# Distributed Management of Fluctuating Energy Resources in Dynamic Networked Systems

arXiv: https://arxiv.org/abs/2405.19015 · HTML: https://mlsanity.com/paper/2405.19015/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 47 references that are in the map.
- First posted on arXiv 29 May 2024.

## Builds on (most cited first, 11 of 11)

- [Online Convex Optimization with Stochastic Constraints](https://mlsanity.com/paper/1708.03741/) (2017)
- [Adaptive Algorithms for Online Convex Optimization with Long-term Constraints](https://mlsanity.com/paper/1512.07422/) (2015)
- [MetaGrad: Multiple Learning Rates in Online Learning](https://mlsanity.com/paper/1604.08740/) (2016)
- [Bandit Convex Optimization in Non-stationary Environments](https://mlsanity.com/paper/1907.12340/) (2019)
- [Bandit Convex Optimization for Scalable and Dynamic IoT Management](https://mlsanity.com/paper/1707.09060/) (2017)
- [Distributed Bandit Online Convex Optimization with Time-Varying Coupled Inequality Constraints](https://mlsanity.com/paper/1912.03719/) (2019)
- [Distribution-Free One-Pass Learning](https://mlsanity.com/paper/1706.02471/) (2017)
- [Distributed Task Management in Cyber-Physical Systems: How to Cooperate under Uncertainty?](https://mlsanity.com/paper/1812.03557/) (2018)
- [A Non-Stationary Bandit-Learning Approach to Energy-Efficient Femto-Caching with Rateless-Coded Transmission](https://mlsanity.com/paper/2005.04154/) (2020)
- [Distributed User Association in Energy Harvesting Small Cell Networks: A Competitive Market Model with Uncertainty](https://mlsanity.com/paper/1511.01976/) (2015)
- [Dynamic Control and Optimization of Distributed Energy Resources in a Microgrid](https://mlsanity.com/paper/1410.0054/) (2014)

## Built on by (most cited first, 1 of 1)

- [Structure-Dependent Regret and Constraint Violation Bounds for Online Convex Optimization with Time-Varying Constraints](https://mlsanity.com/paper/2603.14319/) (2026)

## Abstract (arXiv)

Modern power systems integrate renewable distributed energy resources (DERs) as an environment-friendly enhancement to meet the ever-increasing demands. However, the inherent unreliability of renewable energy renders developing DER management algorithms imperative. 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 that correspond to each node's limitations for energy production. We propose distributed decision-making policies to solve the formulated problem, where we utilize the notion of dynamic regret as the performance metric. We also include an adjustment strategy in our developed algorithm to reduce the constraint violations. Besides, we design a policy that deals with the non-stationary environment. Theoretical analysis shows the effectiveness of our proposed algorithm. Numerical experiments using a real-world dataset show superior performance of our proposal compared to state-of-the-art methods.