Abstract
Power buffers are DC-DC converters where a large capacitor helps shield the DC grid from abrupt load changes. While point of load converters (PoLC)s are mainly tasked with meeting the terminal load requirements, power buffers add inertia to the DC grid during transients. The stochastic behaviour of loads could necessitate an adaptive optimal control strategy for power buffers. The optimal control of power buffers is usually formulated as a nonzero-sum differential game. The load behaviour can be captured using a multivariate probabilistic collocation method (MPCM) to sample its uncertainty. An integral reinforcement learning (IRL) algorithm, applied to the multiplayer differential game, finds the optimal control policy. Simulation studies demonstrate the performance of the IRL-based stochastic optimal control of power buffers in a DC microgrid.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2023 American Control Conference, ACC 2023 |
| Publisher | IEEE |
| Pages | 3245-3250 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798350328066 |
| ISBN (Print) | 9781665469524 |
| DOIs | |
| Publication status | Published - 2023 |
| Externally published | Yes |
| Event | 2023 American Control Conference, ACC 2023 - San Diego, United States Duration: 31 May 2023 → 2 Jun 2023 |
Publication series
| Name | Proceedings of the American Control Conference |
|---|---|
| ISSN (Print) | 0743-1619 |
| ISSN (Electronic) | 2378-5861 |
Conference
| Conference | 2023 American Control Conference, ACC 2023 |
|---|---|
| Country/Territory | United States |
| City | San Diego |
| Period | 31/05/23 → 2/06/23 |
Bibliographical note
Publisher Copyright:© 2023 American Automatic Control Council.
Funding
This work is supported, in part, by the National Science Foundation Grant 1839804 and, in part, by Department of Navy Awards N00014-20-1-2858 and N00014-22-1-2001 issued by the Office of Naval Research.
Keywords
- DC microgrid
- power buffer
- reinforcement learning
- uncertainty