Title :
Outage management through AMR systems using an intelligent data filter
Author :
Sridharan, Krishna ; Schulz, Noel N.
Author_Institution :
Dept. of Electr. & Comput. Eng., Michigan Technol. Univ., Houghton, MI, USA
fDate :
10/1/2001 12:00:00 AM
Abstract :
Automatic meter reading (AMR) is the remote collection of consumption data from customers´ utility meters over telecommunication, radio, power-line and other links. Electric utilities are exploring the usage of AMR data for outage management for distribution systems. Signals from automated meters can provide additional information in the outage detection and determination processes as well as restoration phases of outage management. However due to its low quality, AMR outage data cannot be fed directly into outage management systems. This paper details the development of an intelligent information filter for automated metering systems. The filter prevents false outage notifications in addition to improving the quality of outage data. The nature of wireless communication in the AMR system introduces uncertainty issues in the query process. This uncertainty has been modeled using probabilistic and fuzzy engineering techniques. The filter has also been tested using historical outage data
Keywords :
automatic meter reading; data acquisition; fuzzy set theory; power consumption; power distribution faults; probability; AMR outage data; AMR systems; automated metering systems; automated meters; automatic meter reading; distribution systems; false outage notifications; fuzzy engineering techniques; historical outage data; intelligent data filter; intelligent information filter; low quality; outage data quality improvement; outage detection; outage determination processes; outage management; outage management systems; probabilistic engineering techniques; query process; remote consumption data collection; restoration phases; uncertainty issues; Automatic meter reading; Information filtering; Information filters; Intelligent systems; Phase detection; Power industry; Power system management; Power system restoration; Signal processing; Uncertainty;
Journal_Title :
Power Delivery, IEEE Transactions on