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Mahmoudi Nasr P. A Petri-net Model for Operational Cycle in SCADA Systems. JSDP 2020; 17 (2) :14-3
URL: http://jsdp.rcisp.ac.ir/article-1-900-en.html
URL: http://jsdp.rcisp.ac.ir/article-1-900-en.html
Mazandaran University
Abstract: (2975 Views)
Supervisory control and data acquisition (SCADA) system monitors and controls industrial processes in critical infrastructures (CIs) and plays the vital role in maintaining the reliability of CIs such as power, oil, and gas system. In fact, SCADA system refers to the set of control process, which measures and monitors sensors in remote substations from a control center. These sensors usually have a type of automated response capability when a certain criteria is met. When an abnormal system status occurs, an alarm signal is raised in control center and as a result the operator will be notified. In this way, all normal and abnormal system statuses are monitored in control center. In CI’s application, since several substation resources and their related sensors are too high (because the CI’s grid is often large, complex and wide), the number of alarms is very high. It gets worse when the operator mistakes and as a result, cascading alarms are flooded. In this condition, the rate of raising alarms may be more than clearing them.
In SCADA system, alarm clearing is one of the main duties of operators. When an alarm is raised in control center, the operator should clear it as soon as possible. However, the recent reports confirm the poor alarm clearing causes accidents in the SCADA system. As any operator mistake can increase the number of alarms and jeopardize the system reliability, alarms processing and decision-making for clearing them are a stressful and time-consuming for the SCADA operators. In a large and complex CI such as power system, when operators are overwhelmed by the system alarms, they may take wrong decisions and even ignore alarms. Alarm flooding, lots of operator’s workload and his/her fatigue as a result, are the main causes of operator’s mistake.
If generating of an alarm in a remote substation is denoted as an operational cycle in an SCADA system until clearing it by the operator in control center, the aim of this paper is modeling the operational cycle by using colored petri nets. The proposed model is based on a general approach which alarm messages are integrated with the operator’s commands. Of course, the model focuses on generating of alarms by substation resources. To verify the proposed model, a real data set of power system of Iran is used and to demonstrate the potential of the proposed model some scenarios about operator’ workload and alarm flooding are simulated.
In SCADA system, alarm clearing is one of the main duties of operators. When an alarm is raised in control center, the operator should clear it as soon as possible. However, the recent reports confirm the poor alarm clearing causes accidents in the SCADA system. As any operator mistake can increase the number of alarms and jeopardize the system reliability, alarms processing and decision-making for clearing them are a stressful and time-consuming for the SCADA operators. In a large and complex CI such as power system, when operators are overwhelmed by the system alarms, they may take wrong decisions and even ignore alarms. Alarm flooding, lots of operator’s workload and his/her fatigue as a result, are the main causes of operator’s mistake.
If generating of an alarm in a remote substation is denoted as an operational cycle in an SCADA system until clearing it by the operator in control center, the aim of this paper is modeling the operational cycle by using colored petri nets. The proposed model is based on a general approach which alarm messages are integrated with the operator’s commands. Of course, the model focuses on generating of alarms by substation resources. To verify the proposed model, a real data set of power system of Iran is used and to demonstrate the potential of the proposed model some scenarios about operator’ workload and alarm flooding are simulated.
Type of Study: Research |
Subject:
Paper
Received: 2018/09/15 | Accepted: 2019/09/2 | Published: 2020/09/14 | ePublished: 2020/09/14
Received: 2018/09/15 | Accepted: 2019/09/2 | Published: 2020/09/14 | ePublished: 2020/09/14
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