Abstract
The integration of renewable energy sources (RES) into power distribution grids poses challenges to system reliability due to the inherent uncertainty in their power production. To address this issue, battery energy sources (BESs) are being increasingly used as a promising solution to counter the uncertainty associated with RES power production. During the overall system planning stage, the optimal capacity of the BESs has to be decided. In the operational phase, policies on when to charge the BESs and when to use them to support loads must be determined so that the BESs remain within their operating range, avoiding depletion of charge on one hand and remaining within acceptable margins of maximum charge on the other. In this paper, a stochastic control framework is used to determine BESs capacity, for microgrids (MGs), ensuring that during the operational phase, BESs' operating range is respected with pre-specified high probability. We provide an explicit analytical expression of the required BESs energy capacity for a single MG with RES as the main power source. Leveraging insights from the single MG case, the article focuses on the design and planning of BESs for the two-MG scenario. In this setting, MGs are allowed to share power while respecting the capacity constraints imposed by the power lines. We characterize the optimal power transfer policy between the MGs and the optimal BES capacity for the MGs.
| Original language | English (US) |
|---|---|
| Title of host publication | 2024 American Control Conference, ACC 2024 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 3551-3556 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798350382655 |
| DOIs | |
| State | Published - 2024 |
| Event | 2024 American Control Conference, ACC 2024 - Toronto, Canada Duration: Jul 10 2024 → Jul 12 2024 |
Publication series
| Name | Proceedings of the American Control Conference |
|---|---|
| ISSN (Print) | 0743-1619 |
Conference
| Conference | 2024 American Control Conference, ACC 2024 |
|---|---|
| Country/Territory | Canada |
| City | Toronto |
| Period | 7/10/24 → 7/12/24 |
Bibliographical note
Publisher Copyright:© 2024 AACC.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 13 Climate Action
Keywords
- Battery sizing
- Brownian motion
- Renewable
- Stochastic optimization
- Uncertainty
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