Analysis of Loss Allocation in Radial Distribution Systems Incorporating Distributed Generation

Authors

  • Shaik Rafiuddin Department of Electrical and Electronics Engineering, Kakatiya Institute of Technology and Science (Autonomous), Warangal – 506 015, Telangana, India Author
  • G. Ugender Department of Electrical and Electronics Engineering, Kakatiya Institute of Technology and Science (Autonomous), Warangal – 506 015, Telangana, India Author
  • V. Siddartha Department of Electrical and Electronics Engineering, Kakatiya Institute of Technology and Science (Autonomous), Warangal – 506 015, Telangana, India Author
  • P. Raviteja Department of Electrical and Electronics Engineering, Kakatiya Institute of Technology and Science (Autonomous), Warangal – 506 015, Telangana, India Author
  • G. Sudheer Kumar Department of Electrical and Electronics Engineering, Kakatiya Institute of Technology and Science (Autonomous), Warangal – 506 015, Telangana, India Author

DOI:

https://doi.org/10.32628/IJSRST2512139

Keywords:

loss allocation, distribution generation, transmission system, distribution system

Abstract

This explores Distribution Loss Allocation for Radial Systems Including Distributed Generators (DGs), focusing on the application and comparison of four different loss allocation methods: Pro Rata, Marginal, Z-bus, and branch current decomposition method (BCDM). The primary objective is to calculate and allocate transmission losses among generators and consumers in a radial distribution network, particularly in the presence of DGs. The Pro Rata method, although simple, allocates losses proportionally but lacks precision in complex systems. The Marginal method improves allocation by considering the marginal cost of losses, offering more equitable results. The impedance-bus (Z-bus) method, using network impedance, provides a detailed approach to account for the topology and placement of generators, making it well-suited for systems with DGs. The BCDM method compensates for flow deviations and is effective in systems where power flows are influenced by network constraints and DGs. The results highlight that while the Pro Rata method is suitable for simpler systems, more advanced methods like Marginal, Z-bus, and BCDM offer more accurate and fair loss allocations, ensuring a more equitable distribution of transmission losses in modern power systems with distributed generation.

Downloads

Download data is not yet available.

References

Kamel S, Abdel-Mawgoud H, Hashim FA, Bouaouda A, Dominiquez-Garcia JL (2024) Achieving optimal PV allocation in distribution networks using a modified reptile search algorithm. IEEE Access 12:42651–42666. DOI: https://doi.org/10.1109/ACCESS.2024.3376629

Prasad H, Subbaramaiah K, Sujatha P (2023) Optimal DG unit placement in distribution networks by multi-objective whale opti- mization algorithm & its techno-economic analysis. Elect Power Syst Res 214:108869. DOI: https://doi.org/10.1016/j.epsr.2022.108869

Sellami R, Sher F, Neji R (2022) An improved MOPSO algorithm for optimal sizing & placement of distributed generation: a case study of the Tunisian offshore distribution network (ASHTART). Energy Rep 8:6960–6975 DOI: https://doi.org/10.1016/j.egyr.2022.05.049

Kholaif MMNHK, Xiao M, Tang X (2022) Covid-19′s fear- uncertainty effect on renewable energy supply chain management and ecological sustainability performance; the moderate effect of big-data analytics. Sustain Energy Technol Assess 53:102622. DOI: https://doi.org/10.1016/j.seta.2022.102622

Pamponet MC, Maranduba HL, de Almeida Neto JA, Rodrigues LB (2021) Energy balance and carbon footprint of the very large-scale photovoltaic power plant. Int J Energy Res 46(5):6901–6918. DOI: https://doi.org/10.1002/er.7529

Bhowmik C, Bhowmik S, Ray A (2022) Green energy sources selection for sustainable planning: a case study. IEEE Trans Eng Manage 69(4):1322–1334. DOI: https://doi.org/10.1109/TEM.2020.2983095

Gumas TE, Emiroglu S, M. a. Yalcim, (2023) Optimal DG allo- cation and sizing in distribution systems with Thevenin based impedance stability index. Int J Elect Power & Energy Syst 144:108555. https://doi.org/10.1016/j.ijepes.2022.108555.

Adepoju GA, Aderemi BA, Salimon SA, Alabi OJ (2023) Optimal placement and sizing of distributed generation for power loss mini- mization in distribution network using particle swarm optimization technique. Eur J Eng Technol Res 8(1):19–25. DOI: https://doi.org/10.24018/ejeng.2023.8.1.2886

Gumus TL, Emiroglu S, Yalcin MA (2023) Optimal DG allocation and sizing in distribution systems with Thevenin-based impedance stability index. Int J Electr Power Energy Syst 144:108555. DOI: https://doi.org/10.1016/j.ijepes.2022.108555

Tang W, Huang K, Zhang Y, Qian T (2023) Optimal allocation of photovoltaic generations in buildings-to-distribution-network inte- gration systems using improved backtracking search optimization algorithm. IET Gener Transm Distrib 17(18):4086–4106. DOI: https://doi.org/10.1049/gtd2.12966

Arunjothi R, Meena KP (2024) Optimizing capacitor size and placement in radial distribution networks for maximum efficiency. Syst Soft Comput 6:200111. DOI: https://doi.org/10.1016/j.sasc.2024.200111

Saeed MAEM, Abdel-Gwaad AF, Farahat MA (2023) Solving the capacitor placement problem in radial distribution networks. Result Eng 17:100870. DOI: https://doi.org/10.1016/j.rineng.2022.100870

G. Naguraiah and K. Jithendra Goud, “Power Flow Method for Loss Allocation in Radial Distribution Networks with DGs”, IRJET Syst., vol. 2, no. 2, pp. 2395-0072 , September 2015.

Z. Ghofrani-Jahromi, Z. Mahmoodzadeh and M. Ehsan, "Distribution Loss Allocation for Radial Systems Including DGs," in IEEE Transactions on Power Delivery, vol. 29, no. 1, pp. 72-80, Feb. 2014, doi: 10.1109/TPWRD.2013.2277717. DOI: https://doi.org/10.1109/TPWRD.2013.2277717

Downloads

Published

03-02-2025

Issue

Section

Research Articles

How to Cite

Analysis of Loss Allocation in Radial Distribution Systems Incorporating Distributed Generation. (2025). International Journal of Scientific Research in Science and Technology, 12(1), 395-403. https://doi.org/10.32628/IJSRST2512139

Similar Articles

1-10 of 182

You may also start an advanced similarity search for this article.