The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Distributed Robust Power System State Estimation
Abstract
Deregulation of energy markets, penetration of renewables, advanced metering capabilities, and the urge for situational awareness, all call for system-wide power system state estimation (PSSE). Implementing a centralized estimator though is practically infeasible due to the complexity scale of an interconnection, the communication bottleneck in real-time monitoring, regional disclosure policies, and reliability issues. In this context, distributed PSSE methods are treated here under a unified and systematic framework. A novel algorithm is developed based on the alternating direction method of multipliers. It leverages existing PSSE solvers, respects privacy policies, exhibits low communication load, and its convergence to the centralized estimates is guaranteed even in the absence of local observability. Beyond the conventional least-squares based PSSE, the decentralized framework accommodates a robust state estimator. By exploiting interesting links to the compressive sampling advances, the latter jointly estimates the state and identifies corrupted measurements. The novel algorithms are numerically evaluated using the IEEE 14-, 118-bus, and a 4200-bus benchmarks. Simulations demonstrate that the attainable accuracy can be reached within a few inter-area exchanges, while largest residual tests are outperformed.
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Power System Static-State Estimation, Part I: Exact Model
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False data injection attacks against state estimation in electric power grids
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Cyber–Physical Security of a Smart Grid Infrastructure
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On the Linear Convergence of the ADMM in Decentralized Consensus Optimization
Shi, W., Ling, Q., Yuan, K., Wu, G., & Yin, W. (2014) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2014.2304432 · Cited by 820
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Yuan, K., Ling, Q., & Yin, W. (2013) · arXiv · doi:10.48550/arxiv.1310.7063 · Cited by 635
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Survey of Security Advances in Smart Grid: A Data Driven Approach
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Metadata
- Authors
- Kekatos, V., & Giannakis, G. B.
- Venue
- IEEE Transactions on Power Systems
- Published
- 2013-05
- Volume
- 28
- Issue
- 2
- Pages
- 1617-1626
- ISSN
- 0885-8950 (ISSN-L)
- 1558-0679
- OpenAlex
- W1983933235
- Cited by
- 521
- References
- 16
- FWCI
- 21.77
- Type
- journal article
- Language
- en
- Open access
- closed
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