Sharing wind power forecasts in electricity markets: A numerical analysis

Lazaros Exizidis, S. Jalal Kazempour, Pierre Pinson, Zacharie de Greve and François Vallée

Applied Energy, 2016, vol. 176, issue C, 65-73

Abstract: In an electricity pool with significant share of wind power, all generators including conventional and wind power units are generally scheduled in a day-ahead market based on wind power forecasts. Then, a real-time market is cleared given the updated wind power forecast and fixed day-ahead decisions to adjust power imbalances. This sequential market-clearing process may cope with serious operational challenges such as severe power shortage in real-time due to erroneous wind power forecasts in day-ahead market. To overcome such situations, several solutions can be considered such as adding flexible resources to the system. In this paper, we address another potential solution based on information sharing in which market players share their own wind power forecasts with others in day-ahead market. This solution may improve the functioning of sequential market-clearing process through making more informed day-ahead schedules, which reduces the need for balancing resources in real-time operation. This paper numerically evaluates the potential value of sharing forecasts for the whole system in terms of system cost reduction. Besides, its impact on each market player’s profit is analyzed. The framework of this study is based on a stochastic two-stage market setup and complementarity modeling, which allows us to gain further insights into information sharing impacts.

Keywords: Wind power; Forecast sharing; Day-ahead; Real-time; Two-stage market clearing; Out-of-sample simulation (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (13)

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DOI: 10.1016/j.apenergy.2016.05.052

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