Heuristics-based design and optimization of offshore wind farms collection systems

An optimization framework for automated design of offshore wind farms collection systems is proposed in this paper. The core of the framework consists of a metaheuristic algorithm, namely a Genetic Algorithm (GA). The GA is designed for searching high-quality feasible solutions in terms of the capital expenditure (CAPEXcs); a subsequent step runs a power flow in order to calculate electrical power losses for estimating the collection systems share on the Levelized Cost of Energy (LCOEcs).Finally, after several executions of the full framework, the feasible solution bringing the cheapest LCOEcs is selected. The main inputs are the coordinate’s location of the wind turbines and the offshore substation (OSS), wind power production time series, and the set of considered cables for the collection system design. The proposed approach offers a full search space exploration for feasible solutions, while taking into account cables capacities and disallowing for cable crossings. The results show that this framework can find feasible solutions improving benchmark methods by 8%.