Symbiotic Organism Search Based on Sensitivity Factor for Optimal Location and Sizing of Distributed Generation
Abstract
The technology of Distributed Generations (DGs) has attracted the focus of researchers and engineers over the past two decades as an effective solution to address power quality and supply issues for customers. Determining the optimal locations and sizes for DGs remains a significant challenge. This study explores the optimization of DG placement and sizing to reduce power losses in radial distribution systems. The Loss Sensitivity Factor (LSF) is used to identify suitable locations for DGs, while Symbiotic Organisms Search (SOS) is utilized to determine their capacities. Simulation results using three DGs on the IEEE 33-bus distribution system indicate that this approach can reduce active power losses by 67.66%.
Keywords
Full Text:
PDFReferences
M. Delfanti, D. Falabretti, and M. Merlo, "Dispersed generation impact on distribution network losses," Electric Power Systems Research, vol. 97, pp. 10-18, 2013.
A.-M. Borbely and J. F. Kreider, Distributed generation: the power paradigm for the new millennium. CRC press, 2001.
O. Penangsang, "Simultaneously placement and sizing of multiple DGs and shunt capacitor banks in unbalanced distribution systems using real coded GA," in 2016 International Seminar on Intelligent Technology and Its Applications (ISITIA), 2016: IEEE, pp. 487-492.
A. Uniyal and A. Kumar, "Comparison of optimal DG allocation based on sensitivity based and optimization based approach," in 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), 2016: IEEE, pp. 1-6.
S. Kirmani, A. Kumar, and A. K. Pandey, "DG placements in distribution network using exhaustive search approach," in 2019 International Conference on Electrical, Electronics and Computer Engineering (UPCON), 2019: IEEE, pp. 1-6.
S. Sannigrahi and P. Acharjee, "A stability index based analytical technique for optimal placement of various DG types in distribution networks," in 2017 14th IEEE India Council International Conference (INDICON), 2017: IEEE, pp. 1-6.
A. Patwa, T. Thakur, and S. Gupta, "Voltage stability index based optimal sizing and placement of DG," in 2020 IEEE Students Conference on Engineering & Systems (SCES), 2020: IEEE, pp. 1-6.
A. Singhal and V. Ajjarapu, "Impact assessment and sensitivity analysis of distribution systems with dg," in 2015 North American Power Symposium (NAPS), 2015: IEEE, pp. 1-6.
G. Sakulphaisan, N. Junhuathon, and K. Chayakulkheeree, "Minimizing power loss in a DC distribution system through an analysis of the loss sensitivity factor and distributed generator loss characteristics," in 2022 International Electrical Engineering Congress (iEECON), 2022: IEEE, pp. 1-4.
U. Umar et al., "Single-phase distributed generations for power balanced using adaptive real coded genetic algorithm," International Journal of Applied, vol. 13, no. 1, pp. 11-19, 2024.
G. He et al., "Optimal Location and Sizing of Distributed Generator via Improved Multi-Objective Particle Swarm Optimization in Active Distribution Network Considering Multi-Resource," Energy Engineering, vol. 120, no. 9, 2023.
X. Shi, T. Liu, W. Mu, and J. Zhao, "Implementing an optimal energy management system for a set of microgrids using the harmony search algorithm," Energy Engineering, vol. 119, no. 5, pp. 1843-1860, 2022.
A. Lakum and V. Mahajan, "A novel approach for optimal placement and sizing of active power filters in radial distribution system with nonlinear distributed generation using adaptive grey wolf optimizer," Engineering Science and Technology, an International Journal, vol. 24, no. 4, pp. 911-924, 2021.
K. Subbaramaiah and P. Sujatha, "Optimal DG unit placement in distribution networks by multi-objective whale optimization algorithm & its techno-economic analysis," Electric Power Systems Research, vol. 214, p. 108869, 2023.
F. M. Behbahani, B. Ahmadi, and R. Caglar, "Multi-objective multiverse optimization for optimal allocation of distributed energy resources: The optimal parallel processing schemes," Electric Power Systems Research, vol. 231, p. 110298, 2024.
D. Q. Hung and N. Mithulananthan, "Multiple distributed generator placement in primary distribution networks for loss reduction," IEEE Transactions on industrial electronics, vol. 60, no. 4, pp. 1700-1708, 2011.
S. Kansal, V. Kumar, and B. Tyagi, "Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks," International Journal of Electrical Power & Energy Systems, vol. 75, pp. 226-235, 2016.
A. Priyadi, M. Pujiantara, and M. H. Purnomo, "A Hybrid Adaptively Modified Firefly and Differential Evolution in DG Integration Optimization for Improving the Radial Power Distribution Networks," International Journal of Intelligent Engineering & Systems, vol. 16, no. 5, 2023.
M.-Y. Cheng and D. Prayogo, "Symbiotic organisms search: a new metaheuristic optimization algorithm," Computers & Structures, vol. 139, pp. 98-112, 2014.
U. Umar, F. Faanzir, I. Iswan, M. Said, and H. Haryati, "Improved Symbiotic Organism Search (I-SOS) for global numerical optimization," Engineering and Applied Science Research, vol. 50, no. 5, pp. 499-505, 2023.
A. E. Ezugwu and D. Prayogo, "Symbiotic organisms search algorithm: theory, recent advances and applications," Expert systems with Applications, vol. 119, pp. 184-209, 2019.
DOI: https://doi.org/10.33387/ijeeic.v3i1.9716
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
| Journal Policies | Submissions | People | Â Information |
International Journal Of Electrical Engineering And Intelligent Computing
Departement of Electrical Engineering, Faculty of Engineering, Universitas Khairun,
Address: Yusuf Abdulrahman No. 53 (Gambesi) Ternate City - Indonesia
Email: ijeeic.unkhair@gmail.com
International Journal of Electrical Engineering and Intelligent Computing (IJEEIC), Universitas Khairun This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.