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Reactive Power Optimization

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Reactive Power Management of Power Networks with Wind Generation

Part of the book series: Lecture Notes in Energy ((LNEN,volume 5))

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Abstract

Every optimization problem employed to study electric power systems consists of an objective function and a group of constraints to be observed by this function that concurrently define the problem itself. The main constraints associated with the problem of reactive power planning are related to load flow equations. These problems are widely known as optimum load flow. Current operating conditions of reactive systems imply the necessity of redefining the reactive power planning problem, though bearing in mind its performance under normal conditions and faults or disturbances. The employment of these constraints by the planning of reactive power leads to a second optimization model known as optimum load flow with security constraints. Finally, more recent studies have raised the possibility of including voltage stability into the objective function, as well as into the problem constraints of reactive power planning, to maximize the voltage stability margin. Thus, a third optimization problem is derived, namely optimum load flow with security and voltage stability constraints. This optimization method aims to guarantee the existence of voltage stability margins in the system under faults and disturbances.

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References

  1. Pudjianto D, Ahmed S, Strbac G (2002) Allocation of var support using LP and NLP based optimal power flows. IEE Proceed Gener Trans Distrib 149(4):377–383

    Article  Google Scholar 

  2. Hsu CU, Yan YH, Chen CS, Her SR (1993) Optimal reactive power planning for distribution systems with nonlinear loads. In: TENCON ‘93. Proceedings. IEEE Region 10 conference on computer, communication, control and power engineering, Beijing, China, vol 5, pp 330–333, Oct 1993

    Google Scholar 

  3. Chen Y-L (1996) Weak bus oriented reactive power planning for system security. IEE Proceed Gener Trans Distrib 143(6):541–545

    Article  Google Scholar 

  4. Ajjarapu V, Ping Lin Lau S, Battula S (1994) An optimal reactive power planning strategy against voltage collapse. IEEE Trans Power Syst 9(2):906–917

    Article  Google Scholar 

  5. Chakrabarti BB, Chattopadhyay D, Krumble C (2001) Voltage stability constrained var planning-a case study for New Zealand. In: 2001 large engineering systems conference on power engineering. LESCOPE ‘01, Halifax, Canada, pp 86–91

    Google Scholar 

  6. Obadina OO, Berg GJ (1989) Var planning for power system security. IEEE Trans Power Syst 4(2):677–686

    Article  Google Scholar 

  7. Aoki K, Fan M, Nishikori A (1988) Optimal var planning by approximation method for recursive mixed-integer linear programming. IEEE Trans Power Syst 3(4):1741–1747

    Article  Google Scholar 

  8. Delfanti M, Granelli GP, Marannino P, Montagna M (2000) Optimal capacitor placement using deterministic and genetic algorithms. IEEE Trans Power Syst 15(3):1041–1046

    Article  Google Scholar 

  9. Degeneff RC, Neugebauer W, Saylor CH, Corey SL (1988) Security constrained optimization: an added dimension in utility systems optimal power flow. Comput Appl Power IEEE 1(4):26–30

    Article  Google Scholar 

  10. Gomez T, Perez-Arriaga IJ, Lumbreras J, Parra VM (1991) A security-constrained decomposition approach to optimal reactive power planning. IEEE Trans Power Syst 6(3):1069–1076

    Article  Google Scholar 

  11. Chattopadhyay D, Bhattacharya K, Parikh J (1995) Optimal reactive power planning and its spot-pricing: an integrated approach. IEEE Trans Power Syst 10(4):014–2020

    Google Scholar 

  12. Lee KY, Bai X, Park Y-M (1995) Optimization method for reactive power planning by using a modified simple genetic algorithm. IEEE Trans Power Syst 10(4):1843–1850

    Article  Google Scholar 

  13. Granville S, Pereira MVP, Monticelli A (1988) An integrated methodology for var sources planning. IEEE Trans Power Syst 3(2):549–557

    Article  Google Scholar 

  14. Zhu JZ, Chang CS, Yan W, Xu GY (1998) Reactive power optimisation using an analytic hierarchical process and a nonlinear optimisation neural network approach. IEE Proceed Gener Trans Distrib 145(1):89–97

    Article  Google Scholar 

  15. Chen YL, Ke YL (2004) Multi-objective var planning for large-scale power systems using projection-based two-layer simulated annealing algorithms. IEE Proc Gener Trans Distrib 151(4):555–560

    Article  Google Scholar 

  16. Jwo W-S, Liu C-W, Liu C-C, Hsiao Y-T (1995) Hybrid expert system and simulated annealing approach to optimal reactive power planning. IEE Proc Gener Trans Distrib 142(4):381–385

    Article  Google Scholar 

  17. Iba K (1993) Reactive power optimization by genetic algorithm. In: Conference proceedings on power industry computer application conference, Scottsdale, AZ, USA, pp 195–201, May 1993

    Google Scholar 

  18. Hsiao Y-T, Chiang H-D, Liu C-C, Chen Y-L (1994) A computer package for optimal multi-objective var planning in large scale power systems. IEEE Trans Power Syst 9(2):668–676

    Article  Google Scholar 

  19. Mantovani JRS, Garcia AV (1996) A heuristic method for reactive power planning. IEEE Trans Power Syst 11(1):68–74

    Article  Google Scholar 

  20. Thomas WR, Dixon AM, Cheng DTY, Dunnett RM, Schaff G, Thorp JD (1995) Optimal reactive planning with security constraints. In: 1995 I.E. conference proceedings on power industry computer application conference, Salt Lake City, UT, USA, pp 79–84, May 1995

    Google Scholar 

  21. Venkataramana A, Carr J, Ramshaw RS (1987) Optimal reactive power allocation. IEEE Trans Power Syst 2(1):138–144

    Article  Google Scholar 

  22. Kazempour SJ, Conejo AJ (2012) Strategic generation investment under uncertainty via benders decomposition. IEEE Trans Power Syst 27(1):424–432

    Article  Google Scholar 

  23. Kirkpatrick S, Gelatt C, Vecchi M (1983) Optimization by simulated annealing. Science 220(4598):498–516

    Article  MathSciNet  Google Scholar 

  24. Dreo J (2006) Metaheuristics for hard optimization: methods and case studies. Springer, Berlin

    MATH  Google Scholar 

  25. Hsiao Y-T, Liu C-C, Chiang H-D, Chen Y-L (1993) A new approach for optimal var sources planning in large scale electric power systems. IEEE Trans Power Syst 8(3):988–996

    Article  Google Scholar 

  26. Glover F (1986) Future paths for integer programming and links to artificial intelligence. Comp Operat Res 13(5):533–549

    Article  MathSciNet  MATH  Google Scholar 

  27. Zhang W, Liu Y, Liu Y (2002) Optimal var planning in area power system. In: International conference on power system technology. Proceedings. PowerCon 2002, Kunming, China, vol 4, pp 2072–2075

    Google Scholar 

  28. Lee KY, Yang FF (1998) Optimal reactive power planning using evolutionary algorithms: a comparative study for evolutionary programming, evolutionary strategy, genetic algorithm, and linear programming. IEEE Trans Power Syst 13(1):101–108

    Article  Google Scholar 

  29. Ajjarapu V, Albanna Z (1991) Application of genetic based algorithms to optimal capacitor placement. In: Proceedings of the first international forum on applications of neural networks to power systems, Seattle, WA, USA, pp 251–255, July 1991

    Google Scholar 

  30. Dong Z-Y, Hill DJ (2000) Power system reactive scheduling within electricity markets. In: 2000 international conference on advances in power system control, operation and management. APSCOM-00, Hong Kong, China, vol 1, pp 70–75, Oct–1 Nov 2000

    Google Scholar 

  31. Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Reading

    MATH  Google Scholar 

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Authors and Affiliations

  1. University Carlos III of Madrid, Av. Universidad, Madrid, Spain

    Hortensia Amaris, Monica Alonso & Carlos Alvarez Ortega

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  1. Hortensia Amaris
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  2. Monica Alonso
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  3. Carlos Alvarez Ortega
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Correspondence to Hortensia Amaris .

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Amaris, H., Alonso, M., Ortega, C.A. (2013). Reactive Power Optimization. In: Reactive Power Management of Power Networks with Wind Generation. Lecture Notes in Energy, vol 5. Springer, London. https://doi.org/10.1007/978-1-4471-4667-4_4

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  • DOI: https://doi.org/10.1007/978-1-4471-4667-4_4

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4666-7

  • Online ISBN: 978-1-4471-4667-4

  • eBook Packages: EnergyEnergy (R0)

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