Abstract
Information and Communication Technologies (ICT), Wide Area Measurement Systems (WAMS) and state estimation represent the key-tools for achieving a reliable and accurate knowledge of the power grid, and represent the foundation of an information-based operation of Smart Grids. Nevertheless, ICT brings new potential vulnerabilities within the power grid operation, that need to be evaluated. The strong interdependence between power system and ICT systems requires new methodologies for modeling the smart grid as a Cyber Physical System (CPS), and finally analyzing the impact of ICT failures on the power grid operation. This paper proposes a novel methodological approach that combines Stochastic Activity Networks (SAN) modeling and numerical computation for dependability analysis of a 5G-based WAMS. Internal influences such as component failures and external influences such as rain effect are considered, and the impact of these failures are assessed over the WAMS capability to provide reliable data for performing an accurate power network state estimation. Different state estimation approaches (traditional SCADA and PMU-based algorithms) and weather conditions are compared in terms of mean states estimation error and safety. The results highlight that 5G based WAMS result in a close-to-ideal behavior which enforces the prospect of a future adoption for smart grid monitoring applications.
Highlights
The digitalization wave has invested many areas of industry, utilities and services in the last decades
These substations are provided with Phasor Measurement Units (PMUs)/μPMUs, whose signals may be aggregated by local or remote Phasor Data Concentrators (PDC) and sent to the Distribution System Operator (DSO) control center, where this information is stored in databases and/or processed for real time monitoring by Distribution Management System (DMS) algorithms
Different state estimator algorithms are compared, namely traditional Weighted Least Squares (WLS) state estimator and PMU-based state estimator. The performance of these algorithms are compared in terms of Mean Estimation Error and Safety metrics
Summary
The digitalization wave has invested many areas of industry, utilities and services in the last decades. To the knowledge of the authors, this is the first paper that investigates the overall dependability of 5G based wide area monitoring system (WAMS) comprehensively Both internal influences such as component failures and external influences such. A novel methodological approach is proposed, that combines Stochastic Activity Networks (SAN) modeling and numerical analysis, to take into account the continuous and discrete event activities of power system and ICT system, respectively Based on this method, a simulation tool is developed with the Möbius platform, extended with external C++ libraries developed by the authors. Different state estimation approaches are analyzed and compared by taking into account internal and external sources of failures, such as component faults and environmental conditions This analysis is performed over a novel 5G communication infrastructure proposed by the authors, and the suitability of this communication technology is analyzed in relation with the wide area measurement system requirements.
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