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Increasingly severe weather threats urge system operators to apply a systematic approach to cope with emergencies. In this context, a sound estimation of the time needed to recover electric service and infrastructure plays an important role for recovery management. The paper proposes a quantitative methodology to simulate the service and infrastructure recovery process with its uncertainties, highlighting the dependence of the main recovery characteristics (e.g. duration, energy not supplied) on several technical and environmental aspects (e.g. visibility, road availability). Simulations run on a realistic HV (High Voltage) grid show that results are consistent with operator's experience, and the approach can be used to improve the organization and management of the recovery process at planning and actual emergency stages.
E. Ciapessoni; D. Cirio; A. Pitto; M. Sforna. A quantitative methodology to assess the process of service and infrastructure recovery in power systems. Electric Power Systems Research 2020, 189, 106735 .
AMA StyleE. Ciapessoni, D. Cirio, A. Pitto, M. Sforna. A quantitative methodology to assess the process of service and infrastructure recovery in power systems. Electric Power Systems Research. 2020; 189 ():106735.
Chicago/Turabian StyleE. Ciapessoni; D. Cirio; A. Pitto; M. Sforna. 2020. "A quantitative methodology to assess the process of service and infrastructure recovery in power systems." Electric Power Systems Research 189, no. : 106735.
Severe natural events leading to wide and intense impacts on power systems are becoming more and more frequent due to climate changes. Operators are urged to set up plans to assess the possible consequences of such events, in view of counteracting them. To this aim, the application of the resilience concept can be beneficial. The paper describes a methodology for power system resilience assessment and enhancement, aimed at quantifying both system resilience indicators evaluated for severe threats, and the benefits to resilience brought by operational and grid hardening measures. The capabilities of the methodology are demonstrated on real study cases.
Emanuele Ciapessoni; Diego Cirio; Andrea Pitto; Marino Sforna. Quantification of the Benefits for Power System of Resilience Boosting Measures. Applied Sciences 2020, 10, 5402 .
AMA StyleEmanuele Ciapessoni, Diego Cirio, Andrea Pitto, Marino Sforna. Quantification of the Benefits for Power System of Resilience Boosting Measures. Applied Sciences. 2020; 10 (16):5402.
Chicago/Turabian StyleEmanuele Ciapessoni; Diego Cirio; Andrea Pitto; Marino Sforna. 2020. "Quantification of the Benefits for Power System of Resilience Boosting Measures." Applied Sciences 10, no. 16: 5402.
A thorough investigation of power system security requires the analysis of the vulnerabilities to natural and man-related threats which potentially trigger multiple contingencies. In particular, extreme weather events are becoming more and more frequent due to climate changes and often cause large load disruptions on the system, thus the support for security enhancement gets tricky. Exploiting data coming from forecasting systems in a security assessment environment can help assess the risk of operating power systems subject to the disturbances provoked by the weather event itself. In this context, the paper proposes a security assessment methodology, based on an updated definition of risk suitable for power system risk evaluations. Big data analytics can be useful to get an accurate model for weather-related threats. The relevant software (SW) platform integrates the security assessment methodology with prediction systems which provide short term forecasts of the threats affecting the system. The application results on a real wet snow threat scenario in the Italian High Voltage grid demonstrate the effectiveness of the proposed approach with respect to conventional security approaches, by complementing the conventional “N − 1” security criterion and exploiting big data to link the security assessment phase to the analysis of incumbent threats.
Emanuele Ciapessoni; Diego Cirio; Andrea Pitto; Pietro Marcacci; Matteo Lacavalla; Stefano Massucco; Federico Silvestro; Marino Sforna. A Risk-Based Methodology and Tool Combining Threat Analysis and Power System Security Assessment. Energies 2017, 11, 83 .
AMA StyleEmanuele Ciapessoni, Diego Cirio, Andrea Pitto, Pietro Marcacci, Matteo Lacavalla, Stefano Massucco, Federico Silvestro, Marino Sforna. A Risk-Based Methodology and Tool Combining Threat Analysis and Power System Security Assessment. Energies. 2017; 11 (1):83.
Chicago/Turabian StyleEmanuele Ciapessoni; Diego Cirio; Andrea Pitto; Pietro Marcacci; Matteo Lacavalla; Stefano Massucco; Federico Silvestro; Marino Sforna. 2017. "A Risk-Based Methodology and Tool Combining Threat Analysis and Power System Security Assessment." Energies 11, no. 1: 83.