An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks

<p>With the falling cost of Distributed Energy Resources (DERs) and the shift from fossil fuel to renewable energy in many countries, the integration of DERs is expected to grow. This can lead to a wide range of problems in the power system, such as voltage violations, overloading of distribut...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Mohammad Zain Ul Abideen (16904637) (author)
مؤلفون آخرون: Omar Ellabban (16864227) (author), Furkan Ahmad (709809) (author), Luluwah Al-Fagih (10063137) (author)
منشور في: 2022
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author Mohammad Zain Ul Abideen (16904637)
author2 Omar Ellabban (16864227)
Furkan Ahmad (709809)
Luluwah Al-Fagih (10063137)
author2_role author
author
author
author_facet Mohammad Zain Ul Abideen (16904637)
Omar Ellabban (16864227)
Furkan Ahmad (709809)
Luluwah Al-Fagih (10063137)
author_role author
dc.creator.none.fl_str_mv Mohammad Zain Ul Abideen (16904637)
Omar Ellabban (16864227)
Furkan Ahmad (709809)
Luluwah Al-Fagih (10063137)
dc.date.none.fl_str_mv 2022-11-14T00:00:00Z
dc.identifier.none.fl_str_mv 10.1109/access.2022.3221944
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/An_Enhanced_Approach_for_Solar_PV_Hosting_Capacity_Analysis_in_Distribution_Networks/24056313
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Engineering
Communications engineering
Electrical engineering
Information and computing sciences
Artificial intelligence
Distribution networks
Load flow
Particle swarm optimization
Springs
Reactive power
Energy management
Distributed power generation
Distributed energy resources
Hosting capacity
IEEE 123~bus network
Particle swarm optimization (PSO)
dc.title.none.fl_str_mv An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p>With the falling cost of Distributed Energy Resources (DERs) and the shift from fossil fuel to renewable energy in many countries, the integration of DERs is expected to grow. This can lead to a wide range of problems in the power system, such as voltage violations, overloading of distribution lines, reverse power flow, etc. Therefore, it is imperative to account for these adverse effects of the integration of DERs on the distribution network and minimize their impact when calculating the Hosting Capacity (HC). Two algorithms are presented in this study derived from a novel modified iterative method and a novel Repeated Particle Swarm Optimization (RPSO) method for determining the HC for multiple DER units simultaneously or a single DER unit integrating into radial or mesh networks. These algorithms calculate the optimal HC based on six scenarios of annual load and DER generation profiles. The developed algorithms were tested on the IEEE 123 bus network, and their results were compared. For a large-scale DER case, the modified iterative method significantly outperforms both the PSO and the normal iterative method in terms of computation time (30 minutes versus 3 hours versus 6 hours, respectively). In the case of multiple DERs, the RPSO method is the only option, as the other two methods cannot simultaneously optimize multiple DERs. As a result, it has been concluded that it is necessary to select HC calculation methods carefully and in accordance with the application, as each method has its own strengths and weaknesses.</p><h2>Other Information</h2><p>Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/legalcode" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2022.3221944" target="_blank">https://dx.doi.org/10.1109/access.2022.3221944</a></p>
eu_rights_str_mv openAccess
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identifier_str_mv 10.1109/access.2022.3221944
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/24056313
publishDate 2022
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spelling An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution NetworksMohammad Zain Ul Abideen (16904637)Omar Ellabban (16864227)Furkan Ahmad (709809)Luluwah Al-Fagih (10063137)EngineeringCommunications engineeringElectrical engineeringInformation and computing sciencesArtificial intelligenceDistribution networksLoad flowParticle swarm optimizationSpringsReactive powerEnergy managementDistributed power generationDistributed energy resourcesHosting capacityIEEE 123~bus networkParticle swarm optimization (PSO)<p>With the falling cost of Distributed Energy Resources (DERs) and the shift from fossil fuel to renewable energy in many countries, the integration of DERs is expected to grow. This can lead to a wide range of problems in the power system, such as voltage violations, overloading of distribution lines, reverse power flow, etc. Therefore, it is imperative to account for these adverse effects of the integration of DERs on the distribution network and minimize their impact when calculating the Hosting Capacity (HC). Two algorithms are presented in this study derived from a novel modified iterative method and a novel Repeated Particle Swarm Optimization (RPSO) method for determining the HC for multiple DER units simultaneously or a single DER unit integrating into radial or mesh networks. These algorithms calculate the optimal HC based on six scenarios of annual load and DER generation profiles. The developed algorithms were tested on the IEEE 123 bus network, and their results were compared. For a large-scale DER case, the modified iterative method significantly outperforms both the PSO and the normal iterative method in terms of computation time (30 minutes versus 3 hours versus 6 hours, respectively). In the case of multiple DERs, the RPSO method is the only option, as the other two methods cannot simultaneously optimize multiple DERs. As a result, it has been concluded that it is necessary to select HC calculation methods carefully and in accordance with the application, as each method has its own strengths and weaknesses.</p><h2>Other Information</h2><p>Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/legalcode" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2022.3221944" target="_blank">https://dx.doi.org/10.1109/access.2022.3221944</a></p>2022-11-14T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2022.3221944https://figshare.com/articles/journal_contribution/An_Enhanced_Approach_for_Solar_PV_Hosting_Capacity_Analysis_in_Distribution_Networks/24056313CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/240563132022-11-14T00:00:00Z
spellingShingle An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
Mohammad Zain Ul Abideen (16904637)
Engineering
Communications engineering
Electrical engineering
Information and computing sciences
Artificial intelligence
Distribution networks
Load flow
Particle swarm optimization
Springs
Reactive power
Energy management
Distributed power generation
Distributed energy resources
Hosting capacity
IEEE 123~bus network
Particle swarm optimization (PSO)
status_str publishedVersion
title An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
title_full An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
title_fullStr An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
title_full_unstemmed An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
title_short An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
title_sort An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
topic Engineering
Communications engineering
Electrical engineering
Information and computing sciences
Artificial intelligence
Distribution networks
Load flow
Particle swarm optimization
Springs
Reactive power
Energy management
Distributed power generation
Distributed energy resources
Hosting capacity
IEEE 123~bus network
Particle swarm optimization (PSO)