Forecast Competition in Energy Imbalance Market

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

5 Scopus Citations
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Original languageEnglish
Pages (from-to)2397-2413
Journal / PublicationIEEE Transactions on Power Systems
Issue number3
Online published6 Oct 2021
Publication statusPublished - May 2022


Uncertainties in renewable generation make accurate load forecast essential for reliable power system operation. This paper considers energy imbalance market (EIM), where market players are allowed to procure energy ahead of time and trade the mismatch due to forecast error and strategic behaviors. The ISO sets the trading prices according to the market conditions, and pursues various system-level objectives. We first identify the power-law relationship between data volume and forecast accuracy, which enables the formulation of forecast cost model. Then, we cast the interactions in the EIM in the Stackelberg game framework with the ISO acting as the leader. We offer explicit subgame perfect equilibrium among the players in EIM, and derive the sufficient condition for the existence of unique equilibrium. Then, we show that this equilibrium, if exists, supports the maximal social welfare and under certain conditions, minimizes the total mismatch. We further examine the local and global impacts of the forecast errors under mild conditions, together with robustness analysis. Such analysis provides mechanism design guidelines for the ISO to enable the data sharing and forecast method sharing among market players in the EIM. Numerical studies further examine the effectiveness, robustness and sensitivity of the subgame.

Research Area(s)

  • Uncertainty, Renewable energy sources, Predictive models, Load forecasting, ISO, Data models, Costs, Load forecast, stackelberg game, subgame perfect equilibrium, power law, ENGINE, OPTIMIZATION, GENERATION, DEMAND, PRICE

Citation Format(s)

Forecast Competition in Energy Imbalance Market. / Cui, Jingshi; Gu, Nan; Zhao, Tianyu et al.

In: IEEE Transactions on Power Systems, Vol. 37, No. 3, 05.2022, p. 2397-2413.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review