Jellyfish search optimizer algorithm based multiple distributed generation placements

Majlesi Journal of Electrical Engineering

دوره 18، شماره 3، آذر 2024، صفحه 1-13   

نوع مقاله: Reseach Article

شناسه دیجیتال (DOI): 10.57647/j.mjee.2024.180347

چکیده

The efficient and economical operation of a distribution power network (DPN) has been essential in recent times, considering the energy crisis and shortage of fossil fuels. A DPN is known to be efficient and economical if power losses are minimal, the voltage drop along the lines is less, and stability is maintained during different operating conditions. However, due to the crisis for primary fuel, all DPNs including radial power distribution networks (RPDN) are operated at threshold level. This has led to higher power losses, more voltage drops, and stability issues in RDPN. Hence, to reduce the power losses and voltage deviation and improve the stability of the power system network, distributed generation (DG) units are optimally allocated into radial DPN. In this study, an optimization technique using Jellyfish search optimizer (JSO) algorithm is proposed to optimize multiple DGs into RDPN to minimize a multi-objective function corresponds to real power loss (RPL) minimization, voltage stability (VS) enhancement, and total operating cost (TOC) minimization. The performance of the proposed technique is evaluated for multiple type I and type III DGs placement on an IEEE standard 33-bus RDPN. Besides, the effectiveness of the proposed technique is investigated considering a nominal and peak power demand. The efficacy of the research outcome of the suggested JSO approach has been compared with the outcome of
other optimization algorithms presented in the literature. The comparison exemplifies that JSO gives more promising outcomes than other algorithms by delivering the least real power losses and better voltage profile enhancement at minimum operating cost.

کلیدواژه‌ها

Radial distribution power network؛ Distributed generation؛ Power losses؛ Voltage stability؛ Total operating cost

مراجع

[1] S. H. Lee and J. J. Grainger. “Optimum placement of fixed and switched capacitors on primary distribution feeders.”. IEEE Trans. Power
Appl. Syst., 100(1):pp. 345–352, 1981. DOI:
https://doi.org/10.1109/TPAS.1981.316862.
[2] W. EI-hattam and M. M. A. Salma. “Distributed
generation technologies, definitions and benefits.”.
Electr. Power Syst. Res., 71(2):pp. 119–128, 2004.
DOI: https://doi.org/10.1016/j.epsr.2004.01.006.
[3] T. Ackermann, G. Andersson, and L. Soder.
“Distributed generation: a definition.”. Electr.
Power Syst. Res., 57:pp. 195–204, 2001. DOI:
https://doi.org/10.1016/S0378-7796(01)00101-8.
[4] Cigre. “Impact of increasing contribution of dispersed generation on the power system.”. CIGRE
study committee, (37), 1998.
[5] D. Q. Hung, N. Mithulananthan, and R. C. Bansal.
“Analytical expressions for dg allocation in primary distribution networks.”. IEEE Trans. Energy Convers, page pp. 814–820, 2010. DOI:
https://doi.org/10.1109/TEC.2010.2044414.
[6] D. K. Rajkumar Viral and A. Khatod. “Analytical
approach for sizing and siting of dgs in
balanced radial distribution networks for
loss minimization.”. Int. J. Electr. Power
Energy Syst., 67:pp. 191–201, 2015. DOI:
https://doi.org/10.1016/j.ijepes.2014.11.017.
[7] V. V. S. N. Murty and Ashwani Kumar. “Optimal
placement of dg in radial distribution systems based on new voltage stability index
under load growth.”. Int. J. Electr. Power
Energy Syst., 69:pp. 246–256, 2015. DOI:
https://doi.org/10.1016/j.ijepes.2014.12.080.
[8] M. H. Moradi and M. Abedini. “A combination of
genetic and particle swarm optimization for optimal dg location and sizing in distribution system.”. International Journal of Electrical Power
and Energy Systems, 34(1):pp. 66–74, 2012. DOI:
https://doi.org/10.1016/j.ijepes.2011.08.023.
[9] D. B. Prakash and C. Lakshminarayana. “Optimal
siting of capacitors in radial distribution network
using whale optimization algorithm.”. Alexandria Engg. J, 56:pp. 499–509, 2017. DOI:
https://doi.org/10.1016/j.aej.2016.10.002.
[10] D. B. Prakash and C. Lakshminarayana. “Multiple
dg placements in radial distribution system
for multi objectives using whale optimization algorithm.”. Alexandria Engineering
Journal, 57(4):pp. 2797–2806, 2018. DOI:
https://doi.org/10.1016/j.aej.2017.11.003.
[11] A. A. Saleh, A. A. A. Mohamed, and A. Hemeida.
“Optimal allocation of distributed generations and
capacitor using multi-objective different optimization techniques.”. in Proc. of the 2019 International
Conference on Innovative Trends in Computer Engineering (ITCE), page pp. 377–383, 2019. DOI:
https://doi.org/10.1109/ITCE.2019.8646426.
[12] U. Sultana, Azhhar B. Khairuddin, A. S.
Mokhtar, and N. Zareen. “Grey wolf optimizer based placement and sizing of multiple
distributed generation in the distribution system.”. Energy, 111:pp. 525–536, 2016. DOI:
https://doi.org/10.1016/j.energy.2016.05.128.
[13] Chandrasekhar Yammani, Sydulu Maheshwarapu,
and Sailaja Kumari Matam. “A multi-objective
shuffled bat algorithm for optimal placement
and sizing of multi distributed generations with
different load models.”. Int. J. Electr. Power
Energy Syst, 79:pp. 120–131, 2016. DOI:
https://doi.org/10.1016/j.ijepes.2016.01.003.
[14] Bikash Das, V. Mukherjee, and Debapriya Das.
“Dg placement in radial distribution network
by symbiotic organisms search algorithm
for real power loss minimization.”. Appl.
Soft Comput., 49:pp. 920–936, 2016. DOI:
https://doi.org/10.1016/j.asoc.2016.09.015.
[15] E. S. Ali, S. M. Abd-Elazim, and A. Y. Abdelaziz.
“Improved harmony algorithm and power loss index for optimal locations and sizing of capacitors in radial distribution systems.”. Int. J. Electr.
Power Energy Syst., 80:pp. 252–263, 2016. DOI:
https://doi.org/10.1016/j.ijepes.2015.11.085.
[16] A. Y. Abdelaziz, E. S. Ali, and S. M. Abd-Elazim.
“Flower pollination algorithm and loss sensitivity
factors for optimal sizing and placement of capacitors in radial distribution systems.”. Int. J. Electr.
Power Energy Syst., 78:pp. 207–214, 2016. DOI:
https://doi.org/10.1016/j.ijepes.2015.11.059.
[17] Injeti Sathish Kumar and N. Prema Kumar. “A novel
approach to identity optimal access point and capacity of multiple dgs in a small, medium, and
large scale radial distribution systems.”. Electr.
Power Energy Syst, 45:pp. 142–151, 2013. DOI:
https://doi.org/10.1016/j.ijepes.2012.08.043.
[18] A. M. Imran and M. Kowsalya. “Optimal size and
siting of multiple distributed generators in distribution system using bacterial foraging optimization.”. Swarm Evol. Comput., 15:pp. 58–65, 2014.
DOI: https://doi.org/10.1016/j.swevo.2013.12.001.
[19] B. Nasreddine, B. Fethi, H. Yassine, H. Imane,
and B. Riyadh. “Optimal sizing and placement
of distributed generation with short-circuit
analysis using a combined technique based on
modified pso and etap.”. 2024 2nd International
Conference on Electrical Engineering and Automatic Control (ICEEAC), pages pp. 1–6, 2024. DOI:
https://doi.org/10.1109/ICEEAC61226.2024.10576230.[20] S. Sultana and P. K. Roy. “Multi-objective
quasi oppositional teaching learning based optimization for optimal location of distributed
generator in radial distribution systems.”. International Journal of Electrical Power and Energy Systems, 63(1):pp. 534–545, 2014. DOI:
https://doi.org/10.1016/j.ijepes.2014.06.031.
[21] Usharani Raut and Sivkumar Mishra. “An
improved sine–cosine algorithm for simultaneous network reconfiguration and dg allocation in power distribution systems.”. Applied
Soft Computing, 92:pp. 106293, 2020. DOI:
https://doi.org/10.1016/j.asoc.2020.106293.
[22] S. Sultana and P. K. Roy. “Krill herd algorithm for optimal location of distributed generator in radial distribution system.”. Appl.
Soft Comput., 40:pp. 391–404, 2016. DOI:
https://doi.org/10.1016/j.asoc.2015.11.036.
[23] Hoshang Qasim Awla, Shahab Wahhab Kareem, and
Amin Salih Mohammed. “A comparative evaluation of bayesian networks structure learning
using falcon optimization algorithm.”. International Journal of Interactive Multimedia and Artificial Intelligence, 8(2):pp. 81–87, 2023. DOI:
https://doi.org/10.9781/ijimai.2023.01.004.
[24] Francisco Garc´ıa, Helena Hernandez, Mar ´ ´ıa N.
Moreno-Garc´ıa, Juan F. de Paz Santana, Vivian F.
Lopez, and Javier Bajo. “ ´ Traffic optimization
through waiting prediction and evolutive algorithms.”. International Journal of Interactive Multimedia and Artificial Intelligence, pages pp. 1–8, 2023.
DOI: https://doi.org/10.9781/ijimai.2023.12.001.
[25] J. S. Chou and D. N. Truong. “A novel
metaheuristic optimizer inspired by behavior
of jellyfish in ocean.”. Applied Mathematics
and Computation, 389:pp. 125535, 2021. DOI:
https://doi.org/10.1016/j.amc.2020.125535.
[26] M. Gandomkar, M. Vakilian, and M. Ehsan.
“A genetic-based tabu search algorithm for
optimal dg allocation in distribution networks.”. Electric Power Components and
Systems, 33(12):pp. 1351–1362, 2005. DOI:
https://doi.org/10.1080/15325000590964254.
[27] K. Prakash and M. Sydulu. “Particle swarm optimization based capacitor placement on radial distribution systems.”. IEEE Power Engineering Society General Meeting, pages pp. 1–5, 2007. DOI:
https://doi.org/10.1109/PES.2007.386149.
[28] P. Kayal P and C. Chanda. “Placement of wind and
solar based dgs in distribution system for power
loss minimization and voltage stability improvement.”. International Journal of Electrical Power
and Energy Systems, 53:pp. 795–809, 2013. DOI:
https://doi.org/10.1016/j.ijepes.2013.05.047.
[29] M. Khasanov, S. Kamel, C. Rahmann, and
H. M. Hasanien. “Optimal distributed generation and battery energy storage units integration in distribution systems considering
power generation uncertainty.”. IET Gener.
Transm. Distrib., 15:pp. 3400–3422, 2021. DOI:
https://doi.org/10.1049/gtd2.12230.
[30] N. C. Sahoo and K. Prasad. “A fuzzy genetic approach for network reconfiguration
to enhance voltage stability in radial distribution systems.”. Energy Conversion and
Management, 47:pp. 3288–3306, 2006. DOI:
https://doi.org/10.1016/j.enconman.2006.01.004.
[31] A. Augugliaro, L. Dusonchet, S. Favuzza, M. G. Ippolito, and E. Riva Sanseverino. “A backward sweep
method for power flow solution in distribution networks.”. International Journal of Electrical Power
& Energy Systems, 32(4):pp. 1540–1544, 2014. DOI:
https://doi.org/10.1016/j.ijepes.2009.09.007.