Current wind farm layout optimization research assumes a continuous piece of land is readily available and focuses on advancing optimization methods. In reality, projects rely on landowners’ permission for success. When a viable site is identified, local residents are approached for permission to build turbines on their land, typically in exchange for monetary compensation. Landowners play a crucial role in the development process, and some land parcels are more important to the success of project than others. This paper relaxes the assumption that a continuous piece of land is available, developing a novel approach that includes a model of landowner participation rates. A genetic algorithm (GA) is adopted to solve the nonlinear constrained optimization problem, minimizing cost and maximizing power output. The optimization results show that, given a projected participation rate, we can identify the most crucial plots prior to the negotiation process with landowners. This will ultimately increase the efficiency of wind farm development.

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