CRITFeb 19, 2019

Secure Distributed Dynamic State Estimation in Wide-Area Smart Grids

arXiv:1902.07288v271 citations
AI Analysis

This addresses security vulnerabilities in smart grids, which are critical for reliable energy distribution, but the approach is incremental as it combines existing techniques like Kalman filters and blockchain.

The paper tackles the problem of secure state estimation in wide-area smart grids by proposing a distributed mechanism that integrates blockchain for security, anomaly detection, and trust management, achieving reliable estimation and timely anomaly detection with theoretical guarantees on false alarm rates.

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.

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