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- W4372260123 abstract "Modern power systems integrate renewable distributed energy resources (DERs) as an environment-friendly enhancement to meet the ever-increasing demands. However, due to the inherent unreliability of renewable energy, it is imperative to develop effective algorithms for DER management. In this work, we study the energy-sharing problem in a system consisting of several DERs. Each agent harvests and distributes renewable energy in its neighborhood to optimize the network's performance while minimizing energy waste. We model this problem as a bandit convex optimization problem with constraints, where the constraints correspond to each node's limitations for energy production. We propose a distributed decision-making policy to solve the formulated problem, that achieves ${mathcal{O}}left( {{T^{frac{3}{4}}}} right)$ regret bound and ${mathcal{O}}left( {{T^{frac{3}{4}}}} right)$ constraint violations. To reduce the constraint violations, we suggest two decision-making variations. Numerical experiments using a real-world dataset show superior performance of our proposal compared to state-of-the-art methods." @default.
- W4372260123 created "2023-05-07" @default.
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- W4372260123 date "2023-06-04" @default.
- W4372260123 modified "2023-09-27" @default.
- W4372260123 title "A Bandit Online Convex Optimization Approach To Distributed Energy Management In Networked Systems" @default.
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- W4372260123 doi "https://doi.org/10.1109/icassp49357.2023.10095936" @default.
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