Artificial Bee Colony Algorithm to Generator Maintenance Scheduling in Competitive Market

paper proposes an Artificial Bee Colony (ABC) algorithm to Generator Maintenance Scheduling (GMS) in competitive market. In the regulated market the problem of generating optimal maintenance schedules of generating units for the purpose of maximizing economic benefits and improving reliable operation of a power system, subject to satisfying system constraints. In case of deregulated market, the self-governing generation company GENCO prepares GMS aims to maximize their revenue with less consideration on reliability. The Independent System Operator (ISO) receives the maintenance schedules from GENCO and compares with ISO schedules for sanction. This paper proposes an ABC algorithm to solve the GMS in GENCO to maximize their revenue without considering expected renewal cost. Numerical examples on 4 and 32 unit power producers are utilized to demonstrate the effectiveness of the proposed ABC algorithm.

[1]  Salih O. Duffuaa,et al.  A Tabu search algorithm for maintenance scheduling of generating units , 2000 .

[2]  H. M. Merrill,et al.  Power plant maintenance scheduling: optimizing economics and reliability , 1991 .

[3]  Roy Billinton,et al.  Short-term generating unit maintenance scheduling in a deregulated power system using a probabilistic approach , 2003 .

[4]  Bilal Alatas,et al.  Chaotic bee colony algorithms for global numerical optimization , 2010, Expert Syst. Appl..

[5]  S. M. Shahidehpour,et al.  Long-term transmission and generation maintenance scheduling with network, fuel and emission constraints , 1999 .

[6]  Marco Furini,et al.  International Journal of Computer and Applications , 2010 .

[7]  Siba K. Udgata,et al.  Artificial bee colony algorithm for small signal model parameter extraction of MESFET , 2010, Eng. Appl. Artif. Intell..

[8]  Jong-Bae Park,et al.  A new game-theoretic framework for maintenance strategy analysis , 2003 .

[9]  R. Eshraghnia,et al.  Generation Maintenance Scheduling in Power Market Based on Genetic Algorithm , 2006, 2006 IEEE PES Power Systems Conference and Exposition.

[10]  X. Wang,et al.  Modern power system planning , 1994 .

[11]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[12]  Dantong Ouyang,et al.  An artificial bee colony approach for clustering , 2010, Expert Syst. Appl..

[13]  Ganesh K. Venayagamoorthy,et al.  Optimal generator maintenance scheduling using a modified discrete PSO , 2008 .

[14]  Marjorie V. Batey,et al.  AUTHORS. IN PROFILE , 1969 .

[15]  K. Bhattacharya,et al.  Security Coordinated Maintenance Scheduling in Deregulation Based on Genco Contribution to Unserved Energy , 2008, IEEE Transactions on Power Systems.

[16]  R. Billinton,et al.  Composite system maintenance coordination in a deregulated environment , 2005, IEEE Transactions on Power Systems.

[17]  Xifan Wang,et al.  A Competitive Mechanism of Unit Maintenance Scheduling in a Deregulated Environment , 2010, IEEE Transactions on Power Systems.

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

[19]  Fushuan Wen,et al.  Unit maintenance scheduling coordination mechanism in electricity market environment , 2008 .

[20]  M. Shahidehpour,et al.  GENCO's Risk-Based Maintenance Outage Scheduling , 2008, IEEE Transactions on Power Systems.

[21]  Furong Li,et al.  Optimal maintenance scheduling of power producers considering unexpected unit failure , 2009 .

[22]  E. Handschin,et al.  A new genetic algorithm for preventive unit maintenance scheduling of power systems , 2000 .

[23]  Koichi Nara,et al.  Maintenance scheduling by using simulated annealing method (for power plants) , 1991 .

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