Multi-Area Active Distribution Network Scheduling in the Presence of Soft Open Points based on Information Gap Decision Theory
In this paper, a three-level framework is proposed to determine the optimal scheduling of a Multi-Area Active Distribution Network in the presence of inter-area Soft Open Points (SOPs). In this framework, the uncertainty of renewable generation and forecasted demand is modeled using information gap...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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University of Isfahan
2023-09-01
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| Series: | هوش محاسباتی در مهندسی برق |
| Subjects: | |
| Online Access: | https://isee.ui.ac.ir/article_27657_253348c5185abaad325adf7152622edd.pdf |
| _version_ | 1797315240050819072 |
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| author | Houman Bastami Mahmood reza Shakarami Meysam Doostizadeh |
| author_facet | Houman Bastami Mahmood reza Shakarami Meysam Doostizadeh |
| author_sort | Houman Bastami |
| collection | DOAJ |
| description | In this paper, a three-level framework is proposed to determine the optimal scheduling of a Multi-Area Active Distribution Network in the presence of inter-area Soft Open Points (SOPs). In this framework, the uncertainty of renewable generation and forecasted demand is modeled using information gap decision theory in a risk-averse manner. Coordinated scheduling of Controllable Distributed Generators (CDGs) and SOPs, inter-area energy exchanges and energy trading with upstream network considering the uncertainties are the contribution of the presented method. To improve the computational efficiency and to achieve the optimal solution, the scheduling problem is modeled as a second-order conic programming in which the operational and security constraints of the network, CDG limitations, and operational constraints of SOPs are accurately modeled and the problem is solved by executing CPLEX solver in MATLAB environment. A case study on IEEE 33-bus test system showcases the superiority of the proposed model compared to meta-heuristic algorithms such as particle swarm optimization, genetic algorithm, and gravitational search algorithm. |
| first_indexed | 2024-03-08T02:58:50Z |
| format | Article |
| id | doaj.art-44808e53bf5f4fe2aa1a89c13d5a4888 |
| institution | Directory Open Access Journal |
| issn | 2821-0689 |
| language | English |
| last_indexed | 2024-03-08T02:58:50Z |
| publishDate | 2023-09-01 |
| publisher | University of Isfahan |
| record_format | Article |
| series | هوش محاسباتی در مهندسی برق |
| spelling | doaj.art-44808e53bf5f4fe2aa1a89c13d5a48882024-02-13T11:55:32ZengUniversity of Isfahanهوش محاسباتی در مهندسی برق2821-06892023-09-011439510610.22108/isee.2023.134689.157827657Multi-Area Active Distribution Network Scheduling in the Presence of Soft Open Points based on Information Gap Decision TheoryHouman Bastami0Mahmood reza Shakarami1Meysam Doostizadeh2Department of Electrical Engineering, Faculty of Engineering, Lorestan University, Khorramabad, IranProfessor, Department of Electrical Engineering, Faculty of Engineering, Lorestan University, Khorramabad, IranAssistant Professor, Department of Electrical Engineering, Faculty of Engineering, Lorestan University, Khorramabad, IranIn this paper, a three-level framework is proposed to determine the optimal scheduling of a Multi-Area Active Distribution Network in the presence of inter-area Soft Open Points (SOPs). In this framework, the uncertainty of renewable generation and forecasted demand is modeled using information gap decision theory in a risk-averse manner. Coordinated scheduling of Controllable Distributed Generators (CDGs) and SOPs, inter-area energy exchanges and energy trading with upstream network considering the uncertainties are the contribution of the presented method. To improve the computational efficiency and to achieve the optimal solution, the scheduling problem is modeled as a second-order conic programming in which the operational and security constraints of the network, CDG limitations, and operational constraints of SOPs are accurately modeled and the problem is solved by executing CPLEX solver in MATLAB environment. A case study on IEEE 33-bus test system showcases the superiority of the proposed model compared to meta-heuristic algorithms such as particle swarm optimization, genetic algorithm, and gravitational search algorithm.https://isee.ui.ac.ir/article_27657_253348c5185abaad325adf7152622edd.pdfactive distribution networkinformation gap decision theoryrenewable resourcesschedulingsoft open pointsuncertainty |
| spellingShingle | Houman Bastami Mahmood reza Shakarami Meysam Doostizadeh Multi-Area Active Distribution Network Scheduling in the Presence of Soft Open Points based on Information Gap Decision Theory هوش محاسباتی در مهندسی برق active distribution network information gap decision theory renewable resources scheduling soft open points uncertainty |
| title | Multi-Area Active Distribution Network Scheduling in the Presence of Soft Open Points based on Information Gap Decision Theory |
| title_full | Multi-Area Active Distribution Network Scheduling in the Presence of Soft Open Points based on Information Gap Decision Theory |
| title_fullStr | Multi-Area Active Distribution Network Scheduling in the Presence of Soft Open Points based on Information Gap Decision Theory |
| title_full_unstemmed | Multi-Area Active Distribution Network Scheduling in the Presence of Soft Open Points based on Information Gap Decision Theory |
| title_short | Multi-Area Active Distribution Network Scheduling in the Presence of Soft Open Points based on Information Gap Decision Theory |
| title_sort | multi area active distribution network scheduling in the presence of soft open points based on information gap decision theory |
| topic | active distribution network information gap decision theory renewable resources scheduling soft open points uncertainty |
| url | https://isee.ui.ac.ir/article_27657_253348c5185abaad325adf7152622edd.pdf |
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