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

## TL;DR

This paper introduces a secure, distributed dynamic state estimation framework for wide-area smart grids, integrating blockchain-based security, real-time anomaly detection, and trust management to enhance resilience against cyber threats.

## Contribution

It presents a novel multi-layered security approach combining distributed Kalman filtering, blockchain security, and real-time anomaly and trust detection for smart grid state estimation.

## Key findings

- Achieves near-optimal state estimation under normal conditions.
- Effectively detects measurement anomalies and malicious centers in real-time.
- Ensures reliable state recovery after anomalies are identified.

## Abstract

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.