Price-based unit commitment: a case of Lagrangian relaxation versus mixed integer programming

This paper formulates the price-based unit commitment (PBUC) problem based on the mixed integer programming (MIP) method. The proposed PBUC solution is for a generating company (GENCO) with thermal, combined-cycle, cascaded-hydro, and pumped-storage units. The PBUC solution by utilizing MIP is compared with that of Lagrangian relaxation (LR) method. Test results on the modified IEEE 118-bus system show the efficiency of our MIP formulation and advantages of the MIP method for solving PBUC. It is also shown that MIP could be applied to solve hydro-subproblems including cascaded-hydro and pumped-storage units in the LR-based framework of hydro-thermal coordination. Numerical experiments on large systems show that the MIP-based computation time and memory requirement would represent the major obstacles for applying MIP to large UC problems. It is noted that the solution of large UC problems could be accomplished by improving the MIP formulation, the utilization of specific structure of UC problems, and the use of parallel processing.

[1]  S. Stoft Power System Economics: Designing Markets for Electricity , 2002 .

[2]  S. Oren,et al.  Solving the Unit Commitment Problem by a Unit Decommitment Method , 2000 .

[3]  S. M. Shahidehpour,et al.  Unit commitment with transmission security and voltage constraints , 1999 .

[4]  M. Shahidehpour,et al.  Short-term scheduling of combined cycle units , 2004, IEEE Transactions on Power Systems.

[5]  Samer Takriti,et al.  Incorporating Fuel Constraints and Electricity Spot Prices into the Stochastic Unit Commitment Problem , 2000, Oper. Res..

[6]  Tao Li,et al.  Strategic bidding of transmission-constrained GENCOs with incomplete information , 2005, IEEE Transactions on Power Systems.

[7]  S. M. Shahidehpour,et al.  Optimal generation scheduling with ramping costs , 1993, Conference Proceedings Power Industry Computer Application Conference.

[8]  A. Semlyen,et al.  Short-Term Hydro-Thermal Dispatch Detailed Model and Solutions , 1989, IEEE Power Engineering Review.

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

[10]  S. M. Shahidehpour,et al.  Effects of ramp-rate limits on unit commitment and economic dispatch , 1993 .

[11]  M. Shahidehpour,et al.  Short-term scheduling of battery in a grid-connected PV/battery system , 2005, IEEE Transactions on Power Systems.

[12]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988 .

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

[14]  A.I. Cohen,et al.  Optimization-based methods for operations scheduling , 1987, Proceedings of the IEEE.

[15]  Peter B. Luh,et al.  An optimization-based algorithm for scheduling hydrothermal power systems with cascaded reservoirs and discrete hydro constraints , 1997 .

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

[17]  B. Hobbs,et al.  An oligopolistic power market model with tradable NO/sub x/ permits , 2005, IEEE Transactions on Power Systems.

[18]  Jacques F. Benders,et al.  Partitioning procedures for solving mixed-variables programming problems , 2005, Comput. Manag. Sci..

[19]  Peter B. Luh,et al.  Optimization-based scheduling of hydrothermal power systems with pumped-storage units , 1994 .

[20]  K. W. Edwin,et al.  Integer Programming Approach to the Problem of Optimal Unit Commitment with Probabilistic Reserve Determination , 1978, IEEE Transactions on Power Apparatus and Systems.

[21]  Yong Fu,et al.  Security-constrained unit commitment with AC constraints , 2005, IEEE Transactions on Power Systems.

[22]  B. Hobbs,et al.  Linear Complementarity Models of Nash-Cournot Competition in Bilateral and POOLCO Power Markets , 2001, IEEE Power Engineering Review.

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

[24]  Benjamin F. Hobbs,et al.  An Oligopolistic Power Market Model With Tradable NO x Permits , 2005 .

[25]  E. Allen,et al.  Price-Based Commitment Decisions in the Electricity Market , 1998 .

[26]  Philip G. Hill,et al.  Power generation , 1927, Journal of the A.I.E.E..

[27]  John D. C. Little,et al.  On model building , 1993 .

[28]  A. Renaud,et al.  Daily generation scheduling optimization with transmission constraints: a new class of algorithms , 1992 .

[29]  A. Papalexopoulos,et al.  Pricing energy and ancillary services in integrated market systems by an optimal power flow , 2004, IEEE Transactions on Power Systems.

[30]  F. N. Lee,et al.  Short-term thermal unit commitment-a new method , 1988 .

[31]  Jonathan F. Bard,et al.  Short-Term Scheduling of Thermal-Electric Generators Using Lagrangian Relaxation , 1988, Oper. Res..

[32]  John A. Muckstadt,et al.  An Application of Lagrangian Relaxation to Scheduling in Power-Generation Systems , 1977, Oper. Res..

[33]  J. Contreras,et al.  Price-Maker Self-Scheduling in a Pool-Based Electricity Market: A Mixed-Integer LP Approach , 2002, IEEE Power Engineering Review.

[34]  Arthur I. Cohen,et al.  A Branch-and-Bound Algorithm for Unit Commitment , 1983, IEEE Transactions on Power Apparatus and Systems.

[35]  M. Shahidehpour,et al.  Risk-constrained FTR bidding strategy in transmission markets , 2005, IEEE Transactions on Power Systems.

[36]  M. Shahidehpour,et al.  Unit commitment with flexible generating units , 2005, IEEE Transactions on Power Systems.

[37]  S. M. Shahidehpour,et al.  A practical resource scheduling with OPF constraints , 1995, Proceedings of Power Industry Computer Applications Conference.