behavior characteristics of regional electric vehicle users, the electric vehicle charging station model can be proposed. Finally, a joint planning and optimal operation planning model is constructed in the AC/DC hybrid distribution network that takes micro-turbine, energy storage system, electric vehicle charging station and renewable energy system into account. The model is a nonlinear non-convex mixed-integer programming problem, which could be used by linearization and second-order cone relaxation techniques to transform into a mixed-integer second-order cone-convex optimization problem that can be efficiently solved by commercial solvers. The case study takes a modified IEEE33 system as an example, combined with the weather conditions in a certain area, to verify the validity and rationality of the proposed model.