Cost Effective Operational Planning of a Retail Market with Distributed Generations

Abstract

In the retail electricity market, retailers play a very crucial role. They exchange energy through the grid and serve the load demand. Encouragement to deploy more renewable energy sources and storage devices (R&SD) is giving an opportunity to the retailers to install their own distributed generators (DG). In such cases, a market framework must be designed to maintain the rational behavior of an electricity market. In this paper, a retail market simulation model is framed considering R&SD owned by retailers. Profit earned by all retailers is maximized individually, and loss is also minimized from a utility point of view. In this way, this problem can be designed in many ways. Two distinct algorithms based on mixed-integer conic programming are proposed here, depending upon the different solution approaches. The first algorithm is solved as a multi-objective optimization problem (OP) using $\epsilon$-constraint method. The second algorithm is solved as mathematical programming with equilibrium constraints (MPEC) model, which is converted into a single objective OP. A non-cooperative game theory approach is employed in this algorithm to satisfy the multiple objectives for different players (retailers). The proposed methodology is implemented on the 16-bus distribution test system to analyze the feasibility and effectiveness of the proposed algorithms. Results of the proposed algorithms are also compared with the existing algorithm comprising no retailers.