A decision support procedure for a Price-Taker producer operating on day-ahead and physical derivatives electricity markets

In this paper we develop a decision support procedure for a Price-Taker producer on Day-Ahead and Physical Derivatives Electricity Markets. The management of the electricity generation companies and their operation in the liberalized electricity market on a short-term horizon is an interesting problem in continuous evolution. Specifically, the incorporation of the Electricity Derivatives Market is the natural improvement in the Electricity Day-Ahead Markets in most countries in the world. Therefore, the inclusion of the management of derivatives products in generation company models is also a natural improvement of them. In this work, the derivatives products in generation company models is also a natural improvement of them. In this work, the derivatives products studied are the futures contracts. This work is based on Vespucci and Innorta [2008] where a decision support procedure was developed for the short-term hydro-thermal resource scheduling problem of a power producer who operates in the liberalized electricity market and aims at maximizing his own profit. The generation company is supposed to be price-taker and the resources owned by the producer are hydroelectric plants and thermal units. In the short-term horizon (from one to ten days), the generation company has to solve the unit commitment problem for the thermal units and the economic dispatch for the available hydro plants and the committed thermal units. Its decision must be compatible with both technical constraints and market constraints. This decision support procedure has been improved modelling the settlement of the futures contracts, see Corchero and Heredia [2007], controlling the quantity that each committed thermal unit or hydro plant has to produce to fulfill these contracts. The settlement of the futures contracts could change all the decisions in the model, both th unit commitment and the economic dispatch optimal solution. The model is a mixed integer linear programming model, where the objective function represetnts the total profit determined on the bases of price forecast and the constraints describe the hydro system, the thermal system, the futures contracts settlement and the market.