A customer baseline load prediction and optimization method based on non-demand-response factors

摘要

With the rapid growth of power demand, there are more and more concerns on demand response as it helps improve the power consumption efficiency and maintain the balance between electricity supply and consumption. Customer baseline load(CBL) forecasting is the basis of demand response implementing, and the selection of similar days and the method of calculating significantly affect the accuracy of CBL prediction. This paper proposes a baseline load forecasting and optimal method based on non-demand-response factors, considering the effects of non-demand-response factors on costumer load characteristics and CBL forecasting. The proposed method combines non-demand-response factors mining, similar days selecting and CBL calculating. A combined calculation model is adopted to predict the CBL. The case study reveals the greater accuracy of this method.