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Optimal sizing and placement of rooftop solar photovoltaic at Kabul city real distribution network
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- Mikaeel Ahmadi
- Faculty of Engineering University of the Ryukyus 1 Senbaru Nishihara‐cho Okinawa 903‐0213 Japan
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- Mohammed Elsayed Lotfy
- Faculty of Engineering University of the Ryukyus 1 Senbaru Nishihara‐cho Okinawa 903‐0213 Japan
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- Ryuto Shigenobu
- Faculty of Engineering University of the Ryukyus 1 Senbaru Nishihara‐cho Okinawa 903‐0213 Japan
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- Atsushi Yona
- Faculty of Engineering University of the Ryukyus 1 Senbaru Nishihara‐cho Okinawa 903‐0213 Japan
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- Tomonobu Senjyu
- Faculty of Engineering University of the Ryukyus 1 Senbaru Nishihara‐cho Okinawa 903‐0213 Japan
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Description
<jats:p>Renewable energy resources (RERs) such as wind and solar are said to be considerable promising of the power system worldwide, and Afghanistan is evaluated for abundant and feasible electricity generation capacity from these resources. It fortifies merging of RER to the electric power system of Afghanistan where power quality issue sums up with scheduled and unscheduled load shedding due to the shortage of electricity. This research study presents an optimal solution comprising of rooftop solar photovoltaic (PV) as distributed generation to a real and substantial 162‐bus electric distribution network (EDN) in Kabul, the capital of Afghanistan. Genetic algorithm (GA) based on Newton–Raphson power flow with the objective of power loss minimisation is put forward for sizing and placement of the solar PV at practically available locations or candidate buses of the network. This approach tends to reduce the dependency on the import power and at the same time improves the performance of the current system through minimisation of the total power loss and voltage deviation. The proposed method is simulated by MATLAB<jats:sup>®</jats:sup> software to compare and demonstrate the performance of the system under different scenarios of the PV allocations.</jats:p>
Journal
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- IET Generation, Transmission & Distribution
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IET Generation, Transmission & Distribution 12 (2), 303-309, 2017-11-20
Institution of Engineering and Technology (IET)
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Details 詳細情報について
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- CRID
- 1360565166906014976
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- ISSN
- 17518695
- 17518687
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- Article Type
- journal article
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- Data Source
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- Crossref
- KAKEN