Selling price for a retailer using a comprehensive methodology with risk management

Retail electricity markets are critical in assuring that final customers receive the full benefits of competition in wholesale electricity markets. Retailers act as a service interface between the energy market and customers. In this paper, a comprehensive methodology to solve the problem that retailers face in an electricity energy market, including risk management, is proposed. The methodology consist of two main stages, at the first stage, consumers are characterized and classified using clustering techniques, and at the second stage an optimization problem for each group of consumers is solved to get the optimal energy offer. The optimization problem considers uncertainty of price from the wholesale market through a scenario tree, and the Conditional Value at Risk (CVaR) as risk measure. The problem results into a quadratic optimization problem, and it is solved using the GAMS software.