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Mobile robot for automated identification of failures in HV substations

Reference Number
NIA_NGTO006
Title
Mobile robot for automated identification of failures in HV substations
Status
Completed
Energy Categories
Other Cross-Cutting Technologies or Research
Other Power and Storage Technologies(Electricity transmission and distribution)
Research Types
Applied Research and Development
Science and Technology Fields
PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics)
ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering)
UKERC Cross Cutting Characterisation
Not Cross-cutting
Principal Investigator
Project Contact
National Grid Electricity Transmission
Award Type
Network Innovation Allowance
Funding Source
Ofgem
Start Date
01 October 2016
End Date
31 July 2021
Duration
ENA months
Total Grant Value
£550,000
Industrial Sectors
Power
Region
London
Programme
Network Innovation Allowance
Investigators
Principal Investigator
Project Contact, National Grid Electricity Transmission
Industrial Collaborator
Project Contact, National Grid plc
Web Site
Objectives
The project will seek to develop an autonomous device that can take regular thermographic / RF measurements of substation assets (including within risk management zones) and use the information collected by these measurements to identify patterns of unusual behavior in the substation asset. The scope of the work will be as follows:Task 1. Data collation: The first part of classifying normal behaviour is to collate data from multiple sources on the high risk assets. Data from previous tests will be made available for use and a fixed monitoring system (with appropriate sensors) will be installed at a substation. This fixed monitoring system will allow the measurement of data in a range of weather conditions and under a range of load conditions. It will therefore provide specific data that can be used in the data analytics task. New data will be also be collected as required in experiments in the high voltage (HV) lab at the University of Manchester.Task 2. Data processing: Different statistical analysis tools will be applied to interpret the data collated in task 1 in order to create metrics. From this analysis, models of normal asset behaviour will be produced. This task will investigate methods for predicting if the measurements are within the normal range. If not in range, it is assumed that the asset is at a higher risk of failure / investigations should take place. Task 3. Comparison of available localisation systems: A number of systems exist to accurately provide location data for mobile robotic platforms. The standard method of differential global positioning system (GPS) and magnetometers may not work correctly in HV substations, due to the metalwork reflections and the noisy RF environment. Trials of different localisation systems will be carried out to understand the likelihood of receiving accurate location data. The trial will also include buying a robotic platform, attaching measuring devices and operating the platform in a high voltage substation.Task 4. Providing information to the operator: This task will evaluate ways to present intuitive information to the operator of the measurement system [the human – machine interface (HMI)
Abstract
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Added to Database
09/11/22