Risk-constrained self-scheduling of a fuel and emission constrained power producer using rolling window procedure

Abstract This work addresses a relevant methodology for self-scheduling of a price-taker fuel and emission constrained power producer in day-ahead correlated energy, spinning reserve and fuel markets to achieve a trade-off between the expected profit and the risk versus different risk levels based on Markowitz’s seminal work in the area of portfolio selection. Here, a set of uncertainties including price forecasting errors and available fuel uncertainty are considered. The latter uncertainty arises because of uncertainties in being called for reserve deployment in the spinning reserve market and availability of power plant. To tackle the price forecasting errors, variances of energy, spinning reserve and fuel prices along with their covariances which are due to markets correlation are taken into account using relevant historical data. In order to tackle available fuel uncertainty, a framework for self-scheduling referred to as rolling window is proposed. This risk-constrained self-scheduling framework is therefore formulated and solved as a mixed-integer non-linear programming problem. Furthermore, numerical results for a case study are discussed.

[1]  F. Nogales,et al.  Risk-constrained self-scheduling of a thermal power producer , 2004, IEEE Transactions on Power Systems.

[2]  Fushuan Wen,et al.  Coordination of bidding strategies in day-ahead energy and spinning reserve markets , 2002 .

[3]  J. Ramos,et al.  Electricity Market Price Forecasting Based on Weighted Nearest Neighbors Techniques , 2007, IEEE Transactions on Power Systems.

[4]  Rabih A. Jabr.  Self-scheduling under ellipsoidal price uncertainty: conic-optimisation approach , 2007 .

[5]  J. Contreras,et al.  Forecasting next-day electricity prices by time series models , 2002 .

[6]  David Kendrick,et al.  GAMS, a user's guide , 1988, SGNM.

[7]  J. Contreras,et al.  ARIMA models to predict next-day electricity prices , 2002 .

[8]  Antonio J. Conejo,et al.  Self-Scheduling of a Hydro Producer in a Pool-Based Electricity Market , 2002, IEEE Power Engineering Review.

[9]  F. Nogales,et al.  Price-Taker Bidding Strategy under Price Uncertainty , 2002, IEEE Power Engineering Review.

[10]  J. Sharma,et al.  Short term hydro scheduling using two-phase neural network , 2002 .

[11]  Fushuan Wen,et al.  Optimal bidding strategies for competitive generators and large consumers , 2001 .

[12]  A. Conejo,et al.  Optimal Response of a Power Generator to Energy, AGC, and Reserve Pool-Based Markets , 2002, IEEE Power Engineering Review.

[13]  A. Conejo,et al.  Optimal response of a thermal unit to an electricity spot market , 2000 .

[14]  Mohammad Shahidehpour,et al.  Market operations in electric power systems , 2002 .

[15]  T. Dillon,et al.  Electricity price short-term forecasting using artificial neural networks , 1999 .

[16]  Rajat K. Deb.  Operating Hydroelectric Plants and Pumped Storage Units in a Competitive Environment , 2000 .

[17]  Karl V. Bury,et al.  Statistical Distributions in Engineering: Statistics , 1999 .

[18]  Ning Lu,et al.  Pumped-storage hydro-turbine bidding strategies in a competitive electricity market , 2004, IEEE Transactions on Power Systems.

[19]  M. Parsa Moghaddam,et al.  Risk-constrained dynamic self-scheduling of a pumped-storage plant in the energy and ancillary service markets , 2009 .

[20]  Heather Fry,et al.  A user’s guide , 2003 .

[21]  A. Stuart,et al.  Portfolio Selection: Efficient Diversification of Investments , 1959 .

[22]  Stein-Erik Fleten,et al.  Short-term hydropower production planning by stochastic programming , 2008, Comput. Oper. Res..

[23]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[24]  Hossein Seifi,et al.  On the self-scheduling of a power producer in uncertain trading environments , 2008 .

[25]  P. Attaviriyanupap,et al.  A fuzzy-optimization approach to dynamic economic dispatch considering uncertainties , 2004, IEEE Transactions on Power Systems.

[26]  G. Sheblé,et al.  Power generation operation and control — 2nd edition , 1996 .

[27]  Farshid Keynia,et al.  Day ahead price forecasting of electricity markets by a mixed data model and hybrid forecast method , 2008 .

[28]  H.Y. Yamin.  Fuzzy self-scheduling for GenCos , 2005, IEEE Transactions on Power Systems.

[29]  Y.-y. Hong,et al.  Locational marginal price forecasting in deregulated electricity markets using artificial intelligence , 2002 .

[30]  S. M. Shahidehpour,et al.  Self-scheduling and energy bidding in competitive electricity markets , 2004 .

[31]  R. N. Adams,et al.  The flexible rolling schedule for infinite-horizon optimality in generation expansion planning , 1992 .

[32]  R. Jabr.  Robust self-scheduling under price uncertainty using conditional value-at-risk , 2005, IEEE Transactions on Power Systems.