Application Analysis of Clustering Improvement Algorithm in Cost Evaluation of Power Engineering

China’seconomy has been strengthening steadily in recent years, leading to a fast expansion of the domestic power system and a progressive increase in national power grid firms’ development projects. As a result, the price of power engineering has grown to be a significant element in project building. If the project cost is too low, it won’t be easy to ensure project quality and will impede the advancement of power engineering. One way to evaluate the cost of power production in power engineering is to use the particle swarm clustering technique. In this instance, engineers compute the overall production capacity of each source using data from several sources, including weather, wind speed, solar radiation, etc. After classifying them into many groups based on their potential, the engineer applies a formula to get the average value of each group. This formula computes the average value of various factors the engineer knows, including efficiency and maximum power production per unit area.