Study of Short-term Load Forecasting Based on FCM and Multiple WOA-LSSVM Combination under Electricity Market Environment
Author:
Affiliation:
1. Economic Research Institute State Grid Jiangxi Electric Power Company,China,330000
2. South China University of Technology,School of Electric Power Engineering,Guangzhou,China,510641
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10061847/10061862/10062299.pdf?arnumber=10062299
Reference12 articles.
1. Short?term substation load forecast based on wide & Deep?LSTM model;haican;Power System Technology,2020
2. A new method of load forecasting based on generalized autoregressive conditional heteroscedasticity model;chen;Automation of Electric Power Systems,2007
3. A Hybrid Short-Term Load Forecasting Model Based on Improved Fuzzy C-Means Clustering, Random Forest and Deep Neural Networks
4. Industrial Power Load Forecasting Method Based on Reinforcement Learning and PSO-LSSVM
5. A hybrid electricity price scenario generation method for stochastic virtual bidding in the electricity market
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