Interval prediction algorithm and optimal scenario making model for wind power producers bidding strategy

Nowadays, renewable energies are important sources for supplying electric power demand and a key entity of future energy markets. Therefore, wind power producers (WPPs) in most of the power systems in the world have a key role. On the other hand, the wind speed uncertainty makes WPPs deferent power generators, which in turn causes adequate bidding strategies, that leads to market rules, and the functional abilities of the turbines to penetrate the market. In this paper, a new bidding strategy has been proposed based on optimal scenario making for WPPs in a competitive power market. As known, the WPP generation is uncertain, and different scenarios must be created for wind power production. Therefore, a prediction intervals method has been improved in making scenarios and increase the accuracy of the presence of WPPs in the balancing market. Besides, a new optimization algorithm has been proposed called the grasshopper optimization algorithm to simulate the optimal bidding problem of WPPs. A set of numerical examples, as well as a case-study based on real-world data, allows illustrating and discussing the properties of the proposed method

Cournot Versus Supply Functions: What does the Data Tell us?

The liberalization of the electricity sector increases the need for realistic and robust models of the oligopolistic interaction of electricity firms. This paper compares the two most popular models: Cournot and the Supply Function Equilibrium (SFE), and tests which model describes the observed market data best. Using identical demand and supply specifications, both models are calibrated to the German electricity market by varying the contract cover of firms. Our results show that each model explains an identical fraction of the observed price variation. We therefore suggest using Cournot models for short term analysis, as more market details, such as network constraints, can be accommodated. As the SFE model is less sensitive to the choice of the calibration parameters, it might be more appropriate for long term analysis, such as the study of a merger.supply function equilibrium;Cournot competition;electricity markets

Simulation and Evaluation of Zonal Electricity Market Designs

Zonal pricing with countertrading (a market-based redispatch) gives arbitrage opportunities to the power producers located in the export-constrained nodes. They can increase their profit by increasing the output in the day-ahead market and decrease it in the real-time market (the inc-dec game). We show that this leads to large inefficiencies in a standard zonal market. We also show how the inefficiencies can be significantly mitigated by changing the design of the real-time market. We consider a two-stage game with oligopoly producers, wind-power shocks and real-time shocks. The game is formulated as a two-stage stochastic equilibrium problem with equilibrium constraints (EPEC), which we recast into a two-stage stochastic Mixed-Integer Bilinear Program (MIBLP). We present numerical results for a six-node and the IEEE 24-node system

Cournot versus Supply Functions: What Does the Data tell us?

The liberalization of the electricity sector increases the need for realistic and robust models of the oligopolistic interaction of electricity firms. This paper compares the two most popular models: Cournot and the Supply Function Equilibrium (SFE), and tests which model describes the observed market data best. Using identical demand and supply specifications, both models are calibrated to the German electricity market by varying the contract cover of firms. Our results show that each model explains an identical fraction of the observed price variation. We therefore suggest using Cournot models for short term analysis, as more market details, such as network constraints, can be accommodated. As the SFE model is less sensitive to the choice of the calibration parameters, it might be more appropriate for long term analysis, such as the study of a merger.supply function equilibrium;Cournot competition;electricity markets

Cournot versus supply functions: what does the data tell us?

The liberalization of the electricity sector increases the need for realistic and robust models of the oligopolistic interaction of electricity firms. This paper compares the two most popular models: Cournot and the Supply Function Equilibrium (SFE), and tests which model describes the observed market data best. Using identical demand and supply specifications, both models are calibrated to the German electricity market by varying the contract cover of firms. Our results show that each model explains an identical fraction of the observed price variation. We therefore suggest using Cournot models for short term analysis, as more market details, such as network constraints, can be accommodated. As the SFE model is less sensitive to the choice of the calibration parameters, it might be more appropriate for long term analysis, such as the study of a merger.supply function equilibrium, Cournot competition, electricity markets

Nash Equilibrium of Joint Day-ahead Electricity Markets and Forward Contracts in Congested Power Systems

Uncertainty in the output power of large-scale wind power plants (WPPs) can face the electricity market players with undesirable profit variations. Market players can hedge themselves against these risks by participating in forward contracts markets alongside the day-ahead markets. The participation of market players in these two markets affects their profits and also the prices and power quantities of each market. Moreover, limitations in the transmission grid can affect the optimal behavior of market players. In this paper, a Cournot Nash equilibrium model is proposed to study the behavior of market players in the forward contract market and the day-ahead electricity market in a congested power system with large-scale integration of WPPs. The proposed method is applied to a test system, and the results are discussed