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Projects: Projects for Investigator
Reference Number NIA_NGGD0011
Title Demand Scaling
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 PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics) 100%
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Project Contact
No email address given
Cadent Gas
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 October 2013
End Date 01 January 2014
Duration 5 months
Total Grant Value £183,731
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_NGGD0011
Objectives The aim of this project is to create a proof-of-concept off-peak demand model for below 7 bar networks, along with algorithms for scaling these demands to peak. In addition, a working prototype spreadsheet tool containing these models will also be produced. Both the demand model and the scaling model will use selected consumer data from DDS and produce output in the form of Scaling Factors, with one set representing validation day demand and a further set for 1: 20 peak demands. If successful this will enable delivery of a consistent, robust and transparent demand model tool capable of providing a method of extrapolating from a validation condition to the 1 in 20 peak six minute demand condition. This could potentially be further developed to extend the use of the tool and to implement the software within business systems, such as GBNA. Success of this project will be the development of a new peak demand model that is proven to be consistent and readily applicable to network models.
Abstract National Grid Gas Distribution plans its below 7 bar networks in accordance with industry guidance document IGE/GL/1, which requires that network analysis models are periodically validated against actual network performance. National Grid Policy T/PL/NP/16 and Management Procedure T/PM/NP/29 define the requirement in detail. Having confirmed the validity of the network model against actual network performance data it is then necessary to extrapolate the demand on the model from the level at the validation condition to the peak 1 in 20 six minute demand condition required for use in planning the network, as defined in IGE/GL/1. Over time a number of approaches to extrapolation have been applied, all of which can lead to an over or under estimate of the 1 in 20 peak six minute demand condition, potentially resulting in over or under investment in the network. This project therefore seeks to develop a more robust, transparent and intuitive method of extrapolating from a validation demand condition to the 1 in 20 peak six minute demand condition. This project seeks to develop a statistical demand methodology, based on learning from work carried out under a previous Innovation Funding Incentive (IFI) project, through use of a substantial quantity of actual consumer demand data collected, to provide improvements to the accuracy of network analysis. The method relies on training a statistical model against actual six minute meter point demand data logged during winter 2009/10 and winter 2010/11. The model is likely to rely on ‘day of the week’, ‘month of the year’ and Composite Weather Variable to assess what percentage of the peak 1 in 20 six minute demand conditionb occurred on the network validation day for each category of demand, thus enabling extrapolation to the peakdemand condition. The new demand model tool will require population with meter point data taken from the existing Demand Derivation System (DDS). The tool would be presented to the user via an interface, with the output likely to be a simple set of scaling factors to be applied to the demand data in the network model to give the 1 in 20 peak six minute demand condition.Note : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above
Publications (none)
Final Report (none)
Added to Database 09/08/18