Electricity procurement for large consumers based on Information Gap Decision Theory

In the competitive electricity market, consumers seek strategies to meet their electricity needs at minimum cost and risk. This paper provides a technique based on Information Gap Decision Theory (IGDT) to assess different procurement strategies for large consumers. Supply sources include bilateral contracts, a limited self-generating facility, and the pool. It is considered that the pool price is uncertain and its volatility around the estimated value is modeled using an IGDT model. The proposed method does not minimize the procurement cost but assesses the risk aversion or risk-taking nature of some procurement strategies with regard to the minimum cost. Using this method, the robustness of experiencing costs higher than the expected one is optimized and the related strategy is determined. The proposed method deals with optimizing the opportunities to take advantage of low procurement costs or low pool prices. A case study is used to illustrate the proposed technique.

[1]  X. Guan,et al.  Purchase allocation and demand bidding in electric power markets , 2002 .

[2]  M. Carrion,et al.  Forward Contracting and Selling Price Determination for a Retailer , 2007, IEEE Transactions on Power Systems.

[3]  Steven A. Gabriel,et al.  A Simulation Approach to Balancing Annual Risk and Reward in Retail Electrical Power Markets , 2002, IEEE Power Engineering Review.

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

[5]  Shmuel S. Oren,et al.  VaR constrained hedging of fixed price load-following obligations in competitive electricity markets , 2009, Risk Decis. Anal..

[6]  B. Daryanian,et al.  Optimal Demand-Side Response to Electricity Spot Prices for Storage-Type Customers , 1989, IEEE Power Engineering Review.

[7]  Chi-Keung Woo,et al.  Managing electricity procurement cost and risk by a local distribution company , 2004 .

[8]  A. Conejo,et al.  Risk-constrained electricity procurement for a large consumer , 2006 .

[9]  H. Co Supply and Demand Management under Inducement of Price Discounts - A Monte Carlo Simulation Analysis , 2004, ICEB.

[10]  D. Kirschen Demand-side view of electricity markets , 2003 .

[11]  A. Conejo,et al.  A Stochastic Programming Approach to Electric Energy Procurement for Large Consumers , 2007, IEEE Transactions on Power Systems.

[12]  Antonio J. Conejo,et al.  Energy procurement for large consumers in electricity markets , 2005 .

[13]  J. Bednarz,et al.  Deregulation and opportunities for industrial customers , 1998 .

[14]  Chi-Keung Woo,et al.  Efficient frontiers for electricity procurement by an LDC with multiple purchase options , 2006 .

[15]  Houmin Yan,et al.  Optimal energy purchases in deregulated California energy markets , 2000, 2000 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.00CH37077).

[16]  S. Gabriel,et al.  Optimal price and quantity determination for retail electric power contracts , 2006, IEEE Transactions on Power Systems.

[17]  Mohammad Kazem Sheikh-El-Eslami,et al.  Optimal selling price and energy procurement strategies for a retailer in an electricity market , 2009 .

[18]  P. Kleindorfer,et al.  Multi-Period VaR-Constrained Portfolio Optimization with Applications to the Electric Power Sector , 2005 .

[19]  Y. Ben-Haim Information-gap decision theory : decisions under severe uncertainty , 2001 .

[20]  R. I. Karimov,et al.  The efficient frontier for spot and forward purchases: an application to electricity , 2004, J. Oper. Res. Soc..

[21]  L. Yaan,et al.  Purchase Allocation and Demand Bidding in Electric Power Markets , 2002, IEEE Power Engineering Review.