Optimization of Electrical System Topology for Offshore Wind Farm Based on Q-learning Particle Swarm Optimization Algorithm

For the electrical system topology optimization of multi-substation offshore wind farms, the current methods are to divide the overall offshore wind farm into several fixed sub-areas according to the predefined number of substations, then independently optimize the cable connection layout in each sub-area and eventually combine all of them as the overall scheme. However, it is often hard to obtain the global optimal scheme due to the fixed partition strategy. Therefore, this paper designs a cable connection layout model for multi-substation offshore wind farms and proposes a Q-learning particle swarm optimization algorithm based on Voronoi adaptive partition, which aims to minimize the total cost considering substation locations, cable type selection, and power loss. Taking the Q-learning particle swarm optimization algorithm as the key, the proposed method designs an adaptive partition strategy based on the Voronoi diagram, which can realize the cable connection in different partitions with coding and decoding strategies. Finally, the case analysis proves the effectiveness of the proposed model and algorithm. © 2021 Automation of Electric Power Systems Press.