Impacts of large-scale penetration of wind power on day-ahead electricity markets and forward contracts

Utilization of renewable energy resources, especially wind power, for producing electric energy is growing fast in the world. Besides the environmental advantages, the variability, unpredictability, and uncontrollability of the wind turbines' output power face the market players with different financial risks. Producers and consumers prefer to have a stable income in the power system and try to avoid the uncertainties and fluctuations in their profits. In this situation, forward contracts are used as efficient tools for helping the market players to hedge themselves against these risks. Since market players participate in both forward and day-ahead markets, their actions in each market affect the other market. So, day-ahead and forward markets affect each other. In this paper, the behavior of market players in the forward and day-ahead electricity markets in the presence of largescale wind farms are studied. To this end, first, the contracting period is modeled considering different outcomes for the delivery period and then, the delivery period is modeled considering the contracting period outcomes. Equilibrium models are presented for each model. Both uniform and pay-as-bid pricing models for the day-ahead market are considered in the modeling procedure. A recently introduced risk management method called concern scenarios is upgraded and applied to model the risk management preferences of market players. Simulation results are presented, analyzed, and compared for models by applying them to a test system case study.

Automated summary

The behavior of market players in the forward and day-ahead electricity markets in the presence of large-scale wind farms is studied in this paper. Modeling the delivery period considering different outcomes for the contracting period and then modeling the contracting period considering the delivery period outcomes. Equilibrium models are presented for each model, with both uniform and pay-as-bid pricing models considered for the day-ahead market. Simulation results are presented, analyzed, and compared for models applied to a test system case study.