ترکیب هیدرو نسل و انرژی بادی : مناقصه و بهره برداری در بازارهای لحظه ای برق

Wind generation is growing rapidly in all the world, especially in Europe. The power produced by this kind of generation is difficult to predict and the predictions are not very accurate. In most systems these imbalances are costly. These penalties reduce the revenue for the wind generation company (WGENCOs). An option to solve this problem would be to work together with another agent. In this paper, a combined strategy for bidding and operating in a power exchange is presented. It considers the combination of a WGENCO and a hydro-generation company (HGENCO). The mathematical formulation for the optimal bids and for the optimal operation is presented, as well as results from realistic cases.

The great amount of non-dispatchable wind energy connected to the grid has led the regulatory authorities in Spain to promote the integration of this kind of energy in the electricity market. The rules that these producers must follow are the same of any other generator. This means that a wind generation company must make a schedule for the day ahead market, and that penalties must be paid if this schedule is not followed. This paper presents two methods to minimize these penalties, taking into account the stochastic nature of the primary source of this energy, the wind. The first method is based on a statistical analysis of the expected production probability, in order to minimize the risk of the prediction for the day ahead. The second one employs a hydro-plant (HGENCO), in order to minimize the penalty for incurring in imbalance. In both cases, it is assumed that the company (WGENCO and HGENCO) is a price-taker.

In this paper, two different strategies for maximizing the revenue of a WGENCO have been presented: (a) the short term wind power prediction tool SIPREOLICO has been used to get the optimal WGENCO bid and (b) a hydro-system was used to make the optimal joint operation maximizing the whole revenue by trying to minimize penalties. Both models have been successfully tested on realistic case studies. The benefits of a short term wind power prediction tool such as SIPREÓLICO have been made apparent under different hypotheses. The convenience of using such a tool when a wind farm is in an electricity market is quantified.