Abstract
This paper presents a new load forecasting system based on the complex system theory. The power network is a complex nonlinear system. The complex system analysis theory is applied to divide a power network into some sub-system according to its different area position and load type, and then uses the BP neural network incorporated with weather influence factors forecast the load value respectively. Experimental results verify that this method can help to improve the forecasting accuracy.
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