Hierarchical Multiobjective Optimization for Independent System Operators (ISOs) in Electricity Markets

The creation of competitive electricity markets has increased the complexity of the economics of system operation. Independent system operators (ISOs) perform optimizations based on a market-driven objective function. However, there may be other objectives that the ISO wishes to consider. These objectives are called secondary objectives, as they are dominated by the economic objective. In this paper, a hierarchical multiobjective (HMO) optimization is developed that, through coordinated control of network devices such as phase shifting transformers and series flexible ac transmission systems (FACTS), allows the market objective to be optimized in a global sense, while the secondary objectives are locally optimized. The method is applied to a modified IEEE 30-bus system incorporating a wide-area impact index-minimizing secondary objective. Formulated in this paper, the wide-area impact index accurately measures the effects of parallel flow over multiple lines in a region. Comparisons are made between the HMO's performance with other single and multiple objective optimizations and between the wide-area impact index and traditional parallel flow calculations

[1]  C. S. Chang,et al.  Security-constrained multiobjective generation dispatch using bicriterion global optimisation , 1995 .

[2]  D. B. Das,et al.  New multi-objective stochastic search technique for economic load dispatch , 1998 .

[3]  Ferial El-Hawary,et al.  A summary of environmental/economic dispatch algorithms , 1994 .

[4]  Thomas J. Overbye,et al.  Extended factors for linear contingency analysis , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[5]  Wang Peng,et al.  Research on multi-objective optimum model of unit maintenance scheduling under the condition of electricity market , 2004, 2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies. Proceedings.

[6]  Hirotaka Nakayama,et al.  Theory of Multiobjective Optimization , 1985 .

[7]  A. Ott,et al.  Experience with PJM market operation, system design, and implementation , 2003 .

[8]  Goran Andersson,et al.  Power flow control by use of controllable series components , 1993 .

[9]  M. Abido.  Environmental/economic power dispatch using multiobjective evolutionary algorithms , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[10]  David G. Luenberger,et al.  Linear and Nonlinear Programming: Second Edition , 2003 .

[11]  G. T. Heydt,et al.  Power flow control and power flow studies for systems with FACTS devices , 1998 .

[12]  I. Wangensteen,et al.  Transmission management in the deregulated environment , 2000, Proceedings of the IEEE.

[13]  Z. X. Han.  Phase Shifter and Power Flow Control , 1982, IEEE Power Engineering Review.

[14]  Yang Song,et al.  Series FACTS devices in financial transmission rights auction for congestion management , 2001 .

[15]  B. M. Pasternack,et al.  OPERATING PROBLEMS WITH PARALLEL FLOWS , 1991 .

[16]  Ralph E. Steuer.  Multiple criteria optimization , 1986 .

[17]  H. Sasaki,et al.  Multiobjective optimal generation dispatch based on probability security criteria , 1988 .

[18]  Glauco N. Taranto,et al.  Representation of FACTS devices in power system economic dispatch , 1992 .

[19]  B. R. Serrano,et al.  Active-reactive power economic dispatch of very short term in competitive electric markets , 2001, 2001 IEEE Porto Power Tech Proceedings (Cat. No.01EX502).

[20]  Gary W. Chang,et al.  Power System Analysis , 1994 .

[21]  Y. Z. Sun,et al.  Power Flow Control Approach to Power Systems with Embedded Facts Devices , 2002, IEEE Power Engineering Review.

[22]  R. Baldick,et al.  Dispatchable transmission in RTO markets , 2005, IEEE Transactions on Power Systems.

[23]  Laszlo Gyugyi,et al.  Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems , 1999 .