A Distributed Stochastic Energy Management Framework Based-Fuzzy-PDMM for Smart Grids Considering Wind Park and Energy Storage Systems
Distributed optimization methods have been vastly investigated and approved by the researchers due to their major advantages including high accuracy, secured performance and low time-consuming structure compared to the centralized frameworks. This paper aims to provide a novel method based on fuzzy...
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| Format: | Article |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9381856/ |
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| author | Mohamed A. Mohamed Abdulaziz Almalaq Heba M. Abdullah Khalid Abdulaziz Alnowibet Adel Fahad Alrasheedi Mazin Saleh Amin Zaindin |
| author_facet | Mohamed A. Mohamed Abdulaziz Almalaq Heba M. Abdullah Khalid Abdulaziz Alnowibet Adel Fahad Alrasheedi Mazin Saleh Amin Zaindin |
| author_sort | Mohamed A. Mohamed |
| collection | DOAJ |
| description | Distributed optimization methods have been vastly investigated and approved by the researchers due to their major advantages including high accuracy, secured performance and low time-consuming structure compared to the centralized frameworks. This paper aims to provide a novel method based on fuzzy primal-dual method of multipliers (PDMM) to manage the optimal energy scheduling problem in the smart grids. The proposed method illustrates some unrivaled points of interest which are more preferable than the conventional alternating direction method of multipliers (ADMM) in terms of preciseness and convergence speed. The proposed smart grid is constructed of different components such as generators, wind park and storage devices as two of the most profitable and applicable energy sources in the power grids. In order to model the uncertainty effects, a stochastic method based on fuzzy cloud theory is developed to capture the high-dimension uncertainty in a more realistic way. The units are scheduled to exchange energy in the smart grid in a fully distributed manner when meeting the active/reactive generation and demand balance. Such an energy exchanging process continues until a proper solution would be found through which all the agents in the system are satiated. The simulation results on the IEEE 24-bus test system indicate that the proposed stochastic distributed energy management framework yields an error of less than 0.018% compared to the centralized approach. |
| first_indexed | 2024-12-13T18:07:21Z |
| format | Article |
| id | doaj.art-162d0649f84f4b72bb943784630c59db |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T18:07:21Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-162d0649f84f4b72bb943784630c59db2022-12-21T23:36:02ZengIEEEIEEE Access2169-35362021-01-019466744668510.1109/ACCESS.2021.30675019381856A Distributed Stochastic Energy Management Framework Based-Fuzzy-PDMM for Smart Grids Considering Wind Park and Energy Storage SystemsMohamed A. Mohamed0https://orcid.org/0000-0001-8700-0270Abdulaziz Almalaq1https://orcid.org/0000-0001-8153-4327Heba M. Abdullah2https://orcid.org/0000-0002-0063-4957Khalid Abdulaziz Alnowibet3https://orcid.org/0000-0001-5760-0216Adel Fahad Alrasheedi4https://orcid.org/0000-0003-4492-1082Mazin Saleh Amin Zaindin5Department of Electrical Engineering, Faculty of Engineering, Minia University, Minia, EgyptDepartment of Electrical Engineering, University of Hail, Ha’il, Saudi ArabiaReHub United Research and Consultation Company, Salmiya, KuwaitDepartment of Statistics and Operations Research, College of Science, King Saud University, Riyadh, Saudi ArabiaDepartment of Statistics and Operations Research, College of Science, King Saud University, Riyadh, Saudi ArabiaDepartment of Statistics and Operations Research, College of Science, King Saud University, Riyadh, Saudi ArabiaDistributed optimization methods have been vastly investigated and approved by the researchers due to their major advantages including high accuracy, secured performance and low time-consuming structure compared to the centralized frameworks. This paper aims to provide a novel method based on fuzzy primal-dual method of multipliers (PDMM) to manage the optimal energy scheduling problem in the smart grids. The proposed method illustrates some unrivaled points of interest which are more preferable than the conventional alternating direction method of multipliers (ADMM) in terms of preciseness and convergence speed. The proposed smart grid is constructed of different components such as generators, wind park and storage devices as two of the most profitable and applicable energy sources in the power grids. In order to model the uncertainty effects, a stochastic method based on fuzzy cloud theory is developed to capture the high-dimension uncertainty in a more realistic way. The units are scheduled to exchange energy in the smart grid in a fully distributed manner when meeting the active/reactive generation and demand balance. Such an energy exchanging process continues until a proper solution would be found through which all the agents in the system are satiated. The simulation results on the IEEE 24-bus test system indicate that the proposed stochastic distributed energy management framework yields an error of less than 0.018% compared to the centralized approach.https://ieeexplore.ieee.org/document/9381856/Smart griddistributed optimizationstochastic energy managementwind parkenergy storage systemsfuzzy cloud theory |
| spellingShingle | Mohamed A. Mohamed Abdulaziz Almalaq Heba M. Abdullah Khalid Abdulaziz Alnowibet Adel Fahad Alrasheedi Mazin Saleh Amin Zaindin A Distributed Stochastic Energy Management Framework Based-Fuzzy-PDMM for Smart Grids Considering Wind Park and Energy Storage Systems IEEE Access Smart grid distributed optimization stochastic energy management wind park energy storage systems fuzzy cloud theory |
| title | A Distributed Stochastic Energy Management Framework Based-Fuzzy-PDMM for Smart Grids Considering Wind Park and Energy Storage Systems |
| title_full | A Distributed Stochastic Energy Management Framework Based-Fuzzy-PDMM for Smart Grids Considering Wind Park and Energy Storage Systems |
| title_fullStr | A Distributed Stochastic Energy Management Framework Based-Fuzzy-PDMM for Smart Grids Considering Wind Park and Energy Storage Systems |
| title_full_unstemmed | A Distributed Stochastic Energy Management Framework Based-Fuzzy-PDMM for Smart Grids Considering Wind Park and Energy Storage Systems |
| title_short | A Distributed Stochastic Energy Management Framework Based-Fuzzy-PDMM for Smart Grids Considering Wind Park and Energy Storage Systems |
| title_sort | distributed stochastic energy management framework based fuzzy pdmm for smart grids considering wind park and energy storage systems |
| topic | Smart grid distributed optimization stochastic energy management wind park energy storage systems fuzzy cloud theory |
| url | https://ieeexplore.ieee.org/document/9381856/ |
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