Power load forecasting is an important task of smart grid, which is of great significance to the sustainable development of society. In this paper, a hybrid support vector regression (HSVR) is raised for the medium an...
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Power load forecasting is an important task of smart grid, which is of great significance to the sustainable development of society. In this paper, a hybrid support vector regression (HSVR) is raised for the medium and long term load forecasting. To further improve prediction accuracy, the coupling and interdependent relationship between hyperparameters and model parameters in the optimization process is focused. A hierarchicaloptimizationmethod based on nested strategy and state transition algorithm (STA) is proposed to find optimal parameters. The effectiveness of the proposed hierarchicaloptimizationmethod is confirmed on several benchmarks, and the resulting hierarchicaloptimizationmethod based SVR is also successfully applied to a real industrial power load forecasting problem in China.
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