Cost and capacity optimization of regional wind-hydrogen integrated energy system

The accurate aging evaluation is one of the important factors to find the optimal operation mode of the regional wind-hydrogen integrated energy system (RWHIES). In this article, a wind turbine (WT) power prediction method is proposed based on wind physical information and topography characteristics (WPITC). By making full use of the modified numerical weather data, the wind power can be predicted by combining wind conditions and terrain information. Under the guidance of the WT power prediction model, the aging state is evaluated and a RWHIES model is proposed, which allows striving to maximizing the production capacity with the minimal cost. An improved multi-objective dragonfly algorithm (IMODA) is proposed to address the optimization problem. Finally, three different cases are conducted to analyze the relationship between cost and capacity, which indicates that the proposed approach can improve the accuracy and speed of the cost and capacity optimization for RWHIES.