Reactive Power Market Simulation: A Particle Swarm Optimization Approach

سال انتشار: 1384
نوع سند: مقاله کنفرانسی
زبان: فارسی
مشاهده: 1,224

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شناسه ملی سند علمی:

PSC20_176

تاریخ نمایه سازی: 8 آذر 1385

چکیده مقاله:

This paper deals with the application of Particle Swarm Optimization algorithm (PSO) for reactive power scheduling in deregulated power system. Reactive power procurement is modeled as a security constraint optimal power flow incorporating voltage stability problem. The model attempts to minimize cost of reactive power procurement and energy losses as a main objective while technical criteria and voltage stability margin, in special, are treated as soft constraints. From mathematical points of view, reactive power market can be expressed as a nonlinear optimization problem. Thus PSO, as a powerful heuristic algorithm, is implemented to find equilibrium point of the reactive power market. Reactive power market is simulated over the IEEE30 bus system and obtained results are compared with another evolutionary programming such as genetic algorithm (GA) in terms of quantity and precision. Results show that the PSO has a good potential to converge to better feasible solution in less iteration and it can be successfully used for reactive power optimization in restructured environments.

نویسندگان

Mozafari

Dept. of Electrical Engineering, Sharif University of Technology, Tehran, Iran و Niroo Research Institute, Tehran, Iran

Amraee

Dept. of Electrical Engineering, Sharif University of Technology, Tehran, Iran و Niroo Research Institute, Tehran, Iran

Ranjbar

Dept. of Electrical Engineering, Sharif University of Technology, Tehran, Iran و Niroo Research Institute, Tehran, Iran

Sadati

Dept. of Electrical Engineering, Sharif University of Technology, Tehran, Iran

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  • Power System Test Case Archive, available: V VXJ VX eه ...
  • . M. Shahidehpour, and M. Alomoush, ، «Re structured Electric ...
  • . Eric.Hirst, and Brendan Kirby, *Creating Competitive Market for Ancillary ...
  • . Kai Xie, etal, ، 'Decomp osition Model and Interior ...
  • . Y. Dai, Y. X. Ni, F. S. Wen, and ...
  • . M. J. Rider, and V. L. Pacuar, *Application of ...
  • . John. W. Lamont, and Jidn Fu, 44Cost analysis of ...
  • . D. Pudjianto, S. Ahmed, and G. Strbac, ، Allocation ...
  • Proceeding of the IEEE Congress on Evolutionary Computation (CEC 1998), ...
  • . R. C. Eberhart, and, Y. Shi 40 Particle Swarm ...
  • . J. Kennedt, and, R. Mendes, ، Neighborho ods Topologies ...
  • +hilitv t؟ _ [17]. P. Kundur, ،Pover %nd Contronl . ...
  • . C. A. Caizares, W. Rosehart, A. Berizzi, and C. ...
  • W. Rosehart, C. Caizares, and V. Quintana, *Optimal Power Flow ...
  • M. Gen and R. Cheng, 4Genetic A1 oorithm< _ Fn ...
  • Using LP and NLP based Optimal Power Flows, * stems: ...
  • . R. C. Bansal, T. S. Bhatti, and D. P. ...
  • . J. Kennedy and R. Eberhart, ،، Particle SWarm optimization, ...
  • . J. B. Park, K. S. Lee, J. R. Shin, ...
  • . Zew-Lee Gaing, " Particle Swarm Optimization to Solving the ...
  • . H. Yoshida, etal, ، A Particle Swarm Optimization for ...
  • . Hsiao Dong Chiang etal, "CPFLOW: A Practical Tool for ...
  • . Y. Shi, and R. C. Eberhart, A modified particle ...
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