Trading Wind Generation From Short-Term Probabilistic Forecasts of Wind Power

Abstract

Abstract-Due to the fluctuating nature of the wind resource, a wind power producer participating in a liberalized electricity market is subject to penalties related to regulation costs. Accurate forecasts of wind generation are therefore paramount for reducing such penalties and thus maximizing revenue. Despite the fact that increasing accuracy in spot forecasts may reduce penalties, this paper shows that, if such forecasts are accompanied with information on their uncertainty, i.e., in the form of predictive distributions, then this can be the basis for defining advanced strategies for market participation. Such strategies permit to further increase revenues and thus enhance competitiveness of wind generation compared to other forms of dispatchable generation. This paper formulates a general methodology for deriving optimal bidding strategies based on probabilistic forecasts of wind generation, as well as on modeling of the sensitivity a wind power producer may have to regulation costs. The benefits resulting from the application of these strategies are clearly demonstrated on the test case of the participation of a multi-MW wind farm in the Dutch electricity market over a year.

On the management of wind power intermittency

“…An influencing factor in integrated SS is modelling the wind generation uncertainty. The risk faced by wind power producers would increase without considering this uncertainty [86,87]. The most significant reasons of using PHS with wind power generation would be as follows:…”

A New Battery Energy Storage Charging/Discharging Scheme for Wind Power Producers in Real-Time Markets

“…The bidding strategy in the spot market is exclusively studied in [5][6][7][8][9], that is out of the scope of this paper. The DA market clearing prices is illustrated in Figure 1.…”

“…Secondly, the bidding approach attempts to optimize the bidding strategy of WPPs in the spot market [5][6][7][8][9]. This strategy takes into account both the asymmetry of regulation prices (up and down regulation) and the availability of the probabilistic error of prediction tools.…”

“…This will result in a reduction of overall regulation cost. The main drawback of this approach is that the credible probabilistic model of prediction error is not always achievable that requires such a long time data [6].…”

Reliability diagrams for non‐parametric density forecasts of continuous variables: Accounting for serial correlation

“…From a decision-making perspective, it has been shown that pricing weather derivatives based on density forecasts would bring significant benefits (Taylor and Buizza, 2006). In parallel for the example case of renewable energy, the production of which is a direct function of meteorological conditions, it is argued that optimal management and trading of generated energy should be based on probabilistic forecasts (Pinson, et al, 2007a). The transition from point to probabilistic forecasts is not only observed in the meteorological literature; probabilistic forecasts are also becoming customary products in economics and finance (Abramson and Clemen, 1995;Tay and Wallis, 2000;Timmermann, 2000) or more generally in management sciences.…”