Research On Wind Farm Location And Wind Turbine Layout Optimization

With the introduction of China’s "carbon peak" and "carbon neutrality" development strategies,the proportion of clean energy consumption continues to rise.Wind energy,as a pollution-free renewable energy source,is currently one of the most competitive and mature clean energy options.In the process of harnessing wind energy resources,two crucial factors are wind farm site selection and optimization of wind turbine layout.In the research on wind farm site selection,the Analytic Hierarchy Process(AHP)is commonly used to make multi-criteria decisions based on factors such as wind energy resources and climatic conditions.However,this method suffers from a lack of quantifiability.AHP heavily relies on subjective judgments and preferences of experts,which can lead to results lacking objectivity and reliability.Additionally,the same expert may provide different judgments in different times or environments,which may raise doubts about the credibility of the results.Therefore,a quantitative model is needed to describe the wind farm site selection scenario.In the study of wind turbine layout optimization,wake effect is an important consideration.The wake effect affects the power generation of downstream wind turbines and creates uneven lift and drag on the blades,thereby reducing the lifespan and efficiency of wind turbines.Therefore,reducing the mutual interference of wake effects between wind turbines is a key method for improving the power generation efficiency of wind farms and the rational utilization of wind energy resources.This article conducts in-depth research on wind farm site selection and wind turbine layout optimization,focusing on the following two aspects:(1)To quantify the wind farm site selection model,this article proposes a multi-objective optimization model that comprehensively considers the total cost and power generation of wind farms.In the process of solving the model,to address the premature convergence or local convergence issues that may occur with the traditional NSGA2 algorithm,instead of selecting the optimal individual as the next generation population,this study retains a portion of the suboptimal results that explore the solution space.Simulation experiments demonstrate that the improved NSGA2 algorithm has certain guiding significance in the wind farm site selection process.(2)To reduce the impact of wake effects,this article proposes a wind turbine layout optimization model that considers variable hub heights.In this model,the crucial parameter of hub height information is introduced.Additionally,this article presents a novel algorithm that combines a greedy strategy with differential evolution and incorporates a multi-strategy mechanism to solve the wind turbine layout optimization model considering variable hub heights.The adjustment strategies of this algorithm comprehensively consider the characteristics of wind turbine variable hub heights and provide diversified search methods for the cost optimization problem.It also introduces a parameter adaptive mechanism considering mutation and crossover factors,which balances the algorithm’s global search capability and local search capability,thereby achieving better results in terms of levelized cost of electricity.Simulation experiments validate the superiority of the differential evolution and greedy method with multiple strategies algorithm.