TY - JOUR
T1 - Monitoring electrical systems data-network equipment by means of Fuzzy and Paraconsistent Annotated Logic
AU - Côrtes, Hyghor Miranda
AU - Santos, Paulo Eduardo
AU - da Silva Filho, João Inácio
PY - 2022/1
Y1 - 2022/1
N2 - The constant increase in the amount and complexity of information obtained from IT data network elements, for its correct monitoring and management, is a reality. The same happens to data networks in electrical systems that provide effective supervision and control of substations and hydroelectric plants. Contributing to this fact is the growing number of installations and new environments monitored by such data networks and the constant evolution of the technologies involved. This situation potentially leads to incomplete and/or contradictory data, issues that must be addressed in order to maintain a good level of monitoring and, consequently, management of these systems. In this paper, a prototype of an expert system is developed to monitor the equipment status of data networks in electrical systems. This expert system is capable of dealing with inconsistencies without trivialising the inferences. This work was developed in the context of the remote control of hydroelectric plants and substations at a Regional Operation Centre (ROC). The expert system is developed with algorithms defined upon a combination of Fuzzy logic and Paraconsistent Annotated Logic with Annotation of Two Values (PAL2v) in order to analyse uncertain signals and generate the operating conditions (faulty, normal, unstable or inconsistent/indeterminate) of the equipment that are identified as important for the remote control of hydroelectric plants and substations. A prototype of this expert system was installed on a virtualised server with CLP500 software (from the EFACEC manufacturer) that was applied to investigate scenarios consisting of a Regional (Brazilian) Operation Centre, with a Generic Substation and a Generic Hydroelectric Plant, representing a remote control environment.
AB - The constant increase in the amount and complexity of information obtained from IT data network elements, for its correct monitoring and management, is a reality. The same happens to data networks in electrical systems that provide effective supervision and control of substations and hydroelectric plants. Contributing to this fact is the growing number of installations and new environments monitored by such data networks and the constant evolution of the technologies involved. This situation potentially leads to incomplete and/or contradictory data, issues that must be addressed in order to maintain a good level of monitoring and, consequently, management of these systems. In this paper, a prototype of an expert system is developed to monitor the equipment status of data networks in electrical systems. This expert system is capable of dealing with inconsistencies without trivialising the inferences. This work was developed in the context of the remote control of hydroelectric plants and substations at a Regional Operation Centre (ROC). The expert system is developed with algorithms defined upon a combination of Fuzzy logic and Paraconsistent Annotated Logic with Annotation of Two Values (PAL2v) in order to analyse uncertain signals and generate the operating conditions (faulty, normal, unstable or inconsistent/indeterminate) of the equipment that are identified as important for the remote control of hydroelectric plants and substations. A prototype of this expert system was installed on a virtualised server with CLP500 software (from the EFACEC manufacturer) that was applied to investigate scenarios consisting of a Regional (Brazilian) Operation Centre, with a Generic Substation and a Generic Hydroelectric Plant, representing a remote control environment.
KW - Automation
KW - Data network monitoring
KW - Electrical system
KW - Fuzzy logic
KW - Paraconsistent Annotated Logic with Annotation of Two Values
KW - SNMP
UR - http://www.scopus.com/inward/record.url?scp=85114932001&partnerID=8YFLogxK
U2 - 10.1016/j.eswa.2021.115865
DO - 10.1016/j.eswa.2021.115865
M3 - Article
AN - SCOPUS:85114932001
SN - 0957-4174
VL - 187
JO - Expert Systems with Applications
JF - Expert Systems with Applications
M1 - 115865
ER -