Network-Cognizant Voltage Droop Control for Distribution Grids
Not on the map. Why?
Abstract (arXiv)
This paper examines distribution systems with a high integration of distributed energy resources (DERs) and addresses the design of local control methods for real-time voltage regulation. Particularly, the paper focuses on proportional control strategies where the active and reactive output-powers of DERs are adjusted in response to (and proportionally to) local changes in voltage levels. The design of the voltage-active power and voltage-reactive power characteristics leverages suitable linear approximations of the AC power-flow equations and is network-cognizant; that is, the coefficients of the controllers embed information on the location of the DERs and forecasted non-controllable loads/injections and, consequently, on the effect of DER power adjustments on the overall voltage profile. A robust approach is pursued to cope with uncertainty in the forecasted non-controllable loads/power injections. Stability of the proposed local controllers is analytically assessed and numerically corroborated.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Feb 2017.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 3; 2022: 1.
4 papers.
- 2021Enforcing Policy Feasibility Constraints through Differentiable Projection for Energy Optimizationcited by 31
- 2021GridLearn: Multiagent Reinforcement Learning for Grid-Aware Building Energy Managementcited by 12
- 2021Controlling Smart Inverters using Proxies: A Chance-Constrained DNN-based Approachcited by 5
- 2022Optimal Design of Volt/VAR Control Rules of Inverters using Deep Learningcited by 2
- 2022Optimal Design of Volt/VAR Control Rules of Inverters using Deep Learning17 Nov 2022
- 2021GridLearn: Multiagent Reinforcement Learning for Grid-Aware Building Energy Management12 Oct 2021
- 2021Enforcing Policy Feasibility Constraints through Differentiable Projection for Energy Optimization19 May 2021
- 2021Controlling Smart Inverters using Proxies: A Chance-Constrained DNN-based Approach2 May 2021