Learning-based hierarchical control for a net-zero commercial building with solar plus storage and high EV Chargers Penetration
The integration of renewable energy resources and electric vehicles in microgrids presents a significant challenge due to generation and demand uncertainty. However, our technical and market research in Solar Plus Storage microgrids, carried out as part of a US Department of Energy's Solar Priz...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-11-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484723014658 |
| _version_ | 1827400891823554560 |
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| author | Masood Shahverdi Arash Jamehbozorg Christopher Serrato Nelson Flores |
| author_facet | Masood Shahverdi Arash Jamehbozorg Christopher Serrato Nelson Flores |
| author_sort | Masood Shahverdi |
| collection | DOAJ |
| description | The integration of renewable energy resources and electric vehicles in microgrids presents a significant challenge due to generation and demand uncertainty. However, our technical and market research in Solar Plus Storage microgrids, carried out as part of a US Department of Energy's Solar Prize project, demonstrates the efficacy of advanced microgrid controls in managing this uncertainty while saving billions of dollars. The control system must be equipped with advanced optimization tools and adaptive forecasting models that minimize planning errors for future optimal operation to achieve this. This study contributes to the literature by quantifying the impact of integrating adaptive learning-based forecasting tools for PV power and electrical load at the tertiary level of a hierarchical control system. Additionally, we use the developed learning forecasters and optimization algorithms of the tertiary level to solve intertwined optimal sizing and operation subproblems as a combined problem for a solar plus storage system. |
| first_indexed | 2024-03-08T20:10:13Z |
| format | Article |
| id | doaj.art-82ef640af3ef49d494aee3bfc426ef9e |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-03-08T20:10:13Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-82ef640af3ef49d494aee3bfc426ef9e2023-12-23T05:21:57ZengElsevierEnergy Reports2352-48472023-11-011037243732Learning-based hierarchical control for a net-zero commercial building with solar plus storage and high EV Chargers PenetrationMasood Shahverdi0Arash Jamehbozorg1Christopher Serrato2Nelson Flores3Corresponding author.; California State University, Los Angeles, Department of Electrical and Computer Engineering, United StatesCalifornia State University, Los Angeles, Department of Electrical and Computer Engineering, United StatesCalifornia State University, Los Angeles, Department of Electrical and Computer Engineering, United StatesCalifornia State University, Los Angeles, Department of Electrical and Computer Engineering, United StatesThe integration of renewable energy resources and electric vehicles in microgrids presents a significant challenge due to generation and demand uncertainty. However, our technical and market research in Solar Plus Storage microgrids, carried out as part of a US Department of Energy's Solar Prize project, demonstrates the efficacy of advanced microgrid controls in managing this uncertainty while saving billions of dollars. The control system must be equipped with advanced optimization tools and adaptive forecasting models that minimize planning errors for future optimal operation to achieve this. This study contributes to the literature by quantifying the impact of integrating adaptive learning-based forecasting tools for PV power and electrical load at the tertiary level of a hierarchical control system. Additionally, we use the developed learning forecasters and optimization algorithms of the tertiary level to solve intertwined optimal sizing and operation subproblems as a combined problem for a solar plus storage system.http://www.sciencedirect.com/science/article/pii/S2352484723014658Hierarchical control systemOptimizationSolar generationAnd Energy Storage System |
| spellingShingle | Masood Shahverdi Arash Jamehbozorg Christopher Serrato Nelson Flores Learning-based hierarchical control for a net-zero commercial building with solar plus storage and high EV Chargers Penetration Energy Reports Hierarchical control system Optimization Solar generation And Energy Storage System |
| title | Learning-based hierarchical control for a net-zero commercial building with solar plus storage and high EV Chargers Penetration |
| title_full | Learning-based hierarchical control for a net-zero commercial building with solar plus storage and high EV Chargers Penetration |
| title_fullStr | Learning-based hierarchical control for a net-zero commercial building with solar plus storage and high EV Chargers Penetration |
| title_full_unstemmed | Learning-based hierarchical control for a net-zero commercial building with solar plus storage and high EV Chargers Penetration |
| title_short | Learning-based hierarchical control for a net-zero commercial building with solar plus storage and high EV Chargers Penetration |
| title_sort | learning based hierarchical control for a net zero commercial building with solar plus storage and high ev chargers penetration |
| topic | Hierarchical control system Optimization Solar generation And Energy Storage System |
| url | http://www.sciencedirect.com/science/article/pii/S2352484723014658 |
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