Efficient layout optimization of offshore wind farm based on load surrogate model and genetic algorithm

• Published in: Energy (Oxford) Vol. 309; p. 133106
• Main Authors: Zhang, Xiaofeng, Wang, Qiang, Ye, Shitong, Luo, Kun, Fan, Jianren
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15-11-2024
• Subjects: Genetic algorithm; Layout optimization; Load; Offshore wind farm; Surrogate model; Load; Surrogate model; Offshore wind farm; Genetic algorithm; Layout optimization
• ISSN: 0360-5442
• DOI: 10.1016/j.energy.2024.133106

Wind farm layout optimization (WFLO) has become a significant approach to enhancing the efficiency of wind energy utilization. However, load also represents a critical factor that must be considered during optimization. To enhance power generation while controlling loads within limitations, an innovative load-constrained layout optimization method that employs a surrogate model based on artificial neural networks and genetic algorithms was proposed. This paper verified the accuracy of the surrogate model and then conducted layout optimizations on a single and a full wind condition case to assess the proposed method. The results indicated that the mean absolute percentage errors of load channels can meet the precision requirements for WFLO. A comparison of layout optimization results between the method proposed in this paper and the traditional method showed that in the single-wind-condition case, the method proposed in this paper reduced the maximum load by 5.64 % compared to the traditional method, with nearly identical power output; in the full-wind-condition case, the reduction of maximum load was 1.70 %, while only sacrificing the annual power generation by 0.10 %. This study provides a load-constrained WFLO method, promising to effectively ensure the lifespan of wind turbines while increasing power generation and offering significant engineering value.
•A wind farm layout optimization method with load constraint was proposed.•Surrogate models were employed initially in GA optimization to evaluate loads.•Limit wind turbine loads while maintaining power generation in two cases.•Guide wind farm layout optimization in engineering projects.