ABSTRACT
Safety-critical infrastructures must operate in a safe and reliable way. Fault tree analysis is a widespread method used for risk assessment of these systems: fault trees (FTs) are required by, e.g., the Federal Aviation Administration and the Nuclear Regulatory Commission. In spite of their popularity, little work has been done on formulating structural queries about and analyzing these, e.g., when evaluating potential scenarios, and to give practitioners instruments to formulate queries on in an understandable yet powerful way. In this paper, we aim to fill this gap by extending [37], a logic that reasons about Boolean. To do so, we introduce a Probabilistic Fault tree Logic is a simple, yet expressive logic that supports easier formulation of complex scenarios and specification of FT properties that comprise probabilities. Alongside, we present, a domain specific language to further ease property specification. We showcase and by applying them to a COVID-19 related FT and to a FT for an oil/gas pipeline. Finally, we present theory and model checking algorithms based on binary decision diagrams (BDDs). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Safety-critical infrastructures must operate in a safe and reliable way. Fault tree analysis is a widespread method used for risk assessment of these systems: fault trees (FTs) are required by, e.g., the Federal Aviation Administration and the Nuclear Regulatory Commission. In spite of their popularity, little work has been done on formulating structural queries about and analyzing these, e.g., when evaluating potential scenarios, and to give practitioners instruments to formulate queries on in an understandable yet powerful way. In this paper, we aim to fill this gap by extending [37], a logic that reasons about Boolean. To do so, we introduce a Probabilistic Fault tree Logic is a simple, yet expressive logic that supports easier formulation of complex scenarios and specification of FT properties that comprise probabilities. Alongside, we present, a domain specific language to further ease property specification. We showcase and by applying them to a COVID-19 related FT and to a FT for an oil/gas pipeline. Finally, we present theory and model checking algorithms based on binary decision diagrams (BDDs). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Due to the effect of Covid-19 the pattern of energy consumption of Uttarakhand State has affected during lockdown. Since the inception of Covid-19 in Uttarakhand there has drastic change in electricity consumption in thirteen districts of the State including Dehradun which is also a Smart City. It has reported that there is decrease in electricity consumption in the year 2020-21. In this study the long-term load forecasting using Artificial Neural Network is used as per the information released by Uttarakhand Electricity Regulatory Commission (UERC) in their tariff order for Financial Year 2021-22. There is eleven million population in Uttarakhand at present. During economic shutdown in Uttarakhand State the power utilities has faced the challenge of electricity generation, transmission, and distribution. It has been observed that during Covid-19 there is 939.97 million units generated energy loss has faced by power utilities companies in Uttarakhand. Uttarakhand is a emerging State where lots of new Technologies are in pipeline. In this Study the forecasted results is for nine years (2022-2030) which represents that there will be sudden rise in electricity consumption after 2025 to 2030 in Uttarakhand due to the intervention of electric vehicles. In Uttarakhand Dehradun is also a smart city where lots of IoT devices have been deployed across city which are are also consuming electricity. This study has reduced the forecast error upto 7.17 % so that there would be minimum revenue loss in future to the power utilities in Uttarakhand. © 2021 IEEE.
ABSTRACT
The demand of electricity has been reduced significantly due to the recent COVID-19 pandemic. Governments around the world were compelled to reduce the business activity in response to minimize the threat of coronavirus. This on-going situation due to COVID-19 has changed the lifestyle globally as people are mostly staying home and working from home if possible. Hence, there is a significant increase in residential load demand while there is a substantial decrease in commercial and industrial loads. This devastating situation creates new challenges in the technical and financial activities of the power sector and hence most of the utilities around the world initiated a disaster management plan to tackle this ongoing challenges/threats. Therefore, this study aims to investigate the global scenarios of power systems during COVID-19 along with the socio-economic and technical issues faced by the utilities. Then, this study further scrutinized the Indian power system as a case study and explored scenarios, issues and challenges currently being faced to manage the consumer load demand, including the actions taken by the utilities/power sector for the smooth operation of the power system. Finally, a set of recommendations are presented to support the government/policymakers/utilities around the world not only to overcome the current crisis but also to overcome future unforeseeable pandemic alike scenario.