Application of Particle Swarm Clustering Algorithm in Power Engineering Cost Estimation

In recent years, with the continuous enhancement of China's economic strength, the scale of the domestic power system is expanding rapidly, and the number of construction projects of national power grid enterprises is also gradually increasing. Therefore, the cost of power engineering cost has become an important factor affecting the project construction. If the cost is too high, it will affect the domestic economic growth, and the power engineering project can not promote the sustainable construction; If the project cost is too low, the quality of the project is not easy to be guaranteed, and it will hinder the development of power engineering. The application of particle swarm clustering algorithm in power engineering cost estimation is a method to estimate the cost of power generation. This method can be used for traditional energy and renewable energy. In this case, engineers use data from various sources, such as weather, wind speed, solar radiation, etc., and use these data to calculate the total production capacity of each source. Then, the engineer divides them into several groups according to their potential, and uses a formula to calculate the average value of each group, which calculates the average value of different parameters known to the engineer, such as maximum power output per unit area, efficiency, etc.