Abstract
Wind energy is currently one of the fastest-growing renewable energy sources in the world. For this reason, research on methods to render wind farms more energy efficient is reasonable. The optimization of wind turbine positions within wind farms makes the exploitation of wind energy more efficient and the wind farms more competitive with other energy resources. The investment costs alone for substation and electrical infrastructure for offshore wind farms run around 15–30% of the total investment costs of the project, which are considered high. Optimizing the substation location can reduce these costs, which also minimizes the overall cable length within the wind farm. In parallel, optimizing the cable routing can provide an additional benefit by finding the optimal grid network routing. In this article, the authors show the procedure on how to create an optimized wind farm already in the design phase using metaheuristic algorithms. Besides the optimization of wind turbine positions for more energy efficiency, the optimization methods of the substation location and the cable routing for the collector system to avoid cable losses are also presented.
Highlights
The main sources of energy are not sustainable and will be exhausted in the foreseeable future due to limited resources
Assuming that the wind farm is in continuous operation, the power losses in the entire collector topology could be reduced by approximately 47.22% by optimizing the substation location compared to the initial layout
For the optimizing of the radial collector topology with the proposed optimization approach, using the combination between the Genetic Algorithm and single depot non-returning Multiple Traveling Salesmen Problem, the wind farm with already optimized substation location in Figure 13b will be used to see if further savings can be made on the overall cable length of the grid network
Summary
The main sources of energy are not sustainable and will be exhausted in the foreseeable future due to limited resources. Energy companies are turning to offshore wind parks as an alternative to avoid the land rental charges that correspond to 10–18% of the total operation and maintenance costs of a wind farm [1] In addition to these advantages, offshore wind farms are more energy yielding due to the winds at sea, which could be strong over the entire day, allowing the turbine to generate more energy. It is reasonable to optimize the wake effect for maximum energy recovery, to optimize the substation location and the electrical network in the design phase of the wind farm to shorten the investment costs for the electrical infrastructure and to decrease the cable power losses over the lifetime of the wind farm. In the last section of this paper, the authors show a method to optimize the grid network of a wind farm using the combination between the Genetic Algorithm and the Multiple Traveling Salesmen Problem
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