Modeling demand response based on utility function considering wind profit maximization in the day-ahead market

Abstract

In this paper, behavior of electricity customers is modeled using utility function. The utility function which measures customer’s preferences is an important concept in microeconomics. This function interprets how a rational consumer would make consumption decisions. Based on the utility function, an economic demand model is developed as a function of customer risk aversion behavior to consider the effect of incentive payment on electricity consumption. The proposed model is designed to maximize the individual customer’s welfare under incentive-based demand response (DR) programs. Then, the DR is used to maximize wind power profit in the day-ahead market. To this end, the wind power producer can either use real time balancing market or DR to cope with the energy submitted in the day-ahead market and the delivered energy. To determine the day-ahead and balancing market prices, a probabilistic two-step market clearing optimization is solved considering uncertainties of wind power and behavior of electricity customers. The results show that as risk aversion behavior increases, more incentive payment is needed to convince the customer to reduce his/her demand. The numerical results demonstrate effectiveness of the proposed DR model in improving the wind generation profit in the day-ahead market.