Projects: Projects for Investigator |
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Reference Number | NIA_NGGD0026 | |
Title | Demand Allocation | |
Status | Completed | |
Energy Categories | Fossil Fuels: Oil Gas and Coal(Oil and Gas, Refining, transport and storage of oil and gas) 100%; | |
Research Types | Applied Research and Development 100% | |
Science and Technology Fields | ENGINEERING AND TECHNOLOGY (Mechanical, Aeronautical and Manufacturing Engineering) 100% | |
UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
Principal Investigator |
Project Contact No email address given Cadent Gas |
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Award Type | Network Innovation Allowance | |
Funding Source | Ofgem | |
Start Date | 01 February 2014 | |
End Date | 01 February 2015 | |
Duration | 12 months | |
Total Grant Value | £437,000 | |
Industrial Sectors | Technical Consultancy | |
Region | London | |
Programme | Network Innovation Allowance | |
Investigators | Principal Investigator | Project Contact , Cadent Gas (100.000%) |
Web Site | http://www.smarternetworks.org/project/NIA_NGGD0026 |
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Objectives | The aim of this project is to deliver a tested and approved prototype database and application to undertake data conflation, demand classification and spatial allocation of the demand within the network model and also report on the steps necessary to implement the system as business as usual. Success of this project will be the development of a new prototype database, application and process that is proven to be consistent and readily applicable to network models and has a positive effect in reducing any security of supply risk and also reduces the level of intervention required. | |
Abstract | National Grid Gas Distribution plans its below 7 bar networks in accordance with industry guidance document IGE/GL/1. The Graphics Based Network Analysis (GBNA) and Demand Derivation System (DDS) are the primary systems utilized in the Network Analysis element of the overall planning process. Key inputs to the GBNA and DDS systems are customer Meter Point Reference Number (MPRN) data, Standard Industrial Classification (SIC) codes and the network location of the demand - node. Current processes to maintain and manage this data are labour intensive and require significant training with the inherent risk of inconsistency of application which has the potential for security of supply and financial impacts. This project therefore seeks to develop a more robust, transparent and repeatable method of classifying and allocating the demand within the network model. This project seeks to develop work carried out under a previous Innovation Funding Incentive (IFI) project, through the innovative use of a combination of socio-economic, Ordnance Survey and customer demand data to better classify and allocate the demand within the network model.Note : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above | |
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 | 09/08/18 |