Optimal Wind Bidding Strategies in Day-Ahead Markets

This paper presents a computer application for wind energy bidding in a day-ahead electricity market to better accommodate the variability of the energy source. The computer application is based in a stochastic linear mathematical programming problem. The goal is to obtain the optimal bidding strategy in order to maximize the revenue. Electricity prices and financial penalties for shortfall or surplus energy deliver are modeled. Finally, conclusions are drawn from an illustrative case study, using data from the day-ahead electricity market of the Iberian Peninsula

Offering Strategies of Wind Power Producers in a Day-Ahead Electricity Market

Part 13: Energy: Decision SupportInternational audienceThis paper presents a stochastic optimization-based approach applied to offer strategies of a wind power producer in a day-ahead electricity market. Further from facing the uncertainty on the wind power the market forces wind power producers to face the uncertainty of the market-clearing electricity price. Also, the producer faces penalties in case of being unable to fulfill the offer. An efficient mixed-integer linear program is presented to develop the offering strategies, having as a goal the maximization of profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach

A description of the operative decision-making process of a power generating company on the Nordic electricity market

In a liberalised electricity market, power generating companies face various trading possibilities. In addition, they have to take scheduling decisions. Both kinds of decisions are affected by uncertainties, e.g. power plant outages, uncertain market prices for electricity or imperfect wind power forecasts. This paper presents an overview of the decision-making process of a power generating company on the Nordic electricity market and illustrates how uncertainties affect this process. As a power generating company’s return on investment arises - at least partly - from its trading and scheduling decisions, it is important to optimise those decisions. Therefore, selected optimisation models are listed in a condensed manner. The paper also includes a both detailed and comprehensive description of the market design in the Nordic countries.</p