# Secure Distributed Dynamic State Estimation in Wide-Area Smart Grids

arXiv: https://arxiv.org/abs/1902.07288 · HTML: https://mlsanity.com/paper/1902.07288/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Feb 2019.

## Built on by (most cited first, 2 of 2)

- [A Comprehensive Survey on the Security of Smart Grid: Challenges, Mitigations, and Future Research Opportunities](https://mlsanity.com/paper/2407.07966/) (2024)
- [A Stream Learning Approach for Real-Time Identification of False Data Injection Attacks in Cyber-Physical Power Systems](https://mlsanity.com/paper/2210.06729/) (2022)

## Abstract (arXiv)

Smart grid is a large complex network with a myriad of vulnerabilities, usually operated in adversarial settings and regulated based on estimated system states. In this study, we propose a novel highly secure distributed dynamic state estimation mechanism for wide-area (multi-area) smart grids, composed of geographically separated subregions, each supervised by a local control center. We firstly propose a distributed state estimator assuming regular system operation, that achieves near-optimal performance based on the local Kalman filters and with the exchange of necessary information between local centers. To enhance the security, we further propose to (i) protect the network database and the network communication channels against attacks and data manipulations via a blockchain (BC)-based system design, where the BC operates on the peer-to-peer network of local centers, (ii) locally detect the measurement anomalies in real-time to eliminate their effects on the state estimation process, and (iii) detect misbehaving (hacked/faulty) local centers in real-time via a distributed trust management scheme over the network. We provide theoretical guarantees regarding the false alarm rates of the proposed detection schemes, where the false alarms can be easily controlled. Numerical studies illustrate that the proposed mechanism offers reliable state estimation under regular system operation, timely and accurate detection of anomalies, and good state recovery performance in case of anomalies.