Abstract
Due to the excellent characteristics of resource conservation and environmental protection, wind energy has been developed on a large scale, and grid-connected operation has been gradually realized. However, there are severe interruptions in wind power generation, so it is difficult to make accurate predictions, which inevitably leads to many problems in the power system when generating electricity. The previous model is no longer applicable to the current situation, and a new model needs to be established to improve it. The economic dispatch model and method meet the needs of large-scale wind power grid integration under the current situation of rapid development of new energy in my country. Therefore, this paper takes the dynamic economic dispatch of power system as the research object, and uses particle swarm optimization algorithm to solve the problem, in order to ensure reliable power supply, the micro gas turbine power generation system has the largest output, and the power supply operation cost is lower when considering the complementary characteristics of wind and solar.
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Du, G., Almulihi, F. (2023). Dynamic Economic Scheduling Optimization Based on Particle Swarm Optimization Algorithm. In: Abawajy, J.H., Xu, Z., Atiquzzaman, M., Zhang, X. (eds) Tenth International Conference on Applications and Techniques in Cyber Intelligence (ICATCI 2022). ICATCI 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 169. Springer, Cham. https://doi.org/10.1007/978-3-031-28893-7_43
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