Layout optimization of Clustered Wind Farms Based on Potential Game Approach

This paper proposes a novel method to design clustered wind farms (WFs). The objectives include the maximization of WF generated power and the minimization of wind turbine (WT) turbulence intensity. To solve this problem, a mathematical model based on the potential game theory is established. Each WF is assumed to be an individual stakeholder, the decision variables and the constraints are mapped to be the strategies and the strategy sets of the stakeholders, respectively, and the objectives are set as their payoffs. The dependency structure matrix genetic algorithm II (DSMGA-II) is used to solve the multi-objective optimization problem (MOOP) and the fuzzy-membership function (FMF) method is used to select the final solution from the Pareto optimal set. The best-strategy-response iterative algorithm is put forward to search for the Nash equilibrium (NE) of the game. Case study on Qidong offshore WFs is carried out to validate the effectiveness of the proposed approach.