Spatial Allocation of Wind Farms and Flexibility Requirements: A Genetic Algorithm-based Optimization Approach

This paper addresses the impact of spatial allocation on the flexibility requirements of wind farms in the context of the mid-term development of wind energy exploitation in Hungary. As a starting point for evaluating flexibility requirements, a wind power simulation model is adopted that converts hourly wind speed time series derived from climate reanalysis into hourly aggregate power output using theoretical power curves. This simulation model allows for evaluating various flexibility metrics for both existing and hypothetical wind farms. As a second step, a Genetic Algorithm (GA) is integrated with the simulation environment to find an optimal subset of hypothetical wind farms with respect to flexibility requirements. The application of GA reveals insights into how spatially optimizing wind farm placement can significantly reduce flexibility requirements. This finding can have practical implications for policy-makers and planners in the renewable energy sector, especially given the evolving regulatory landscape and increasing focus on grid stability.