Optimum Parallel Processing Schemes to Improve the Computation Speed for Renewable Energy Allocation and Sizing Problems
The optimum penetration of distributed generations into the distribution grid provides several technical and economic benefits. However, the computational time required to solve the constrained optimization problems increases with the increasing network scale and may be too long for online implement...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/24/9301 |
| _version_ | 1797459876520132608 |
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| author | Soheil Younesi Bahman Ahmadi Oguzhan Ceylan Aydogan Ozdemir |
| author_facet | Soheil Younesi Bahman Ahmadi Oguzhan Ceylan Aydogan Ozdemir |
| author_sort | Soheil Younesi |
| collection | DOAJ |
| description | The optimum penetration of distributed generations into the distribution grid provides several technical and economic benefits. However, the computational time required to solve the constrained optimization problems increases with the increasing network scale and may be too long for online implementations. This paper presents a parallel solution of a multi-objective distributed generation (DG) allocation and sizing problem to handle a large number of computations. The aim is to find the optimum number of processors in addition to energy loss and DG cost minimization. The proposed formulation is applied to a 33-bus test system, and the results are compared with themselves and with the base case operating conditions using the optimal values and three popular multi-objective optimization metrics. The results show that comparable solutions with high-efficiency values can be obtained up to a certain number of processors. |
| first_indexed | 2024-03-09T16:57:11Z |
| format | Article |
| id | doaj.art-f0732758ee30420ba559a2712af4a74a |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T16:57:11Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-f0732758ee30420ba559a2712af4a74a2023-11-24T14:34:24ZengMDPI AGEnergies1996-10732022-12-011524930110.3390/en15249301Optimum Parallel Processing Schemes to Improve the Computation Speed for Renewable Energy Allocation and Sizing ProblemsSoheil Younesi0Bahman Ahmadi1Oguzhan Ceylan2Aydogan Ozdemir3Department of Electrical Engineering, Istanbul Technical University, 34467 Istanbul, TurkeyDepartment of Electrical Engineering, Mathematics and Computer Science, University of Twente, 7522 NB Enschede, The NetherlandsDepartment of Electrical and Electronics Engineering, Marmara University, 34722 Istanbul, TurkeyDepartment of Electrical Engineering, Istanbul Technical University, 34467 Istanbul, TurkeyThe optimum penetration of distributed generations into the distribution grid provides several technical and economic benefits. However, the computational time required to solve the constrained optimization problems increases with the increasing network scale and may be too long for online implementations. This paper presents a parallel solution of a multi-objective distributed generation (DG) allocation and sizing problem to handle a large number of computations. The aim is to find the optimum number of processors in addition to energy loss and DG cost minimization. The proposed formulation is applied to a 33-bus test system, and the results are compared with themselves and with the base case operating conditions using the optimal values and three popular multi-objective optimization metrics. The results show that comparable solutions with high-efficiency values can be obtained up to a certain number of processors.https://www.mdpi.com/1996-1073/15/24/9301smart gridDG penetrationparallel computingloss minimizationmulti-objective optimization |
| spellingShingle | Soheil Younesi Bahman Ahmadi Oguzhan Ceylan Aydogan Ozdemir Optimum Parallel Processing Schemes to Improve the Computation Speed for Renewable Energy Allocation and Sizing Problems Energies smart grid DG penetration parallel computing loss minimization multi-objective optimization |
| title | Optimum Parallel Processing Schemes to Improve the Computation Speed for Renewable Energy Allocation and Sizing Problems |
| title_full | Optimum Parallel Processing Schemes to Improve the Computation Speed for Renewable Energy Allocation and Sizing Problems |
| title_fullStr | Optimum Parallel Processing Schemes to Improve the Computation Speed for Renewable Energy Allocation and Sizing Problems |
| title_full_unstemmed | Optimum Parallel Processing Schemes to Improve the Computation Speed for Renewable Energy Allocation and Sizing Problems |
| title_short | Optimum Parallel Processing Schemes to Improve the Computation Speed for Renewable Energy Allocation and Sizing Problems |
| title_sort | optimum parallel processing schemes to improve the computation speed for renewable energy allocation and sizing problems |
| topic | smart grid DG penetration parallel computing loss minimization multi-objective optimization |
| url | https://www.mdpi.com/1996-1073/15/24/9301 |
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