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Two-Step Approach for Improving the Distribution Network Voltage Profile Using the Optimal Integration of the PV-BES System
1
Faculty of Electronic Engineering, University of Niš, 18104 Niš, Serbia
Corresponding Author:
Nikola Krstić,
[email protected]
Volume 2, Issue 1
2026
Received: 26 February 2026
Accepted: 19 March 2026
Published: 22 March 2026
Article Information
Volume/Issue
Volume 2, Issue 1, 2026
Pages
31-46
Abstract
This paper proposes the two-step approach for improving the voltage profile of the distribution network (DN) using the optimal integration of photovoltaic-battery energy storage (PV-BES) system. In the first step of the approach the optimal location of the PV-BES system in the DN and its optimal powers are determined, considering the topology and the load of the DN. This is done to improve the voltage profile of the DN using the meta-heuristic wild horse optimization method (WHO) and genetic algorithm (GA). The second step of the approach determines the optimal sizing of the PV-BES system, by taking into account the optimal powers obtained in the first step, the solar irradiance diagram and the average temperature for each month of the year for the area in which the DN is located. The optimal sizing includes optimal maximum power of the PV system and the optimal maximum power and energy capacity of the BES unit, determined by the proposed iterative method. The results are generated using the topology of the IEEE 18-bus radial DN for three different load diagrams, on a monthly and annual basis.
Graphical Abstract
Keywords
distribution network (DN)
genetic algorithm (GA)
photovoltaic-battery energy storage (PV-BES) system
voltage profile
wild horse optimization (WHO)
Data Availability Statement
Data will be made available on request.
Funding
This work was supported by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia under Grant 451-03-34/2026-03/200102.
Conflicts of Interest
The authors declare no conflicts of interest.
AI Use Statement
The authors declare that no generative AI was used in the preparation of this manuscript.
Ethical Approval and Consent to Participate
Not applicable.
References
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APA Style
Krstić, N., & Tasić, D. (2026). Two-Step Approach for Improving the Distribution Network Voltage Profile Using the Optimal Integration of the PV-BES System. ICCK Transactions on Electric Power Networks and Systems, 2(1), 31–46. https://doi.org/10.62762/TEPNS.2026.581037
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TY - JOUR AU - Krstić, Nikola AU - Tasić, Dragan PY - 2026 DA - 2026/03/22 TI - Two-Step Approach for Improving the Distribution Network Voltage Profile Using the Optimal Integration of the PV-BES System JO - ICCK Transactions on Electric Power Networks and Systems T2 - ICCK Transactions on Electric Power Networks and Systems JF - ICCK Transactions on Electric Power Networks and Systems VL - 2 IS - 1 SP - 31 EP - 46 DO - 10.62762/TEPNS.2026.581037 UR - https://www.icck.org/article/abs/TEPNS.2026.581037 KW - distribution network (DN) KW - genetic algorithm (GA) KW - photovoltaic-battery energy storage (PV-BES) system KW - voltage profile KW - wild horse optimization (WHO) AB - This paper proposes the two-step approach for improving the voltage profile of the distribution network (DN) using the optimal integration of photovoltaic-battery energy storage (PV-BES) system. In the first step of the approach the optimal location of the PV-BES system in the DN and its optimal powers are determined, considering the topology and the load of the DN. This is done to improve the voltage profile of the DN using the meta-heuristic wild horse optimization method (WHO) and genetic algorithm (GA). The second step of the approach determines the optimal sizing of the PV-BES system, by taking into account the optimal powers obtained in the first step, the solar irradiance diagram and the average temperature for each month of the year for the area in which the DN is located. The optimal sizing includes optimal maximum power of the PV system and the optimal maximum power and energy capacity of the BES unit, determined by the proposed iterative method. The results are generated using the topology of the IEEE 18-bus radial DN for three different load diagrams, on a monthly and annual basis. SN - 3070-2607 PB - Institute of Central Computation and Knowledge LA - English ER -
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@article{Krsti2026TwoStep,
author = {Nikola Krstić and Dragan Tasić},
title = {Two-Step Approach for Improving the Distribution Network Voltage Profile Using the Optimal Integration of the PV-BES System},
journal = {ICCK Transactions on Electric Power Networks and Systems},
year = {2026},
volume = {2},
number = {1},
pages = {31-46},
doi = {10.62762/TEPNS.2026.581037},
url = {https://www.icck.org/article/abs/TEPNS.2026.581037},
abstract = {This paper proposes the two-step approach for improving the voltage profile of the distribution network (DN) using the optimal integration of photovoltaic-battery energy storage (PV-BES) system. In the first step of the approach the optimal location of the PV-BES system in the DN and its optimal powers are determined, considering the topology and the load of the DN. This is done to improve the voltage profile of the DN using the meta-heuristic wild horse optimization method (WHO) and genetic algorithm (GA). The second step of the approach determines the optimal sizing of the PV-BES system, by taking into account the optimal powers obtained in the first step, the solar irradiance diagram and the average temperature for each month of the year for the area in which the DN is located. The optimal sizing includes optimal maximum power of the PV system and the optimal maximum power and energy capacity of the BES unit, determined by the proposed iterative method. The results are generated using the topology of the IEEE 18-bus radial DN for three different load diagrams, on a monthly and annual basis.},
keywords = {distribution network (DN), genetic algorithm (GA), photovoltaic-battery energy storage (PV-BES) system, voltage profile, wild horse optimization (WHO)},
issn = {3070-2607},
publisher = {Institute of Central Computation and Knowledge}
}
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