THERMAL SCIENCE

International Scientific Journal

Authors of this Paper

External Links

Pavle Dakić

,

Dimitrije Kotur

OPTIMAL PLACEMENT OF PHOTOVOLTAIC SYSTEMS FROM THE ASPECT OF MINIMAL POWER LOSSES IN DISTRIBUTION NETWORK BASED ON GENETIC ALGORITHM

ABSTRACT
In this paper, an optimal placement of photovoltaic systems as a source of active power in radial distribution network is considered. The objective of this optimization problem is minimizing system losses and improving voltage profiles based on optimal placement and sizing of photovoltaic systems. The maximal installed capacity of photovoltaic systems in distribution network is predefined and must not be exceeded. The simulation is done for three different cases from the aspect of input data (characteristic days for each month, Monte Carlo simulation, and whole year data). In this way, both consumption behavior and solar potential are considered in order to find optimal solution. Genetic algorithm is implemented for the calculation of optimal solution.
KEYWORDS
PV Systems, Optimal Placement and Sizing, Power Loss Reduction, Voltage Profile, genetic algorithm
PAPER SUBMITTED: 2017-05-28
PAPER REVISED: 2018-05-28
PAPER ACCEPTED: 2018-06-29
PUBLISHED ONLINE: 2018-09-22
DOI REFERENCE: https://doi.org/10.2298/TSCI170528223D
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2018, VOLUME 22, ISSUE Supplement 4, PAGES [S1157 - S1170]
REFERENCES
  1. T. Funabashi, Integration of Distributed Energy Resources in Power Systems: Implementation, Operation and Control, John Wiley & Sons, Academic Press, Elsevier, 2016, 1st edn
  2. B. K. Sahu, A study on global solar PV energy developments and policies with special focus on the top ten solar PV power producing countries, Renewable and Sustainable Energy Reviews, Volume 43, March 2015, pp. 621-634
  3. O. M. Toledo, D. O. Filho, A. S. A. C. Diniz, Distributed photovoltaic generation and energy storage systems: A review, Renewable and Sustainable Energy Reviews, Volume 14, January 2010, pp. 506-511
  4. A.Kadir, T.Khatib, W.Elmenreich, Integrating Photovoltaic Systems in Power System: Power Quality Impacts and Optimal Planning Challenges, Hindawi Publishing Corporation, International Journal of Photoenergy Volume 2014, Article ID 321826, August 2014.
  5. V. V. S. N. Murty, A. Kumar, Optimal placement of DG in radial distribution systems based on new voltage stability index under load growth, Volume 69, July 2015, pp. 246-256
  6. E. Karatepe, F. Ugranli, T. Hiyama, Comparison of single- and multiple-distributed generation concepts in terms of power loss, voltage profile, and line flows under uncertain scenarios, Renewable and Sustainable Energy Reviews, Volume 48, January 2015, pp. 317-327
  7. P. Karimyan, G. B. Gharehpetian, M. Abedi, A. Gavili, Long term scheduling for optimal allocation and sizing of DG unit considering load variations and DG type, International Journal of Electrical Power & Energy Systems, Volume 54, January 2014, pp. 277-287
  8. A. Zeinalzadeh, Y. Mohammadi, M. H. Moradi, Optimal multi objective placement and sizing of multiple DGs and shunt capacitor banks simultaneously considering load uncertainty via MOPSO approach, International Journal of Electrical Power & Energy Systems, Volume 67, May 2015, pp. 336-349
  9. M. M. Aman, G. B. Jasmon, A. H. A. Bakar, H. Mokhils, A new approach for optimum DG placement and sizing based on voltage stability maximization and minimization of power losses, Energy Conversion and Management, Volume 70, June 2013, pp. 202-210
  10. P. Dehghanian, S. H. Hosseini, M. Moeini-Aghataie, A. Arabali, Optimal siting of DG units in power systems from a probabilistic multi-objective optimization perspective, International Journal of Electrical Power & Energy Systems, Volume 51, Octobar 2013, pp. 14-26
  11. S. Kansal, V. Kumar, B. Tyagi, Optimal placement of different type of DG sources in distribution networks, International Journal of Electrical Power & Energy Systems, Volume 53, December 2013, pp. 752-760
  12. S. Kaur, G. Kumbhar, J. Sharma, A MINLP technique for optimal placement of multiple DG units in distribution systems, International Journal of Electrical Power & Energy Systems, Volume 63, December 2014, pp. 609-617
  13. A. J. G. Mena, J. A. Martin Garcia, An efficient approach for the siting and sizing problem of distributed generation (Article), International Journal of Electrical Power & Energy Systems, Volume 69, July 2015, pp. 167-172
  14. S. Abdi, K. Afshar, Application of IPSO-Monte Carlo for optimal distributed generation allocation and sizing, International Journal of Electrical Power & Energy Systems, Volume 44, Issue 1, January 2013, pp. 786-797
  15. C. L. T. Borges, An overview of reliability models and methods for distribution systems with renewable energy distributed generation, Renewable and Sustainable Energy Reviews, Volume 16, Issue 6, August 2012, pp. 4008-4015
  16. E. E. Sfikas, Y. A. Katsigannis, P. S. Geogrilakis, Simultaneous capacity optimization of distributed generation and storage in medium voltage microgrids, International Journal of Electrical Power & Energy Systems, Volume 67, May 2015, pp. 101-113.
  17. Z. Wang, B. Chen, J. Wang, J. Kim, M. M. Begovic, Robust Optimization Based Optimal DG Placement in Microgrids, IEEE Transactions on Smart Grid, Volume 5, Issue 5, September 2014, pp. 2173-2182
  18. S. Cheng, M-Y Chen, P. J. Flemming, Improved multi-objective particle swarm optimization for optimal DG integration into the distributed system, Neurocomputing, Volume 148, January 2015, pp. 23-29
  19. M. H. Moradi, M. Abedini, A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems, International Journal of Electrical Power & Energy Systems, Volume 34, January 2012, pp. 66-74.
  20. M. H. Moradi, M. Abedini, A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems with Fuzzy Optimal Theory, International Journal of Green Energy, Volume 9, February 2012, pp. 641-660.
  21. J. J. Jamian, M. W. Mustafa, H. Mokhlis, Optimal multiple distributed generation output through rank evolutionary particle swarm optimization, Neurocomputing, Volume 152, March 2015, pp. 190-198.
  22. R. S. Maciel, M. Rosa, V. Miranda, A. Padilha-Feltrin, Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation, Electric Power Systems Research, Volume 89, August 2012, pp. 100-108.
  23. Tan W. S., Hassan M. Y., Rahman H.A., Abdullah M. P., Hussin F., 'Multi-distributed generation planning using hybrid particle swarm optimization-gravitational search algorithm including voltage rise issue', IET Generation, Transmission & Distribution, 2013, 7, (9), pp 929-942
  24. M. Ahmadigorji, N. Amjady, A new evolutionary solution method for dynamic expansion planning of DG-integrated primary distribution networks, Energy Conversion and Management, Volume 82, June 2014, pp. 61-70
  25. Jordehi A. R., 'Allocation of distributed generation units in electric power systems: A review', Renewable and Sustainable Energy Reviews, 2016, 56, pp 893-905
  26. D.Shirmohammadi, H.W.Hong, A.Semlyen, G.X.Luo, A Compesation-Based Power Flow Method For Weakly Meshed Distribution And Transmision Networks, IEEE Transactions on Power Systems, Vol. 3, No. 2, May 1988
  27. HOLLAND H. J., Adaptation in Natural and Artificial Systems, an introductory analysis with application to biology, control and artificial intelligence, The university of Michigan Press, Ann Arbor, USA, 1975
  28. D.Popović, D.Bekut, V.Dabić, Special DMS algorithms, Novi Sad, 2004.(in Serbian)
  29. Rajaram R., Sathish Kumar K., Rajasekar N., 'Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG)', Energy Reports, 2015, 1, pp 116-122
PDF VERSION [DOWNLOAD]
Optimal placement of photovoltaic systems from the aspect of minimal power losses in distribution network based on genetic algorithm

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence