Multi-Objective Optimisation for Large-Scale Offshore Wind Farm Based on Decoupled Groups Operation

Operation optimization for large-scale offshore wind farms can cause the fatigue loads of single turbines to exceed their limits. This study aims improve economic profit by conducting multi-objective via decoupled group operations turbines. To do this, a farm is firstly divided into several subsets through parallel depth-first search (PDFS) and hyperlink-induced topic (HITS) algorithms based on wake-based direction graph. Next, three objectives are considered, including total output power, load, load dispatch turbine (WT) in farm. And then, combined Monte Carlo beetle swarm (CMC-BSO) applied solve non-convex problem decentralized communication network topology. Finally, simulation results demonstrate that proposed method balances power output, with fast convergence.