Based on particle swarm optimization (PSO), an optimization platform for offshore wind farm electrical system (OWFES) is proposed in this paper, where the main components of an offshore wind farm and key technical constraints are considered as input parameters. The offshore wind farm electrical system is optimized in accordance with initial investment by considering three aspects: the number and siting of offshore substations (OS), the cable connection layout of both collection system (CS) and transmission system (TS) as well as the selection of electrical components in terms of voltage level and capacity. Because hundreds of optimization variables, continuous or discrete, are involved in the problem, a mix integer PSO (MIPSO) is required to obtain the solution. The fuzzy C-means clustering (FCM) algorithm is used to partition the wind farm into several sub regions. The collection system layout in each sub region as well as the connection scheme between offshore substations are optimized by an adaptive PSO-minimum spanning tree algorithm (APSO-MST) which has been proposed in a previous work. The simulation results show that the proposed optimization platform can find an optimized layout that save 3.01% total cost compared with the industrial layout, and can be a useful tool for OWFES design and evaluation.