Multi-DGPV Planning Using Artificial Intelligence
Keywords:
Optimization, Loss minimization, Distributed generation, Evolutionary programming, Distributed generation photovoltaic, Backward forward sweep, Total voltage deviationAbstract
This article investigates the impact of multi-Distributed Generation Photovoltaic (DGPV) installation and their degree of penetration on controlling power loss in the radial distribution system. The Integrated Immune Moth Flame Evolution Programming (IIMFEP), a unique hybrid optimization technique, was utilized to identify the ideal DGPV size and location for base case conditions and under load variations. The IIMFEP approach is compared against Evolutionary Programming (EP), Artificial Immune System (AIS), and Moth Flame Optimization (MFO) and validated using the IEEE 118-Bus Radial Distribution Systems (RDS). Incorporating multi-DGPV into a system reduces the total real and reactive power loss while simultaneously increasing the minimum voltage and decreasing the total voltage deviation. In every instance examined in this study, the IIMFEP method yields optimal solutions superior to those generated by the other three methods. As the number of DGPV units increased to nine, the percentage of power loss reduction became the highest among all DG units examined, and DG penetration reached 94.26 percent. This research provides the power system operator with comprehensive findings demonstrating the impact of installing multi-DGPV in distribution networks on system loss.
Downloads
References
S. K. Dash, S. Mishra, A. Y. Abdelaziz, M. L. Alghaythi, and A. Allehyani, “Optimal Allocation of Distributed Generators in Active Distribution Networks Using a New Oppositional Hybrid Sine Cosine Muted Differential Evolution Algorithm,” Energies (Basel), vol. 15, no. 6, Mar. 2022, doi: 10.3390/en15062267.
M. Ntombela, K. Musasa, and M. C. Leoaneka, “Power Loss Minimization and Voltage Profile Improvement by System Reconfiguration, DG Sizing, and Placement,” Computation, vol. 10, no. 10, p. 180, Oct. 2022, doi: 10.3390/computation10100180.
L. C. Kien, T. T. Bich Nga, T. M. Phan, and T. T. Nguyen, “Coot Optimization Algorithm for Optimal Placement of Photovoltaic Generators in Distribution Systems Considering Variation of Load and Solar Radiation,” Math Probl Eng, vol. 2022, 2022, doi: 10.1155/2022/2206570.
G. Tahiliani and A. R. Gupta, “Voltage Profile improvement by optimal DG allocation using atom search optimisation in radial and mesh distribution system,” International Journal of Engineering, Science and Technology, vol. 14, no. 3, pp. 112–121, Aug. 2022, doi: 10.4314/ijest.v14i3.13s.
J. M. Home-Ortiz, M. Pourakbari-Kasmaei, M. Lehtonen, and J. R. Sanches Mantovani, “Optimal location-allocation of storage devices and renewable-based DG in distribution systems,” Electric Power Systems Research, vol. 172, pp. 11–21, Jul. 2019, doi: 10.1016/j.epsr.2019.02.013.
P. Prakash, D. C. Meena, H. Malik, M. A. Alotaibi, and I. A. Khan, “A Novel Analytical Approach for Optimal Integration of Renewable Energy Sources in Distribution Systems,” Energies (Basel), vol. 15, no. 4, Feb. 2022, doi: 10.3390/en15041341.
N. R. Godha Dagade, V. N. Bapat, and I. Korachagaon, “Improved ACO for Planning and Performance Analysis of Multiple Distributed Generations in Distribution System for Various Load Models,” in 2020 2nd International Sustainability and Resilience Conference: Technology and Innovation in Building Designs, Nov. 2020. doi: 10.1109/IEEECONF51154.2020.9319962.
M. J. Afzal, A. Arshad, S. Ahmed, S. bin Tariq, and S. A. A. Kazmi, “A review of DGs and FACTS in power distribution network: Methodologies and objectives,” in 2018 International Conference on Computing, Mathematics and Engineering Technologies: Invent, Innovate and Integrate for Socioeconomic Development, iCoMET 2018 - Proceedings, Apr. 2018, vol. 2018-January, pp. 1–7. doi: 10.1109/ICOMET.2018.8346405.
M. Pesaran H.A, P. D. Huy, and V. K. Ramachandaramurthy, “A review of the optimal allocation of distributed generation: Objectives, constraints, methods, and algorithms,” Renewable and Sustainable Energy Reviews, vol. 75. Elsevier Ltd, pp. 293–312, 2017. doi: 10.1016/j.rser.2016.10.071.
W. L. Theo, J. S. Lim, W. S. Ho, H. Hashim, and C. T. Lee, “Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods,” Renewable and Sustainable Energy Reviews, vol. 67. Elsevier Ltd, pp. 531–573, Jan. 01, 2017. doi: 10.1016/j.rser.2016.09.063.
R. O. Bawazir and N. S. Cetin, “Comprehensive overview of optimizing PV-DG allocation in power system and solar energy resource potential assessments,” Energy Reports, vol. 6. Elsevier Ltd, pp. 173–208, Nov. 01, 2020. doi: 10.1016/j.egyr.2019.12.010.
P. V. K. Babu and K. Swarnasri, “Optimal integration of different types of DGs in radial distribution system by using Harris hawk optimization algorithm,” Cogent Eng, vol. 7, no. 1, Jan. 2020, doi: 10.1080/23311916.2020.1823156.
Z. B. A. Hamid, S. Jipinus, I. Musirin, M. M. Othman, and R. H. Salimin, “Optimal sizing of distributed generation using firefly algorithm and loss sensitivity for voltage stability improvement,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 17, no. 2, pp. 720–727, 2019, doi: 10.11591/ijeecs.v17.i2.pp720-727.
A. Eid, S. Kamel, and L. Abualigah, “Marine predators algorithm for optimal allocation of active and reactive power resources in distribution networks,” Neural Comput Appl, 2021, doi: 10.1007/s00521-021-06078-4.
S. A. Shaaya, I. Musirin, S. I. Sulaiman, M. H. Mansor, and S. A. S. Mustaffa, “Effect of DG types and penetration level in transmission system using hybrid optimization technique for loss control,” International Journal of Emerging Trends in Engineering Research, vol. 8, no. 1 Special Issue 1, pp. 1–6, 2020, doi: 10.30534/ijeter/2020/0181.12020.
R. Sanjay Kumar and N. Anbuselvan, “Power Factor Improvement of Wind based DGs in the Distribution System Using (Fruit Fly and Cat Swarm) Optimization Techniques by Reducing the Harmonics,” 2021.
E. A. Al-Ammar et al., “ABC algorithm based optimal sizing and placement of DGs in distribution networks considering multiple objectives,” Ain Shams Engineering Journal, vol. 12, no. 1, pp. 697–708, Mar. 2021, doi: 10.1016/j.asej.2020.05.002.
S. A. S. Mustaffa, I. Musirin, M. M. Othman, M. K. M. Zamani, and A. Kalam, “Chaotic local search based algorithm for optimal DGPV allocation,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 11, no. 1, pp. 113–120, Jul. 2018, doi: 10.11591/ijeecs.v11.i1.pp113-120.
T. L. Duong, P. T. Nguyen, N. D. Vo, and M. P. Le, “A newly effective method to maximize power loss reduction in distribution networks with highly penetrated distributed generations,” Ain Shams Engineering Journal, vol. 12, no. 2, pp. 1787–1808, Jun. 2021, doi: 10.1016/j.asej.2020.11.003.
S. Kawambwa, R. Mwifunyi, D. Mnyanghwalo, N. Hamisi, E. Kalinga, and N. Mvungi, “An improved backward/forward sweep power flow method based on network tree depth for radial distribution systems,” Journal of Electrical Systems and Information Technology, vol. 8, no. 1, Dec. 2021, doi: 10.1186/s43067-021-00031-0.
D. Issicaba and J. Coelho, “Evaluation of the forward-backward sweep load flow method using the contraction mapping principle,” International Journal of Electrical and Computer Engineering, vol. 6, no. 6, pp. 3229–3237, 2016, doi: 10.11591/ijece.v6i6.11303.
C. S. M. anoj Gupta, “Review of Forward & Backward Sweep Method for Load Flow Analysis of Radial Distribution System,” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol. 04, no. 06, pp. 5595–5599, Jun. 2015, doi: 10.15662/ijareeie.2015.0406049.
B. M’hamdi, M. Teguar, and B. Tahar, “Optimal DG unit placement and sizing in radial distribution network for power loss minimization and voltage stability enhancement,” Periodica polytechnica Electrical engineering and computer science, vol. 64, no. 2, pp. 157–169, Apr. 2020, doi: 10.3311/PPEE.15057.
S. Kumar, K. Krishna Mandal, M. Ghosh, S. Kumar, S. Mandal, and K. Mandal, “Optimal Sizing and Placement of DG Units in Radial Distribution System Using Cuckoo Search Algorithm.” [Online]. Available: http://www.ripublication.com
T. Yuvaraj and K. Ravi, “Multi-objective simultaneous DG and DSTATCOM allocation in radial distribution networks using cuckoo searching algorithm,” Alexandria Engineering Journal, vol. 57, no. 4, pp. 2729–2742, Dec. 2018, doi: 10.1016/j.aej.2018.01.001.
T. Yuvaraj, K. Ravi, and K. R. Devabalaji, “Optimal Allocation of DG and DSTATCOM in Radial Distribution System Using Cuckoo Search Optimization Algorithm,” Modelling and Simulation in Engineering, vol. 2017, 2017, doi: 10.1155/2017/2857926.
D. Zhang, Z. Fu, and L. Zhang, “An improved TS algorithm for loss-minimum reconfiguration in large-scale distribution systems,” Electric Power Systems Research, vol. 77, no. 5–6, pp. 685–694, Apr. 2007, doi: 10.1016/j.epsr.2006.06.005.
H. R. E H Bouchekara, “Comprehensive Review of Radial Distribution Test Systems Optimal Coordination of Directional Overcurrent Relays View project Design of Hybrid Nanogrid in the Desert Camps of Hafr Al-Batin City View project”, doi: 10.36227/techrxiv.12578648.v1.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Azlina Abdullah, Ismail Musirin, Muhammad Murtadha Othman, Siti Rafidah Abdul Rahim, A.V. Sentilkumar
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
