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Optimal economic dispatch of a virtual power plant based on gated recurrent unit proximal policy optimization.
- Source :
- Frontiers in Energy Research; 2024, p1-14, 14p
- Publication Year :
- 2024
-
Abstract
- The intermittent renewable energy in a virtual power plant (VPP) brings generation uncertainties, which prevents the VPP from providing a reliable and user-friendly power supply. To address this issue, this paper proposes a gated recurrent unit proximal policy optimization (GRUPPO)-based optimal VPP economic dispatch method. First, electrical generation, storage, and consumption are established to form a VPP framework by considering the accessibility of VPP state information. The optimal VPP economic dispatch can then be expressed as a partially observable Markov decision process (POMDP) problem. A novel deep reinforcement learning method called GRUPPO is further developed based on VPP time series characteristics. Finally, case studies are conducted over a 24-h period based on the actual historical data. The test results illustrate that the proposed economic dispatch can achieve a maximum operation cost reduction of 6.5% and effectively smooth the supply-demand uncertainties. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 2296598X
- Database :
- Complementary Index
- Journal :
- Frontiers in Energy Research
- Publication Type :
- Academic Journal
- Accession number :
- 175588306
- Full Text :
- https://doi.org/10.3389/fenrg.2024.1357406