Wind Mill Pattern Optimization using Evolutionary Algorithms Article Swipe

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Mill Evolutionary algorithm Optimization algorithm Mathematical optimization Computer science Algorithm Mathematics Engineering Mechanical engineering

Charlie Vanaret , Nicolas Durand , Jean‐Marc Alliot ·

YOU? · · 2020 · Open Access · · OA: W4287687131

When designing a wind farm layout, we can reduce the number of variables by optimizing a pattern instead of considering the position of each turbine. In this paper we show that when reducing the problem to only two variables defining a grid, we can gain up to 3% of energy output on simple examples of wind farms dealing with many turbines (up to 1000) while dramatically reducing computation time. To achieve these results, we compared both a genetic algorithm and a differential evolution algorithm to previous results from the literature. These preliminary results should be extended to examples involving non-rectangular farm layouts and wind distributions that may require pattern deformation variables in order to increase solution diversity.