Including the behavioral aspects of customers in demand response model: Real time pricing versus peak time rebate

Abstract

Demand response (DR) programs enable the demand side to actively optimize its consumption in response to the dynamic prices. The flexibility of consumption can be a useful tool for the electricity market to resolve many of its operation and reliability issues. Several models have been proposed in the literature to explain the human behavior aspect of the customers. These models are based on the classical utility function, but some studies have shown that the price effect on the customer's decision in areas like energy efficiency and consumption reduction depends upon many behavioral characteristics and without considering such characteristics, the results are unrealistic. Thus, loss aversion plays a crucial role in the decision making. So, in this paper, the impact of two time based rate DR programs have been investigated on the peak reduction considering the loss-aversion and its impact on the perception of the customers. Real time pricing and peak time rebate are two competing alternatives for peak reduction. A modified price elasticity based DR model is proposed to simulate the price response of the customers in the presence of both DR programs. MATLAB software is used to implement the DR models. The models are examined on one of the summer days of 2014 in Connecticut. The data is reported by New England ISO. Two PTR cases are generated for this study, with and without considering the loss aversion. Under both scenarios, without considering the loss aversion, PTR has advantages over RTP, but considering the loss-aversion, RTP showed a superior performance. It is shown that the behavioral characteristics of the customers, loss-aversion in this case, is indispensable in the selection of the proper program.