Reliability Assessment of Distribution System Grid-Connected Multi-Inverter for Solar Photo-Voltaic Systems: A Case Study

doi:10.23940/ijpe.24.03.p3.149156

Abstract

Abstract: The contemporary electrical grid aims to deliver safe and reliable energy to consumers. As technology advances and distributed generation (DG) becomes more prevalent, the distribution system grows increasingly complex and decentralized. The swift integration of renewable energy sources, driven by concerns about global warming and carbon emissions, adds to this complexity. Given the direct link between the distribution system and consumer needs, reliability is paramount. However, the current distribution system faces operational issues, necessitating a dependable, resilient power system devoid of interruptions and glitches. Distributed generation (DG), along with its grid integration, holds promise in significantly enhancing the reliability of the existing distribution system. This research studied a case study of distribution system reliability evaluation using solar PV in the system. Various instances were addressed, and we found that after implementing DG, system dependability increased. For the case study and analysis, data were taken from a solar photo-voltaic energy source linked to the Kigali national grid in the Rwanda bus system. The Electrical Transient Analyzer Program (ETAP 19) software is utilized for modeling and reliability analysis.

Key words: distributed generation, energy resources, reliability assessment, Kigali national grid, ETAP

Darius Muyizere, Arcade Nshimiyimana, Theophile Mugerwa, Lawrence K. Letting, and Bernard B. Munyazikwiye. Reliability Assessment of Distribution System Grid-Connected Multi-Inverter for Solar Photo-Voltaic Systems: A Case Study [J]. Int J Performability Eng, 2024, 20(3): 149-156.

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

References

[1] Yan T., Tang W., Wang Y., andZhang X.Reliability Assessment of a Multi‐State Distribution System with Microgrids Based on an Accelerated Monte‐Carlo Method. IET Generation, Transmission & Distribution, vol. 12, no. 13, pp. 3221-3229, 2018.
[2] Adefarati, T. and Bansal, R.C. Application of Renewable Energy Resources in a Microgrid Power System. The Journal of Engineering, vol.2019, no. 18, pp. 5308-5313, 2019.
[3] Zhi-jian, L., Gui-hong, W., Dong-hui, Y., and Qi, S. Reliability Assessment of Distribution Network Considering the Randomness of Distributed Generation. In2016 China International Conference on Electricity Distribution (CICED), IEEE, pp. 1-6, 2016.
[4] Karki R., Billinton R., andVerma A.K. eds. Reliability modeling and analysis of smart power systems. Berlin: Springer, 2014.
[5] Cagnano A.,De Tuglie, E., and Mancarella, P. Microgrids: Overview and Guidelines for Practical Implementations and Operation. Applied Energy, vol. 258, pp. 114039, 2020.
[6] Lu W., Ren Z., Xu J., andChen S.Edge Blockchain Assisted Lightweight Privacy-Preserving Data Aggregation for Smart Grid. IEEE Transactions on Network and Service Management, vol. 18, no. 2, pp. 1246-1259, 2021.
[7] Ansari S., Chandel A., andTariq M.Enhanced Power Sharing of Droop Controlled Differently Rated Inverters in Standalone AC Microgrid. In2021 Fourth International Conference on Electrical, Computer and Communication Technologies (ICECCT), IEEE, pp. 1-6, 2021.
[8] Palati M., Prathap S.S., andNagaraju N.H.Modeling and Analysis of Smart Power System.Artificial Intelligence‐based Smart Power Systems, pp. 15-36, 2023.
[9] Alam M.N., Chakrabarti S., andGhosh A.Networked Microgrids: State-of-The-Art and Future Perspectives. IEEE Transactions on Industrial Informatics, vol. 15, no. 3, pp. 1238-1250, 2018.
[10] Ansari O.A., Safari N., andChung C.Y.Reliability Assessment of Microgrid with Renewable Generation and Prioritized Loads. In2016 IEEE Green Energy and Systems Conference (IGSEC), IEEE, pp. 1-6, 2016.
[11] Zhu, Y. and Singh, C.Topology-Aware Reliability Assessment by Graph Neural Networks. In2022 IEEE Kansas Power and Energy Conference (KPEC), IEEE, pp. 1-6, 2022.
[12] Karngala, A.K. and Singh, C.Reliability Assessment Framework for the Distribution System Including Distributed Energy Resources. IEEE Transactions on Sustainable Energy, vol. 12, no. 3, pp. 1539-1548, 2021.
[13] Maraaba L., Almuhaini M., Habli M., andKhalid M.Neural Networks Based Dynamic Load Modeling for Power System Reliability Assessment. Sustainability, vol. 15, no. 6, pp. 5403, 2023.
[14] Chandraratne C., Naayagi R.T., andLogenthiran T.Smart Grid Protection through Self-Healing. In2017 IEEE Innovative Smart Grid Technologies-Asia (ISGT-Asia), IEEE, pp. 1-6, 2017.
[15] Rwanda Energy Group, Annual Report for Rwanda Energy Group2020-2021, https://www.reg.rw/fileadmin/ REG_ANNUAL_REPORT_2020-2021_V3.pdf, access on February 1, 2024.
[16] Ahmed K.M.U., Alvarez, M., and Bollen, M.H. A Novel Reliability Index to Assess the Computational Resource Adequacy in Data Centers. IEEE Access, vol. 9, pp. 54530-54541, 2021.
[17] He M., Liu Y., Liu H., andGu D.A Novel High Step-Up/Step-Down Transformer-Less Bidirectional DC-DC Converter for Energy Storage Systems. In2021 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia), IEEE, pp. 1409-1414, 2021.
[18] TAŞIN, A. and ÇAVUŞ, T.F. Reliability Analysis of Sakarya Area Electricity Distribution System. Sakarya University Journal of Science, vol. 26, no. 2, pp. 292-299, 2022.
[19] Huda A.S.N. and Živanović, R. Distribution System Reliability Assessment using Sequential Multilevel Monte Carlo Method. In2016 IEEE Innovative Smart Grid Technologies-Asia (ISGT-Asia), IEEE, pp. 867-872, 2016.
[20] Mamo, A. and Hizkiel, A.Reliability Assessment and Enhancement of Dangila Distribution System with Distribution Generation. Cogent Engineering, vol. 10, no. 1, pp. 2191375, 2023.
[21] Saeed M.H., Fangzong W., Kalwar B.A., andIqbal S.A Review on Microgrids’ Challenges & Perspectives. IEEE Access, vol. 9, pp. 166502-166517, 2021.
[22] Aderibigbe M.A., Adoghe A.U., Agbetuyi F., andAiroboman A.E.A Review on Optimal Placement of Distributed Generators for Reliability Improvement on Distribution Network.2021 IEEE PES/IAS PowerAfrica, pp. 1-5, 2021.
[23] Muyizere D., Letting L.K., andMunyazikwiye B.B.Decreasing the Negative Impact of Time Delays on Electricity Due to Performance Improvement in the Rwanda National Grid. Electronics, vol. 11, no. 19, pp. 3114, 2022.
[24] Mansoury I.,El Bourakadi, D., Yahyaouy, A., and Boumhidi, J. A Novel Decision-Making Approach Based on a Decision Tree for Micro-Grid Energy Management. Indonesian Journal of Electrical Engineering and Computer Science, vol. 30, no. 2, pp. 1150-1158, 2023.