In order to solve the problem of active power loss and fatigue damage accumulation caused by wake effect in wind farm operation

it proposes a comprehensive method combining multi-objective optimization and multi-attribute decision-making to realize the collaborative optimization of active power and fatigue damage.Firstly

it constructs the wake attenuation and active power output model based on the Jensen wake model

and establishes the fatigue damage model combining the Palmgren-Miner linear cumulative damage theory.Then

it uses the NSGA-Ⅱ algorithm to solve the model to obtain the Pareto frontier

and finally uses the entropy weight TOPSIS method to select the optimal scheme from the Pareto solution set

and develops the exception handling mechanism to ensure the computational stability.The results show that in the 4×4 fan layout scenario

the total active power of the optimized scheme is increased by 8.9% and the fatigue damage is reduced by 2.2% compared with the benchmark scheme.The Pareto frontier analysis shows that there is a significant negative correlation between active power and damage

and the entropy weight TOPSIS method decision results verify the rationality of the weight allocation

and the proposed method can effectively balance the economy and reliability of wind farms

and provide theoretical support and engineering guidance for the optimization of complex wind farm layout.