Distributed Renewable Energy Cluster Configuration Based on Improved Bare-Bones Multi-objective Particle Swarm Optimization

A bi-level optimal allocation model of renewable energy cluster planning and operation is established in order to maximize the consumption of renewable energy based on the security and stability of the power system are ensured. The planning layer applied the particle swarm optimization algorithm, and the results were used as the input of the operation layer. The optimization model of the operation layer used the CVX toolbox, and the output results are used to evaluate the planning results. An improved bare-bones multi-objective particle swarm optimizer (IBB-MOPSO) algorithm is proposed to overcome the shortcomings of traditional particle swarm optimization (PSO), including the lack of diversity and easy to fall into local optimum. Building on the advantages of the bare-bones particle swarm algorithm (BB-PSO) with high adaptability and few control parameters, the global search and local exploitation capabilities are further enhanced by improvements. The effectiveness of the optimization configuration model and the solution algorithm is verified through the numerical simulations. The proposed method is universal, as the appropriate optimal solution can be selected according to specific demands for configuration in practical applications.