Projects
Projects: Projects for Investigator |
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| Reference Number | NIA_UKPN0059 | |
| Title | Miles better fault location | |
| Status | Completed | |
| Energy Categories | Other Power and Storage Technologies(Electricity transmission and distribution) 100%; | |
| Research Types | Applied Research and Development 100% | |
| Science and Technology Fields | PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 30%; ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 70%; |
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| UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
| Principal Investigator |
Project Contact No email address given UK Power Networks |
|
| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 May 2020 | |
| End Date | 01 May 2023 | |
| Duration | ENA months | |
| Total Grant Value | £1,838,000 | |
| Industrial Sectors | Power | |
| Region | London | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , UK Power Networks (100.000%) |
| Industrial Collaborator | Project Contact , UK Power Networks (0.000%) |
|
| Web Site | https://smarter.energynetworks.org/projects/NIA_UKPN0059 |
|
| Objectives | MILES is a system which aims to give a location of a fault along a feeder. It uses low voltage power quality sensors, voltage drop location algorithms and cloud computing to detect, locate and classify permanent and transient faults. The system aims to provide sufficient pre-fault information to enable proactive asset intervention to prevent the fault from happening. The project will consider: firstly a theoretical test using UK Power Networks (UKPN) specific network topology data; and secondly a field test using QinetiQs low voltage LineWatch sensors. MILES will then be benchmarked against alternative fault location solutions to determine the best value approach for UKPN to adopt across its network.Once the technology is proven, the project will delve into the integration with existing UKPN systems such as PowerOn, following successful results from before. This latter half of the project aims to address the issues of integration with an active network that can reconfigure itself. 1. Desk study of estimated efficacy of algorithm on UKPN network2. Installation of sensors3. Deployment of platform4. Live-trial at selected sites5. Report of platforms results We aim to determine the following:1. Permanent fault location accuracy and efficiency 2. Transient fault detection accuracy and efficiency | |
| Abstract | MILES is a system which aims to give a location of a fault along a feeder. It uses low voltage power quality sensors, voltage drop location algorithms and cloud computing to detect, locate and classify permanent and transient faults. | |
| Data | No related datasets |
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| Projects | No related projects |
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| Publications | No related publications |
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| Added to Database | 02/11/22 | |
