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Projects: Projects for Investigator
Reference Number NIA_NGN_066
Title Off-Take Reform / Alarm & Demand Management
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) 50%;
PHYSICAL SCIENCES AND MATHEMATICS (Statistics and Operational Research) 50%;
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Project Contact
No email address given
Northern Gas Networks
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 January 2015
End Date 01 June 2017
Duration 29 months
Total Grant Value £39,627
Industrial Sectors Technical Consultancy
Region Yorkshire & Humberside
Programme Network Innovation Allowance
Investigators Principal Investigator Project Contact , Northern Gas Networks (100.000%)
Web Site http://www.smarternetworks.org/project/NIA_NGN_066
Objectives Deliver a statement on data supplied by xoserve regarding suitability for use on holiday and weekend factors. Provide an independent review on accuracy of the data with recommendations on suitability of models to determine these factors. Provide techniques they have used for evaluating existing profile data sets and determine if it is accurate for use in profiling demand. Provide an clear assessment of alarm management data and provide evidence of statistical patterns, should these exist in the data, along with commentary. Generate a modelling technique that can accurately profile a pressure controlled offtake and be specific to each individual site. Produce a control algorithm to support accurate control of offtake regulators Produce a more accurate demand profile enabling an improved security of supply and better informed supply/demand balancing Better informed investment strategies in GD2 if analysis done alarm data indentifies that certain assets are generating errors Improved management of pressure controlled offtakes Improve performance of UK Gas Balancing - Primary System Capacity - improved within day performance resulting in reduced penalties to shippers.
Abstract The information used by the Northern Gas Networks to determine the impact of weekends and holidays on the demand forecasting process, do not accurately reflect the actual demand profile customers actually portray. Northern Gas Networks needs to research actual demand patterns over these periods to develop specific algorithms to more accurately predict consumer demand. Pressure and operational system alarms create significant reporting issues for networks to ensure compliance. The large volumes of data generated from alarm activity, has the potential to reduce costs on asset investigation and provide input into asset health strategy. Networks do not have the capacity to research this data for patterns in operational performance that could be used to predict future performance. Current modelling techniques on pressure controlled off-takes cannot accurately predict behaviour with significant human interventions required to maintain supply balance. Better utilisation of available data has the potential to provide a systemised model to increase the accuracy of the offtakes modelling process, thereby reducing the number of corrective actions needed to maintain an accurate supply balance and minimising the errors in capacity profile submissions to the National Grid. Resubmitting off take notifications can result in inefficient use of capacity. This inefficiency impacts across industry stakeholders and on customer costs. Precise control of capacity request from the NTS system will improve the efficiency of the entire gas system by making better use allocated capacity. By research the inaccuracies within the control process should minimise the human interactions and improve capacity strategies 1. Undertake mathematical and statistical analysis on temperature and demand data and use analytical modelling techniques to analyse the data. 2. Undertake mathematical and statistical analysis techniques to historical alarm activities to analyse data to determine if any patterns exist within the data. 3. Analyse seven years of historical diurnal demand data from 23 NGN offtakes to determine if any patterns exist within the data and if asset behaviour affects these patterns. 4. Employee a postNote : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above
Publications (none)
Final Report (none)
Added to Database 17/09/18