This paper presents a new capacity planning method that utilizes the complementary characteristics of wind and solar power output.It addresses the limitations of relying on a single metric for a comprehensive assessme...This paper presents a new capacity planning method that utilizes the complementary characteristics of wind and solar power output.It addresses the limitations of relying on a single metric for a comprehensive assessment of complementarity.To enable more accurate predictions of the optimal wind-solar ratio,a comprehensive complementarity rate is proposed,which allows for the optimization of wind-solar capacity based on this measure.Initially,the Clayton Copula function is employed to create a joint probability distribution model for wind and solar power,enabling the calculation of the comprehensive complementarity rate.Following this,a joint planning model is developed to enhance the system’s economy and reliability.The goal is to minimize total costs,load deficit rates,and curtailment rates by applying an ImprovedMulti-Objective Particle SwarmOptimization algorithm(IMOPSO).Results show that when the proportion of wind power reaches 70%,the comprehensive complementarity rate is optimized.This optimization leads to a 14.83%reduction in total costs and a 9.27%decrease in curtailment rates.Compared to existing studies,this paper offers a multidimensional analysis of the relationship between the comprehensive complementarity rate and the optimal wind-solar ratio,thereby improving predictive accuracy and providing a valuable reference for research on the correlation between wind and solar power.展开更多
基金This work was supported by Inner Mongolia Natural Science Foundation Project and the Optimization of Exergy Efficiency of a Hybrid Energy Storage System with Crossover Control for Wind Power(2023JQ04).
文摘This paper presents a new capacity planning method that utilizes the complementary characteristics of wind and solar power output.It addresses the limitations of relying on a single metric for a comprehensive assessment of complementarity.To enable more accurate predictions of the optimal wind-solar ratio,a comprehensive complementarity rate is proposed,which allows for the optimization of wind-solar capacity based on this measure.Initially,the Clayton Copula function is employed to create a joint probability distribution model for wind and solar power,enabling the calculation of the comprehensive complementarity rate.Following this,a joint planning model is developed to enhance the system’s economy and reliability.The goal is to minimize total costs,load deficit rates,and curtailment rates by applying an ImprovedMulti-Objective Particle SwarmOptimization algorithm(IMOPSO).Results show that when the proportion of wind power reaches 70%,the comprehensive complementarity rate is optimized.This optimization leads to a 14.83%reduction in total costs and a 9.27%decrease in curtailment rates.Compared to existing studies,this paper offers a multidimensional analysis of the relationship between the comprehensive complementarity rate and the optimal wind-solar ratio,thereby improving predictive accuracy and providing a valuable reference for research on the correlation between wind and solar power.
