tailieunhanh - Household electricity load forecasting toward demand response program using data mining techniques in a traditional power grid
At present, the continuous increase of household electricity demand is strategic and crucial in electricity demand management. Household electricity consumers can play an important role in this issue. The rationalization of electricity consumption might be achieved by using an efficient Demand Response (DR) program. In this paper a new methodology is suggested using a combination of data mining techniques namely K-means clustering, K-Nearest Neighbors (K-NN) classification and ARIMA for electricity load forecasting using consumers’ electricity prepaid bills data set of an ordinary electricity grid with prepaid electricity meters. |
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