Optimal Planning of Solar Photovoltaic (PV) and Wind-Based DGs for Achieving Techno-Economic Objectives across Various Load Models
Over the last few decades, distributed generation (DG) has become the most viable option in distribution systems (DSs) to mitigate the power losses caused by the substantial increase in electricity demand and to improve the voltage profile by enhancing power system reliability. In this study, two me...
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MDPI AG
2023-03-01
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Online Access: | https://www.mdpi.com/1996-1073/16/5/2444 |
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author | Habib Ur Rehman Arif Hussain Waseem Haider Sayyed Ahmad Ali Syed Ali Abbas Kazmi Muhammad Huzaifa |
author_facet | Habib Ur Rehman Arif Hussain Waseem Haider Sayyed Ahmad Ali Syed Ali Abbas Kazmi Muhammad Huzaifa |
author_sort | Habib Ur Rehman |
collection | DOAJ |
description | Over the last few decades, distributed generation (DG) has become the most viable option in distribution systems (DSs) to mitigate the power losses caused by the substantial increase in electricity demand and to improve the voltage profile by enhancing power system reliability. In this study, two metaheuristic algorithms, artificial gorilla troops optimization (GTO) and Tasmanian devil optimization (TDO), are presented to examine the utilization of DGs, as well as the optimal placement and sizing in DSs, with a special emphasis on maximizing the voltage stability index and minimizing the total operating cost index and active power loss, along with the minimizing of voltage deviation. The robustness of the algorithms is examined on the IEEE 33-bus and IEEE 69-bus radial distribution networks (RDNs) for PV- and wind-based DGs. The obtained results are compared with the existing literature to validate the effectiveness of the algorithms. The reduction in active power loss is 93.15% and 96.87% of the initial value for the 33-bus and 69-bus RDNs, respectively, while the other parameters, i.e., operating cost index, voltage deviation, and voltage stability index, are also improved. This validates the efficiency of the algorithms. The proposed study is also carried out by considering different voltage-dependent load models, including industrial, residential, and commercial types. |
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institution | Directory Open Access Journal |
issn | 1996-1073 |
language | English |
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spelling | doaj.art-4b2d2122c03844a48a0cea123235142a2023-11-17T07:38:44ZengMDPI AGEnergies1996-10732023-03-01165244410.3390/en16052444Optimal Planning of Solar Photovoltaic (PV) and Wind-Based DGs for Achieving Techno-Economic Objectives across Various Load ModelsHabib Ur Rehman0Arif Hussain1Waseem Haider2Sayyed Ahmad Ali3Syed Ali Abbas Kazmi4Muhammad Huzaifa5US-Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), H-12, Islamabad 44000, PakistanDepartment of Electrical and Computer Engineering, Sungkyunkwan University, Seoul 16419, Republic of KoreaDepartment of Electrical and Computer Engineering, Sungkyunkwan University, Seoul 16419, Republic of KoreaUS-Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), H-12, Islamabad 44000, PakistanUS-Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), H-12, Islamabad 44000, PakistanUS-Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), H-12, Islamabad 44000, PakistanOver the last few decades, distributed generation (DG) has become the most viable option in distribution systems (DSs) to mitigate the power losses caused by the substantial increase in electricity demand and to improve the voltage profile by enhancing power system reliability. In this study, two metaheuristic algorithms, artificial gorilla troops optimization (GTO) and Tasmanian devil optimization (TDO), are presented to examine the utilization of DGs, as well as the optimal placement and sizing in DSs, with a special emphasis on maximizing the voltage stability index and minimizing the total operating cost index and active power loss, along with the minimizing of voltage deviation. The robustness of the algorithms is examined on the IEEE 33-bus and IEEE 69-bus radial distribution networks (RDNs) for PV- and wind-based DGs. The obtained results are compared with the existing literature to validate the effectiveness of the algorithms. The reduction in active power loss is 93.15% and 96.87% of the initial value for the 33-bus and 69-bus RDNs, respectively, while the other parameters, i.e., operating cost index, voltage deviation, and voltage stability index, are also improved. This validates the efficiency of the algorithms. The proposed study is also carried out by considering different voltage-dependent load models, including industrial, residential, and commercial types.https://www.mdpi.com/1996-1073/16/5/2444artificial gorilla troops optimizationdistributed generationdistributed systemoperating costradial distribution networkTasmanian devil optimization |
spellingShingle | Habib Ur Rehman Arif Hussain Waseem Haider Sayyed Ahmad Ali Syed Ali Abbas Kazmi Muhammad Huzaifa Optimal Planning of Solar Photovoltaic (PV) and Wind-Based DGs for Achieving Techno-Economic Objectives across Various Load Models Energies artificial gorilla troops optimization distributed generation distributed system operating cost radial distribution network Tasmanian devil optimization |
title | Optimal Planning of Solar Photovoltaic (PV) and Wind-Based DGs for Achieving Techno-Economic Objectives across Various Load Models |
title_full | Optimal Planning of Solar Photovoltaic (PV) and Wind-Based DGs for Achieving Techno-Economic Objectives across Various Load Models |
title_fullStr | Optimal Planning of Solar Photovoltaic (PV) and Wind-Based DGs for Achieving Techno-Economic Objectives across Various Load Models |
title_full_unstemmed | Optimal Planning of Solar Photovoltaic (PV) and Wind-Based DGs for Achieving Techno-Economic Objectives across Various Load Models |
title_short | Optimal Planning of Solar Photovoltaic (PV) and Wind-Based DGs for Achieving Techno-Economic Objectives across Various Load Models |
title_sort | optimal planning of solar photovoltaic pv and wind based dgs for achieving techno economic objectives across various load models |
topic | artificial gorilla troops optimization distributed generation distributed system operating cost radial distribution network Tasmanian devil optimization |
url | https://www.mdpi.com/1996-1073/16/5/2444 |
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