Skip to main content

Advertisement

SpringerLink
Log in

Multi-objective optimization of passive filters in industrial power systems

  • Original Paper
  • Published:
Electrical Engineering Aims and scope Submit manuscript

Abstract

The formulations employed to the optimization of passive filters can be classified as formulations of a single objective or formulations with multiple objectives. The single-objective formulations normally are devoted to determine the filters of lowest cost that assure the compliance with the power quality standards, while in the multi-objective approaches are added other goals that are related with the improvement of the power quality indexes. In the presented approach, the problem of the reactive power compensation and the problem of the harmonic distortion compensation are considered a unified multi-objective problem in which is determined a set of passive filters that allows the obtaining of the maximum economic benefits as well as the maximum improvement of the power quality of the circuit. While several previous contributions solve the multi-objective problem by minimizing a single function composed of several sub-objectives, this work employs the non-dominated sorting genetic algorithm (NSGA-II) for the optimization of three independent objective functions. This algorithm obtains the Pareto front of the problem and allows the selection of the most effective solutions. The optimization method that presented in this work allows the selection by the algorithm of the filter type proper for compensation in a node of the circuit as well as the obtaining of their parameters. The set of possible filter configurations to place in one candidate node is defined by the user before the optimization is done. This is a distinctive characteristic of the presented approach that is tested with a practical example.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Ghiasi M, Rashtchi V, Hoseini H (2008) Optimum location and sizing of passive filters in distribution networks using genetic algorithm. In: International conference on emerging technologies IEEE-ICET 2008, Rawalpindi, Pakistan, 18–19 Oct 2008

  2. Ruihua Z, Yuhong L, Yaohua L (2008) Optimal parameters for filter using improved genetic algorithms. IEEE Chinese Academy of Sciences, Beijing

    Google Scholar 

  3. Luiz ASA, Filho BJC (2008) Minimum reactive power filter design for high power converters. In: 13th international power electronics and motion control conference, EPE-PEMC 2008

  4. Chang GW, Wang H-L, Chuang G-S, Chu S-Y (2009) Passive harmonic filter planning in a power system with considering probabilistic constraints. IEEE Trans Power Deliv 24(1):208–218

    Article  Google Scholar 

  5. Hong Y-Y, Chiu C-S (2010) Passive filter planning using simultaneous perturbation stochastic approximation. IEEE Trans on Power Deliv 25(2):939–946

    Article  Google Scholar 

  6. Zobaa AF, Vaccaro A, Zeineldin HH, Lecci A, Abdel Monem AM (2010) Sizing of passive filters in time-varying non sinusoidal environments. In: Proceedings of 14th international conference on harmonics and quality of power-ICHQP 2010, IEEE, pp 1–8

  7. Badrzadeh B, Smith KS, Wilson RC (2011) Designing passive harmonic filters for an aluminum smelting plant. IEEE Trans Ind Appl 47(2):973–983

    Article  Google Scholar 

  8. Kovernikova LI, Thanh NC (2012) An optimization approach to calculation of passive filter parameters based on particle swarm optimization. In: International conference on renewable energies and power quality (ICREPQ’12) Spain, 28–30 Mar 2012

  9. Abdel ASHE, Zobaa AF, Aziz MMA (2012) Optimal C-type passive filter based on minimization of the voltage harmonic distortion for nonlinear loads. IEEE Trans Ind Electron 59(1):281–289

    Article  Google Scholar 

  10. Pandi VR, Zeineldin HH, Xiao W (2012) Passive harmonic filter planning to overcome power quality issues in radial distribution systems. In: 2012 IEEE power and energy society general meeting, IEEE, pp 1–6

  11. Ertay MM, Tosun S, Zengin A (2012) Simulated annealing based passive power filter design for a medium voltage power system. In: 2012 international symposium on innovations in intelligent systems and applications (INISTA), IEEE, pp 1–5

  12. Stone PEC, Wang J, Shin Y-J, Dougal RA (2012) Efficient harmonic filter allocation in an industrial distribution system. IEEE Trans Ind Electron 59(2):740–751

    Article  Google Scholar 

  13. Ali HAM, Zobaa AF, El-Zahab EEA (2012) Single-tuned passive harmonic filters design with uncertain source and load characteristics. Recent Pat Electr Eng 5:72–80

    Article  Google Scholar 

  14. Abdel ASHE, Elmathana MT, Zobaa AF (2002) Different design approaches of shunt passive harmonic filters based on IEEE Std. 519–1992 and IEEE Std. 18–2002. Recent Pat Electr Electron Eng 6:68–75

    Google Scholar 

  15. Balci ME, Sakar S (2014) Optimal design of single-tuned passive filters to minimize harmonic loss factor. Middle-East J Sci Res 21(11):2149–2155

    Google Scholar 

  16. Na H, Lina H, Jian W, Dianguo X (2008) Study on optimal design method for passive power filters set at high voltage bus considering many practical aspects. In: Twenty-Third annual IEEE applied power electronics conference and exposition, APEC 2008, IEEE, pp 396–401

  17. Na H, Dianguo X, Lina H (2009) The application of particle swarm optimization to passive and hybrid active power filter design. IEEE Trans Ind Electron 56(8):2841–2851

    Article  Google Scholar 

  18. Ko C-N, Chang Y-P, Wu C-J (2009) A PSO method with nonlinear time-varying evolution for optimal design of harmonic filters. IEEE Trans Power Syst 24(1):437–444

    Article  Google Scholar 

  19. Sharaf AM, El-Gammal AAA (2008) A discrete particle swarm optimization technique (DPSO) for power filter design. In: Proceedings of the IEEE international conference on electrical and power engineering (EPE)

  20. Sharaf AM, El-Gammal AAA (2009) A novel discrete multi-objective particle swarm optimization (MOPSO) of optimal shunt power filter. In: Proceedings of the power systems conference and exposition, Seattle, Washington, USA, PSCE 2009

  21. Maza-Ortega JM, Burgos-Payán M (2010) A software-based tool for optimal design of passive tuned filters. In: Proceedings of the IEEE international symposium on industrial electronic, Bari/Italy, pp 3273–3278

  22. Churio-Barboza JC, Maza-Ortega JM, Burgos-Payán M (2011) Optimal design of passive tuned filters for time varying non-linear loads. In: Proceedings of the 2011 international conference on power engineering, energy and electrical drives, Spain, May 2011

  23. Verma V, Singh B (2010) Genetic-algorithm-based design of passive filters for offshore applications. IEEE Trans Ind Appl 46(4):1295–1303

    Article  Google Scholar 

  24. Dehini R, Sefiane S (2011) Power quality and cost improvement by passive power filters synthesis using ant colony algorithm. J Theor Appl Inf Technol 23(2):70–79

    Google Scholar 

  25. Singh S, Singh B (2010) Passive filter design for a 12-pulse converter fed LCI-synchronous motor drive. In: Power electronics, drives and energy systems (PEDES) & 2010 power India, 2010 joint international conference on IEEE, pp 1–8

  26. Yue H, Li G, Zhou M, Wang K, Wang J (2014) Multi-objective optimal power filter planning in distribution network based on fast nondominated sorting genetic algorithms. In: 2011 4th international conference on electric utility deregulation and restructuring and power technologies (DRPT), IEEE, pp 234–240

  27. Li S, Li Y, Luo X, Zeng L, He Z (2012) Multi-objective optimal design for passive power filters in hybrid power filter system based on multi-island particle swarm optimization. In: IEEE 7th international power electronics and motion control conference—ECCE Asia June 2–5, 2012, Harbin, China

  28. Ji J, Liu H, Zeng G, Zhang J (2012) The multi-objective optimization design of passive power filter based on PSO. In: 2012 Asia-Pacific power and energy engineering conference, IEEE, pp 1–4

  29. Carpinelli G, Ferruzzi G, Russo A (2012) A heuristic multi-objective approach with trade off/risk analysis issues for passive harmonic filters planning I. Problem formulation and solution algorithm. In: 8th Mediterranean conference on power generation, transmission, distribution and energy conversion, MEDPOWER 2012

  30. Carpinelli G, Ferruzzi G, Russo A (2012) A heuristic multi-objective approach with trade off/risk analysis issues for passive harmonic filters planning II. Case Study. In: 8th Mediterranean conference on power generation, transmission, distribution and energy conversion, MEDPOWER 2012

  31. Yang C-F, Lai GG, Su C-T (2013) Optimal planning of passive harmonic filters using hybrid differential evolution considering variation of system parameters. Int Trans Electr Energy Syst 23(8):1317–1334

    Article  Google Scholar 

  32. Kawann C, Emanuel AE (1996) Passive shunt harmonic filters for low and medium voltage: a cost comparison study. IEEE Trans Power Syst 11(4):1825–1831

    Article  Google Scholar 

  33. IEEE recommended practices and requirements for harmonic control in electrical power systems (2014) IEEE standard 519–2014 (Revision of IEEE Std 519–1992), IEEE, New York

  34. IEEE standard for shunt power capacitors (2012) IEEE standard 18-2012 (Revision of IEEE Std 519-1992), IEEE New York

  35. Seshadri A (2012) NSGA-II source code. http://www.mathworks.com/matlabcentral/fileexchange/10429-nsga-ii-a-multi-objective-optimization-algorithm/content/NSGA-II/

Download references

Acknowledgments

The authors acknowledge the Institute of Technology Galileo of Amazon (ITEGAM), the Amazonas Research Foundation (FAPEAM) and the Universidad Central “Marta Abreu” de las Villas for their support for performing this work.

Author information

Authors and Affiliations

  1. Institute of Technology and Education Galileo of Amazonia (ITEGAM), Praça Francisco Pereira da Silva, 149, Manaus, Brazil

    Jandecy Cabral Leite

  2. Universidad Central “Marta Abreu” de Las Villas. Centro de Estudios Electroenergéticos, Carretera de Camajuaní km 5, Santa Clara, Villa Clara, Cuba

    Ignacio Pérez Abril

  3. ITEC-UFPA Institute of Technology, Universidade Federal do Pará, Av. Augusto Corrêa, 01, Guamá, Belém, Amazonas, Brazil

    Maria Emilia de Lima Tostes & Roberto Celio Limão de Oliveira

Authors
  1. Jandecy Cabral Leite
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ignacio Pérez Abril
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Maria Emilia de Lima Tostes
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Roberto Celio Limão de Oliveira
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jandecy Cabral Leite.

Appendix

Appendix

The example system’s source has 250 MVA of short circuit power with an X/R ratio of 10. The maximum load current to calculate the TDD is \(\mathrm{IL} = 30\) A at the 69 kV side.

The data of the transformers and feeders of the circuit are given in Table 5.

Table 5 Transformers and feeders
Full size table
Table 6 The loads and the harmonics spectrum of the non-linear loads
Full size table
Table 7 Cost data
Full size table

The data of the linear loads, the non-linear loads and their harmonics spectrum are given in Table 6.

The cost data are given in Table 7.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Leite, J.C., Abril, I.P., Tostes, M.E.d.L. et al. Multi-objective optimization of passive filters in industrial power systems. Electr Eng 99, 387–395 (2017). https://doi.org/10.1007/s00202-016-0420-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00202-016-0420-3

Keywords

Search

Navigation