Retail Market Pricing Design In Smart Distribution Networks Considering Wholesale Market Price Uncertainty

In this paper, an optimal retail market pricing design for demand response in day-ahead scheduling of smart distribution networks is investigated. Through the well-designed retail market electricity price, the profit of each user is maximized; while the profit of the Distribution Network Operator (DNO) is guaranteed and the risk management model based on the Information Gap Decision Theory (IGDT) method is proposed to protect the DNO from financial risk arising out of the uncertainty of wholesale market prices. Because of the convexity of the problems of users and the DNO, the demand response program is developed based on the Predictor Corrector Proximal Multiplier, which is a distributed algorithm and guaranteed to converge to a global optimal solution, i.e. the retail market electricity price. The numerical simulation is given to show the effectiveness of the proposed pricing method.