DOI: https://doi.org/10.32515/2664-262X.2023.8(39).2.48-57
Determination of the optimal point of connection of the solar power plant to the electrical network by computer simulation
About the Authors
Petro Plieshkov, Professor, Doctor in Technics (Doctor of Technic Sciences), Central Ukrainian National Technical University, Kropivnitskiy, Ukraine, e-mail: plieshkov@gmail.com, ORCID ID: 0000-0003-2141-4811
Vasyl Zinzura, Associate Professor, PhD in Technics (Candidate of Technics Sciences), Central Ukrainian National Technical University, Kropivnitskiy, Ukraine, e-mail: vasiliyzinzura@gmail.com, ORCID ID: 0000-0001-6357-064X
Serhii Plieshkov, Associate Professor, PhD in Technics (Candidate of Technics Sciences), Central Ukrainian National Technical University, Kropivnitskiy, Ukraine, e-mail: sergploff@gmail.com, ORCID ID: 0000-0002-3120-5397
Valentyn Soldatenko, Associate Professor, PhD in Technics (Candidate of Technics Sciences), Central Ukrainian National Technical University, Kropivnitskiy, Ukraine, e-mail: kirovograd41@gmail.com, ORCID ID: 0000-0002-7781-9343
Abstract
The purpose of this study is to minimize the negative impact of the solar power plant on the value of the steady voltage deviation and the level of electricity losses by determining the optimal place for its connection to the distribution network.
Currently, quite a large number of methods of optimal placement of renewable sources of electricity in electrical networks have been developed. However, most of them either do not fully take into account the multifunctional influence of renewable energy sources on the parameters of the electric network regime, or are quite difficult to use. In order to solve the problem of optimal placement of renewable sources of electricity in electric networks, it is proposed to use the method of computer simulation modeling. The essence of this method is to determine the optimal place for connecting a renewable energy source to the electrical network based on the analysis of the results of computer simulation modeling of network mode parameters. This approach is the most acceptable in the case of connecting a solar power plant of average power to the electrical network of an industrial enterprise. The developed computer simulation model of a distribution electric network with a solar power plant allows for the research of network mode parameters, including the determination of the level of active power loss in network elements and the level of steady voltage deviation. The specified computer simulation models of the distribution electric network with a solar power plant made it possible to determine the optimal place for connecting the solar power plant based on the values of power losses in the elements of the electric network at the level of the established voltage deviation.
The results of computer modeling of an electrical network with a solar power plant confirmed the need to take into account not only the values of the established voltage deviation, but also the amount of electrical energy losses in the network elements in the process of choosing a place to install a solar power plant.
The results of the research can be used in solving the problems of determining the place of connection of a medium-power solar power plant to the electrical network of an industrial enterprise.
Keywords
solar power plant, computer modeling, distribution network
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References
1. Aderibigbe M., Adoghe A., Agbetuyi F., Airoboman A. (2021). A Review on Optimal Placement of Distributed Generators for Reliability Improvement on Distribution Network. IEEE PES/IAS PowerAfrica, Nairobi, Kenya, pp. 1-5. DOI: 10.1109/PowerAfrica52236.2021.9543266 [in English].
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4. Chen, M., Ma, S., Soltani, Z., Ayyanar, R., Vittal, V. & Khorsand M. (2023). Optimal Placement of PV Smart Inverters With Volt-VAr Control in Electric Distribution Systems. IEEE Systems Journal,. Vol. 17, No.3, P. 3436-3446. DOI: 10.1109/JSYST.2023.3256121 [in English].
5. Salam I.U., Yousif M., Numan M., Zeb K., Billah M. (2023) Optimizing Distributed Generation Placement and Sizing in Distribution Systems: A Multi-Objective Analysis of Power Losses, Reliability, and Operational Constraints. Energies, vol.16 (16), 5907; DOI: 10.3390/en16165907 [in English].
6. Plieshkov, P.H., Haras'ova, N.Yu. & Soldatenko, V.P. (2018). Optymal'ne keruvannia rezhymom roboty kombinovanoi elektroenerhetychnoi systemy z vidnovliuvanymy dzherelamy enerhii [Optimal Control of the Work of the Hybrid Electric Energy System With Renevable Sources of Energy]. Visnyk Natsional'noho tekhnichnoho universytetu «KhPI». Seriia: Problemy udoskonaliuvannia elektrychnykh mashyn i aparativ. Teoriia i praktyka - Bulletin of the National Technical University "KhPI". Collection of scientific works. Series: Problems of Improvement of Electric Machines and Apparatus, 32(1308), 64–70. DOI: 10.20998/2079-3944.2018.32 [in Ukrainian].
7. Plieshkov, P., Soldatenko, V., Zinzura, V. & Plieshkov S. (2020). Determining weight coefficients for an optimal system of control over electric energy generation in a combined electric power system. Eastern-European Journal of Enterprise Technologies, Vol. 103, No 1/2020, P. 77 – 82. DOI: https://doi.org/10.15587/1729-4061.2020.193362 [in English].
8. Power systems analysis software DIgSILENT PowerFactory. Retrieved from: http://www.digsilent.de/Software/DIgSILENT_PowerFactory/PFv14_Software.pdf.
9. Akintunde, A. et al. (2021). Power Quality Considerations for Distributed Generation Integration in the Nigerian Distribution Network Using NEPLAN Software. International Journal of Energy Economics and Policy, No. 11, P. 331-342. DOI:10.32479/ijeep.11145 [in English].
10. Perelmuter, V. (2020). Advanced Simulation of Alternative Energy (1st ed.). CRC Press. 314 p. DOI: https://doi.org/10.1201/9780429324055 [in English].
Citations
1. Aderibigbe M., Adoghe A., Agbetuyi F., Airoboman A. (2021). A Review on Optimal Placement of Distributed Generators for Reliability Improvement on Distribution Network. IEEE PES/IAS PowerAfrica, Nairobi, Kenya, pp. 1-5. DOI: 10.1109/PowerAfrica52236.2021.9543266.
2. Khasanov, M., Kamel, S., Jurado, F., Kurbanov, A., and Jalilov, U. (2023) Photovoltaic-based Distributed Generation Allocation in Distribution Network for Energy Loss Minimization. E3S Web of Conferences. Vol. 434. DOI:10.1051/e3sconf/202343401015
3. Kansal S., Kumar V., Tyagi B. Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks. International Journal of Electrical Power & Energy Systems. 2016. Vol. 75. Р. 226-235 DOI: https://doi.org/10.1016/j.ijepes.2015.09.002.
4. Chen M., Ma S., Soltani Z., Ayyanar R., Vittal V., Khorsand M. Optimal Placement of PV Smart Inverters With Volt-VAr Control in Electric Distribution Systems. IEEE Systems Journal. 2023. Vol. 17, No. 3. Р. 3436-3446. DOI: 10.1109/JSYST.2023.3256121.
5. Salam I.U., Yousif M., Numan M., Zeb K., Billah M. Optimizing Distributed Generation Placement and Sizing in Distribution Systems: A Multi-Objective Analysis of Power Losses, Reliability, and Operational Constraints. Energies. 2023. Vol.16 (16). Р. 5907. DOI: 10.3390/en16165907
6. Плєшков П.Г., Гарасьова Н.Ю., Солдатенко В.П. Оптимальне керування режимом роботи комбінованої електроенергетичної системи з відновлюваними джерелами енергії. Вісник Національного технічного університету «ХПІ». Серія: Проблеми удосконалювання електричних машин і апаратів. Теорія і практика. 2018. №32 (1308). С. 64-70.
7. Plieshkov P., Soldatenko V., Zinzura V., Plieshkov S. Determining weight coefficients for an optimal system of control over electric energy generation in a combined electric power system. Eastern-European Journal of Enterprise Technologies. 2020. Vol. 103, No 1/2020. P. 77 – 82. DOI: https://doi.org/10.15587/1729-4061.2020.193362.
8. Power systems analysis software DIgSILENT PowerFactory. – Режим доступу: http://www.digsilent.de/Software/DIgSILENT_PowerFactory/PFv14_Software.pdf.
9. Akintunde A., Owoicho O., Shomefun T., Olowoleni O., Ignatius O., Abdulkareem A. Power Quality Considerations for Distributed Generation Integration in the Nigerian Distribution Network Using NEPLAN Software. International Journal of Energy Economics and Policy. 2021. No. 11. Р. 331-342. DOI:10.32479/ijeep.11145
10. Perelmuter, V. Advanced Simulation of Alternative Energy (1st ed.). CRC Press. 2020. 314 p. DOI: https://doi.org/10.1201/9780429324055
Copyright (c) 2023 Petro Plieshkov, Vasyl Zinzura, Serhii Plieshkov, Valentyn Soldatenko
Determination of the optimal point of connection of the solar power plant to the electrical network by computer simulation
About the Authors
Petro Plieshkov, Professor, Doctor in Technics (Doctor of Technic Sciences), Central Ukrainian National Technical University, Kropivnitskiy, Ukraine, e-mail: plieshkov@gmail.com, ORCID ID: 0000-0003-2141-4811
Vasyl Zinzura, Associate Professor, PhD in Technics (Candidate of Technics Sciences), Central Ukrainian National Technical University, Kropivnitskiy, Ukraine, e-mail: vasiliyzinzura@gmail.com, ORCID ID: 0000-0001-6357-064X
Serhii Plieshkov, Associate Professor, PhD in Technics (Candidate of Technics Sciences), Central Ukrainian National Technical University, Kropivnitskiy, Ukraine, e-mail: sergploff@gmail.com, ORCID ID: 0000-0002-3120-5397
Valentyn Soldatenko, Associate Professor, PhD in Technics (Candidate of Technics Sciences), Central Ukrainian National Technical University, Kropivnitskiy, Ukraine, e-mail: kirovograd41@gmail.com, ORCID ID: 0000-0002-7781-9343
Abstract
Keywords
Full Text:
PDFReferences
1. Aderibigbe M., Adoghe A., Agbetuyi F., Airoboman A. (2021). A Review on Optimal Placement of Distributed Generators for Reliability Improvement on Distribution Network. IEEE PES/IAS PowerAfrica, Nairobi, Kenya, pp. 1-5. DOI: 10.1109/PowerAfrica52236.2021.9543266 [in English].
2. Khasanov, M., Kamel, S., Jurado, F., Kurbanov, A., and Jalilov, U. (2023) Photovoltaic-based Distributed Generation Allocation in Distribution Network for Energy Loss Minimization. E3S Web of Conferences, Vol. 434. DOI:10.1051/e3sconf/202343401015 [in English].
3. Kansal, S., Kumar, V. & Tyagi B. (2016). Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks. International Journal of Electrical Power & Energy Systems, Vol. 75, P. 226-235 DOI: https://doi.org/10.1016/j.ijepes.2015.09.002 [in English].
4. Chen, M., Ma, S., Soltani, Z., Ayyanar, R., Vittal, V. & Khorsand M. (2023). Optimal Placement of PV Smart Inverters With Volt-VAr Control in Electric Distribution Systems. IEEE Systems Journal,. Vol. 17, No.3, P. 3436-3446. DOI: 10.1109/JSYST.2023.3256121 [in English].
5. Salam I.U., Yousif M., Numan M., Zeb K., Billah M. (2023) Optimizing Distributed Generation Placement and Sizing in Distribution Systems: A Multi-Objective Analysis of Power Losses, Reliability, and Operational Constraints. Energies, vol.16 (16), 5907; DOI: 10.3390/en16165907 [in English].
6. Plieshkov, P.H., Haras'ova, N.Yu. & Soldatenko, V.P. (2018). Optymal'ne keruvannia rezhymom roboty kombinovanoi elektroenerhetychnoi systemy z vidnovliuvanymy dzherelamy enerhii [Optimal Control of the Work of the Hybrid Electric Energy System With Renevable Sources of Energy]. Visnyk Natsional'noho tekhnichnoho universytetu «KhPI». Seriia: Problemy udoskonaliuvannia elektrychnykh mashyn i aparativ. Teoriia i praktyka - Bulletin of the National Technical University "KhPI". Collection of scientific works. Series: Problems of Improvement of Electric Machines and Apparatus, 32(1308), 64–70. DOI: 10.20998/2079-3944.2018.32 [in Ukrainian].
7. Plieshkov, P., Soldatenko, V., Zinzura, V. & Plieshkov S. (2020). Determining weight coefficients for an optimal system of control over electric energy generation in a combined electric power system. Eastern-European Journal of Enterprise Technologies, Vol. 103, No 1/2020, P. 77 – 82. DOI: https://doi.org/10.15587/1729-4061.2020.193362 [in English].
8. Power systems analysis software DIgSILENT PowerFactory. Retrieved from: http://www.digsilent.de/Software/DIgSILENT_PowerFactory/PFv14_Software.pdf.
9. Akintunde, A. et al. (2021). Power Quality Considerations for Distributed Generation Integration in the Nigerian Distribution Network Using NEPLAN Software. International Journal of Energy Economics and Policy, No. 11, P. 331-342. DOI:10.32479/ijeep.11145 [in English].
10. Perelmuter, V. (2020). Advanced Simulation of Alternative Energy (1st ed.). CRC Press. 314 p. DOI: https://doi.org/10.1201/9780429324055 [in English].
Citations
1. Aderibigbe M., Adoghe A., Agbetuyi F., Airoboman A. (2021). A Review on Optimal Placement of Distributed Generators for Reliability Improvement on Distribution Network. IEEE PES/IAS PowerAfrica, Nairobi, Kenya, pp. 1-5. DOI: 10.1109/PowerAfrica52236.2021.9543266.
2. Khasanov, M., Kamel, S., Jurado, F., Kurbanov, A., and Jalilov, U. (2023) Photovoltaic-based Distributed Generation Allocation in Distribution Network for Energy Loss Minimization. E3S Web of Conferences. Vol. 434. DOI:10.1051/e3sconf/202343401015
3. Kansal S., Kumar V., Tyagi B. Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks. International Journal of Electrical Power & Energy Systems. 2016. Vol. 75. Р. 226-235 DOI: https://doi.org/10.1016/j.ijepes.2015.09.002.
4. Chen M., Ma S., Soltani Z., Ayyanar R., Vittal V., Khorsand M. Optimal Placement of PV Smart Inverters With Volt-VAr Control in Electric Distribution Systems. IEEE Systems Journal. 2023. Vol. 17, No. 3. Р. 3436-3446. DOI: 10.1109/JSYST.2023.3256121.
5. Salam I.U., Yousif M., Numan M., Zeb K., Billah M. Optimizing Distributed Generation Placement and Sizing in Distribution Systems: A Multi-Objective Analysis of Power Losses, Reliability, and Operational Constraints. Energies. 2023. Vol.16 (16). Р. 5907. DOI: 10.3390/en16165907
6. Плєшков П.Г., Гарасьова Н.Ю., Солдатенко В.П. Оптимальне керування режимом роботи комбінованої електроенергетичної системи з відновлюваними джерелами енергії. Вісник Національного технічного університету «ХПІ». Серія: Проблеми удосконалювання електричних машин і апаратів. Теорія і практика. 2018. №32 (1308). С. 64-70.
7. Plieshkov P., Soldatenko V., Zinzura V., Plieshkov S. Determining weight coefficients for an optimal system of control over electric energy generation in a combined electric power system. Eastern-European Journal of Enterprise Technologies. 2020. Vol. 103, No 1/2020. P. 77 – 82. DOI: https://doi.org/10.15587/1729-4061.2020.193362.
8. Power systems analysis software DIgSILENT PowerFactory. – Режим доступу: http://www.digsilent.de/Software/DIgSILENT_PowerFactory/PFv14_Software.pdf.
9. Akintunde A., Owoicho O., Shomefun T., Olowoleni O., Ignatius O., Abdulkareem A. Power Quality Considerations for Distributed Generation Integration in the Nigerian Distribution Network Using NEPLAN Software. International Journal of Energy Economics and Policy. 2021. No. 11. Р. 331-342. DOI:10.32479/ijeep.11145
10. Perelmuter, V. Advanced Simulation of Alternative Energy (1st ed.). CRC Press. 2020. 314 p. DOI: https://doi.org/10.1201/9780429324055