Wind farm layout optimisation considering commercial wind turbines using parallel reference points, radial space division and reference vector guided EA-based approach

Abstract

In this study, a new multiobjective optimisation-based approach for Wind Farm Layout Optimisation (WFLO) is developed. The proposed approach combines four distinct Evolutionary algorithms (EA) based on multiobjective optimisation methods into a more powerful parallel method. The four combined algorithms are: the Radial Space Division based EA (RSEA), the Reference Points based EA (RPEA), RVEA embedded with the reference vector regeneration strategy (RVEAa) and the Reference Vector Guided EA (RVEA). The proposed approach is PRPSVEAa, where the letter P stands for parallel, and the remaining letters are used from different combined methods. In this research, four case studies have been investigated using four different commercial wind turbines where the hub heights of Wind Turbines (WT) are kept the same in some cases and varied in some. The results indicate that the Pareto set of solutions varies from each other with different numbers of WT as they spread over a wide region. This offers the designer the most suitable layout solution based on technical and economic factors. The obtained result can also be used to plan for future extensions of the research work.

Keywords

• Real wind turbine
• Wind farm layout
• EA multiobjective optimisation
• Maximum efficiency
• Maximum power