A bi-level optimization model and hybrid evolutionary algorithm for wind farm layout with different turbine types

Abstract In order to reduce the influence of wake effect between wind turbines under complex terrain in wind farm layout, it is feasible to adopt a deployment scheme of multiple types of wind turbines to maximize the benefits. In this paper, both the cost function and the output power of the wind farm are considered, where the cost functions include of different diameter, hub-height, and types of wind turbines. Therefore, a mode of bi-level constrained optimization is established, where decision variable at the upper-level is the deployment of wind turbine type, and decision variable at the lower-level is the deployment of wind turbine micro-location. Then, according to the characteristics of the decision variables, a hybrid algorithm based on genetic algorithm and differential evolution is proposed, and the above evolution operations and parameter values are improved to improve the performance of the algorithm. Finally, the feasibility of the proposed scheme is verified by extensive simulations.