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Abstract:
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Demand response (DR) is getting more important in smart grids. To have successful DR implementation, one of the key elements is to be able to forecast the reaction of customer due to the price change. In this work, the challenges of forecasting customer response are discussed. Different ways of modeling the customer response are presented, compared and reviewed. One new statistical model is proposed. To overcome the lack of data, we propose a framework where the customers response due to energy management system (EMS) is simulated and the results are fed into the proposed statistic model. The results of EMS and the statistical model are compared to evaluation the forecast ability of the proposed statistical model.
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