Closing the Loop: Dynamic State Estimation and Feedback Optimization of Power Grids


METADATA ONLY
Loading...

Date

2020-12

Publication Type

Journal Article

ETH Bibliography

yes

Citations

Altmetric
METADATA ONLY

Data

Rights / License

Abstract

This paper considers the problem of online feedback optimization to solve the AC Optimal Power Flow in real-time in power grids. This consists in continuously driving the controllable power injections and loads towards the optimal set-points in time-varying conditions based on real-time measurements performed on the grid. However, instead of assuming noise-free full state measurement like in recently proposed feedback optimization schemes, we connect a dynamic State Estimation using available measurements, and study its dynamic interaction with the optimization scheme. We certify stability of this interconnection and the convergence in expectation of the state estimate and the control inputs towards the true state values and optimal set-points respectively. Additionally, we bound the resulting stochastic error. Finally, we show the effectiveness of the approach on a test case using high resolution consumption data. © 2020 Elsevier B.V.

Publication status

published

Editor

Book title

Volume

189

Pages / Article No.

106753

Publisher

Elsevier

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Distribution grid state estimation; AC optimal power flow; Online feedback optimization; Voltage regulation

Organisational unit

09478 - Dörfler, Florian / Dörfler, Florian check_circle

Notes

Funding

Related publications and datasets