Optimal management of demand response aggregators considering customers' preferences within distribution networks

Abstract

In this paper, a privacy-based demand response (DR) trading scheme among end-users and DR aggregators (DRAs) is proposed within the retail market framework and by Distribution Platform Optimizer (DPO). This scheme aims to obtain the optimum DR volume to be exchanged while considering both DRAs’ and customers’ preferences. A bilevel programming model is formulated in a day-ahead market within retail markets. In the upper-level problem, the total operation cost of the distribution system, which consists of DRAs’ cost and other electricity trading costs, is minimized. The production volatility of renewable energy resources is also taken into account in this level through stochastic two-stage programming and MonteCarlo Simulation method. In the lower-level problem, the electricity bill for customers is minimized for customers. The income from DR selling is maximized based on DR prices through secure communication of household energy management systems (HEMS) and DRA. To solve this convex and continuous bilevel problem, it is converted to an equivalent single-level problem by adding primal and dual constraints of lower level as well as its strong duality condition to the upper-level problem. The results demonstrate the effectiveness of different DR prices and different number of DRAs on hourly DR volume, hourly DR cost and power exchange between the studied network and the upstream network.