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Article

Fusion of Improved Sparrow Search Algorithm and Long Short-Term Memory Neural Network Application in Load Forecasting

Department of Electrical Engineering, Fortune Institute of Technology, Kaohsiung 83158, Taiwan
Academic Editors: Victor Becerra and Ahmed Rachid
Energies 2022, 15(1), 130; https://doi.org/10.3390/en15010130
Received: 10 November 2021 / Revised: 11 December 2021 / Accepted: 16 December 2021 / Published: 24 December 2021
Load forecasting (LF) is essential in enabling modern power systems’ safety and economical transportation and energy management systems. The dynamic balance between power generation and load in the optimization of power systems is receiving increasing attention. The intellectual development of information in the power industry and the data acquisition system of the smart grid provides a vast data source for pessimistic load forecasting, and it is of great significance in mining the information behind power data. An accurate short-term load forecasting can guarantee a system’s safe and reliable operation, improve the utilization rate of power generation, and avoid the waste of power resources. In this paper, the load forecasting model by applying a fusion of Improved Sparrow Search Algorithm and Long Short-Term Memory Neural Network (ILSTM-NN), and then establish short-term load forecasting using this novel model. Sparrow Search Algorithm is a novel swarm intelligence optimization algorithm that simulates sparrow foraging predatory behavior. It is used to optimize the parameters (such as weight, bias, etc.) of the ILSTM-NN. The results of the actual examples are used to prove the accuracy of load forecasting. It can improve (decrease) the MAPE by about 20% to 50% and RMSE by about 44.1% to 52.1%. Its ability to improve load forecasting error values is tremendous, so it is very suitable for promoting a domestic power system. View Full-Text
Keywords: energy management systems; long short-term memory neural network; load forecasting; improved sparrow search algorithm energy management systems; long short-term memory neural network; load forecasting; improved sparrow search algorithm
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MDPI and ACS Style

Liao, G.-C. Fusion of Improved Sparrow Search Algorithm and Long Short-Term Memory Neural Network Application in Load Forecasting. Energies 2022, 15, 130. https://doi.org/10.3390/en15010130

AMA Style

Liao G-C. Fusion of Improved Sparrow Search Algorithm and Long Short-Term Memory Neural Network Application in Load Forecasting. Energies. 2022; 15(1):130. https://doi.org/10.3390/en15010130

Chicago/Turabian Style

Liao, Gwo-Ching. 2022. "Fusion of Improved Sparrow Search Algorithm and Long Short-Term Memory Neural Network Application in Load Forecasting" Energies 15, no. 1: 130. https://doi.org/10.3390/en15010130

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