| |
 |
Optimization of
Recloser Placement in DG-Enhanced Distribution Networks Using
a Multi-objective Optimization Approach
Fabian Lopez and Andrés
Pantoja
2017/04/25
|

Abstrac
Efficient placement of protective devices
in electric power distribution networks is necessary in order to achieve
a reliable system and provide continuous power supply to customers as
long as possible. The islanded operation with distributed generation (DG)
provides a way to reduce the energy not supplied (ENS) but the placement
of protections, such as reclosers, is necessary in order to allow the
system to achieve this mode of operation. This paper presents a multi-objective
optimization method to place efficiently normally closed reclosers by
using a constrained non-dominated sorting genetic algorithm (C-NSGA-II)
to reduce SAIDI, ENS and investment costs. A co-simulation approach is
used in such a way that the power system is modelled in PowerFactory,
while MATLAB is used to implement the C-NSGA-II. Then, a distribution
test network is probed in simulation cases with different DG penetration
levels, showing the efficiency of the proposed optimization method. Results
show the importance of protective devices and DG in enhancing system reliability
and reducing the energy not supplied to customers.
| Published in: Renewable Energy
& Power Quality Journal (RE&PQJ, Nº. 15) |
| Pages: 316-321 |
Date of Publication: 2017/04/25 |
| ISSN: 2172-038X |
Date of Current Version: |
| REF: 306-17 |
Issue Date: April 2017 |
| DOI:10.24084/repqj15.306 |
Publisher: EA4EPQ |
Authors and affiliations
Fabian Lopez and Andrés Pantoja
Department of Electronics. Universidad de Nariño, Pasto, Colombia
Key word
Co-simulation, distributed generation, distribution systems
reliability, multi-objective optimization, protective systems.
References
[1] M. Brenna, F. Foiadelli, P. Petroni, G. Sapienza,
and D. Zaninelli. Distributed generation regulation for intentional islanding
in smart grids. In 2012 IEEE PES Innovative Smart Grid Technologies (ISGT),
pp 16, 2012.
[2] L. G. W. da Silva, R. A. F. Pereira, J. R. Abbad, and J. R. S. Mantovani.
Optimised placement of control and protective devices in electric distribution
systems through reactive tabu search algorithm. Electric Power Systems
Research, Vol. 78, No.3, pp.372381, 2008.
[3] M. Hajivand, R. Karimi, M. Karimi, et al. Optimal recloser placement
by binary differential evolutionary algorithm to improve reliability of
distribution system. International Journal of Information, Security and
SystemsManagement, Vol. 3, No. 2, pp.345349, 2014.
[4] A. Pregelj, M. Begovic, and A. Rohatgi. Recloser allocation for improved
reliability of dg-enhanced distribution networks. IEEE Transactions on
Power Systems, Vol. 21, No. 3, pp.14421449, 2006.
[5] R. E. Brown. Electric power distribution reliability. CRC press, 2008.
[6] K. Deb. Multi-objective optimization using evolutionary algorithms,
volume 16. John Wiley & Sons, 2001.
[7] G. D. Ferreira, A. S. Bretas, and G. Cardoso. Optimal distribution
protection design considering momentary and sustained reliability indices.
In Modern Electric Power Systems (MEPS), 2010 Proceedings of the International
Symposium, pages 18. IEEE, 2010
[8] M. R. Mazidi, M. Aghazadeh, Y. A. Teshnizi, and E. Mohagheghi. Optimal
placement of switching devices in distribution networks using multi-objective
genetic algorithm nsgaii. In 2013 21st Iranian Conference on Electrical
Engineering (ICEE), pages 16. IEEE, 2013.
[9] W. Tippachon and D. Rerkpreedapong. Multiobjective optimal placement
of switches and protective devices in electric power distribution systems
using ant colony optimization. Electric Power Systems Research, Vol. 79,
No. 7, pp.11711178, 2009.
[10] J.-H. Teng and Y.-H. Liu. A novel acs-based optimum switch relocation
method. IEEE transactions on power systems, Vol. 18, No. 1, pp.113120,
2003.
[11] K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan. A fast and elitist
multiobjective genetic algorithm: Nsga-ii. IEEE transactions on evolutionary
computation, Vol. 6, No. 2, pp.182197, 2002.
[12] A. Stativ¢a, M. Gavrilas¸, and V. Stahie. Optimal tuning
and placement of power system stabilizer using particle swarm optimization
algorithm. In Electrical and Power Engineering (EPE), 2012 International
Conference and Exposition on, pages 242247. IEEE, 2012.
[13] C. A. C. Coello. Recent trends in evolutionary multiobjective optimization.
In Evolutionary Multiobjective Optimization, pages 732. Springer,
2005.
[14] IEEE Std. 1547-2003, IEEE Standard for interconnecting Distributed
resources with electric power systems, 2003.
[15] R. Billinton and S. Jonnavithula. A test system for teaching overall
power system reliability assessment. IEEE Transactions on Power Systems,
Vol. 11, No. 4, pp.16701676, 1996.
[16] R. N. Allan, R. Billinton, I. Sjarief, L. Goel, and K. So. A reliability
test system for educational purposes-basic distribution system data and
results. IEEE Transactions on Power Systems, Vol. 6, No. 2, pp.813820,
1991.

|
|