Compressive Sensing Based Situational Awareness and Sensor Placement for DC Microgrids with Relatively Fixed Operation Patterns

TL;DR

This paper introduces a compressive sensing framework for efficient state estimation and sensor placement in DC microgrids with fixed operation patterns, reducing sensor count while maintaining accuracy.

Contribution

It develops a novel measurement placement strategy that minimizes matrix coherence, enhancing estimation accuracy with fewer sensors.

Findings

Effective reduction in sensor numbers achieved

Improved state estimation accuracy demonstrated

Framework applicable to fixed-pattern microgrids

Abstract

This paper proposes a DC microgrid state estimation and sensor placement method based on compressive sensing. Formulations of various types of measurements and components are developed under the proposed framework. A measurement placing strategy to minimize the coherence of the measurement matrix and thus increase estimation accuracy is presented. Simulation results show that the proposed state estimation and sensor placing approach can effectively reduce the number of sensors to achieve a certain level of estimation accuracy.