# Fast Local Voltage Control under Limited Reactive Power: Optimality and Stability Analysis

arXiv: https://arxiv.org/abs/1510.07013 · HTML: https://mlsanity.com/paper/1510.07013/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Oct 2015.

## Built on by (most cited first, 5 of 5)

- [Risk-Aware Learning for Scalable Voltage Optimization in Distribution Grids](https://mlsanity.com/paper/2110.01490/) (2021)
- [Bi-level Off-policy Reinforcement Learning for Volt/VAR Control Involving Continuous and Discrete Devices](https://mlsanity.com/paper/2104.05902/) (2021)
- [Learning to Attack Powergrids with DERs](https://mlsanity.com/paper/2204.11352/) (2022)
- [Efficient Reinforcement Learning Through Trajectory Generation](https://mlsanity.com/paper/2211.17249/) (2022)
- [Scalable Optimal Design of Incremental Volt/VAR Control using Deep Neural Networks](https://mlsanity.com/paper/2301.01440/) (2023)

## Abstract (arXiv)

High penetration of distributed energy resources presents several challenges and opportunities for voltage regulation in power distribution systems. A local reactive power (VAR) control framework will be developed that can fast respond to voltage mismatch and address the robustness issues of (de-)centralized approaches against communication delays and noises. Using local bus voltage measurements, the proposed gradient-projection based schemes explicitly account for the VAR limit of every bus, and are proven convergent to a surrogate centralized problem with proper parameter choices. This optimality result quantifies the capability of local VAR control without requiring any real-time communications. The proposed framework and analysis generalize earlier results on the droop VAR control design, which may suffer from under-utilization of VAR resources in order to ensure stability. Numerical tests have demonstrated the validity of our analytical results and the effectiveness of proposed approaches implemented on realistic three-phase systems.