It is well known how power disturbance events typically result in expensive failures of electronics equipping both several susceptible types of equipment and entire critical segments of production processes. A power quality (PQ) monitoring activity is, therefore, crucial to identify causes and possible remedies in order to avoid even huge economical concern for industrial and commercial customers. An Internet of Things (IoT) based solution has been already implemented which provides smart device hardware, a cloud-based database and a Web site development for monitoring alarms from key equipment of electric distribution systems. The smart devices have been integrated with a low-cost PQ monitoring chip. A cheap but effective PQ monitoring network can be thus created by installing a smart device in each LV switchboard. Data recorded by each unit is collected and stored in a cloud-based database that can be analyzed and reported for subsequent analyses.

Distributed Power Quality monitoring in customer's electrical distribution system

Prudenzi A.;Fioravanti A.;Ciancetta F.
2019-01-01

Abstract

It is well known how power disturbance events typically result in expensive failures of electronics equipping both several susceptible types of equipment and entire critical segments of production processes. A power quality (PQ) monitoring activity is, therefore, crucial to identify causes and possible remedies in order to avoid even huge economical concern for industrial and commercial customers. An Internet of Things (IoT) based solution has been already implemented which provides smart device hardware, a cloud-based database and a Web site development for monitoring alarms from key equipment of electric distribution systems. The smart devices have been integrated with a low-cost PQ monitoring chip. A cheap but effective PQ monitoring network can be thus created by installing a smart device in each LV switchboard. Data recorded by each unit is collected and stored in a cloud-based database that can be analyzed and reported for subsequent analyses.
2019
978-1-7281-0653-3
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/142077
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