Virtual energy storage modeling based on electricity customers' behavior to maximize wind profit

Nowadays utilizing renewable energy resources (RES) has become one of the main features of the modern power systems. Despite the many benefits of these resources, the output power uncertainty limits RES competitive ability with the other conventional power producers. Using the energy storage system (ESS) is an effective solution to resolve the output power uncertainty problem. However, ESS remains to be an expensive technology although there are declinations in the cost in recent years. To this end, this paper utilizes demand response resources as a virtual energy storage (VES) in which incentive and discount payment are applied to convince the customers to reduce or increase their consumptions, respectively. The consumption decreasing and increasing provide functions similar to discharging and charging an ESS. Customer behavior plays an important role in designing an effective VES. So, this paper employs the concept of the utility function considering different risk aversion coefficients to model the different customers' behavior. In the numerical Section, the proposed VES is implemented considering different customer types with different risk aversion coefficients to improve the wind generation profit in the day-ahead. From the results, as the risk aversion coefficient increases, a high incentive/ discount is needed to convince the customer to participate in the VES.