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Data-Driven Sparsity-Promoting Optimal Control of Power Buffers in DC Microgrids.
- Source :
-
IEEE Transactions on Energy Conversion . Sep2021, Vol. 36 Issue 3, p1919-1930. 12p. - Publication Year :
- 2021
-
Abstract
- A power buffer is a power electronics converter with a large capacitor that shields a weak DC grid from abrupt load changes. Distributed control solutions have been shown to be superior to the decentralized ones; however, the effects of the communication network topology on the control performance of these buffers have not yet been studied. This article offers a data-driven optimal solution to reduce the interactions between different control loops of power buffers while minimizing a closed-loop performance function. Reinforcement learning methods deal with the optimal control of nonlinear systems, and a Tabu Search method addresses the resulting combinatorial problem. The proposed solutions are validated for a DC microgrid in a controller/hardware-in-the-loop environment. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 08858969
- Volume :
- 36
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Energy Conversion
- Publication Type :
- Academic Journal
- Accession number :
- 153128042
- Full Text :
- https://doi.org/10.1109/TEC.2020.3043709