Affiliations: [a] State Grid Chongqing Electric Power Company, Chongqing, China | [b] China Electric Power Research Institute, Beijing, China
Correspondence:
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Corresponding author: Ninghui Han, China Electric Power Research Institute, Beijing, China. E-mail: [email protected].
Abstract: The evaluation of new power system construction is the research foundation for improving the flexible regulation ability and comprehensive operational efficiency of new power systems, and achieve the comprehensive goals of safe power supply, green consumption, and economic efficiency. However, the existing research on the evaluation index system of new power system construction can not fully reflect the main objectives of new power system construction. Therefore, this paper first develops a source-load and green-intelligence multi-level and multi-dimensional evaluation system for new power system construction from source-load side equipment, green power, reliable power supply, and intelligent power consumption. Secondly, a hybrid optimization algorithm is proposed based on fluid search algorithm (FSO) for improving the Long Short-Term Memory (LSTM) neural network parameter updating method. Then, the improved LSTM neural network is applied to the construction evaluation of the new power system. Finally, the simulation results show that the evaluation error of the new power system construction evaluation method is 0.0063, which has a high evaluation.
Keywords: New power system, construction evaluation system, LSTM neural networks, fluid search algorithms
