Projects
Projects: Projects for Investigator |
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| Reference Number | NIA_NGGT0014 | |
| Title | Daily gas demand forecasting | |
| 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 National Grid Gas Transmission |
|
| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 May 2011 | |
| End Date | 01 September 2014 | |
| Duration | 40 months | |
| Total Grant Value | £375,000 | |
| Industrial Sectors | Technical Consultancy | |
| Region | London | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , National Grid Gas Transmission (100.000%) |
| Web Site | http://www.smarternetworks.org/project/NIA_NGGT0014 |
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| Objectives | The Objective is to develop new methods for forecasting the daily gas demand from the National Transmission System. Project success would be the delivery of a new method to improve the demand forecasts that are provided to the market and to be used in operational decision-making. | |
| Abstract | National Grid Transmission forecasts the national gas demand for each day over a range of timescales, from a week ahead to within the day, and publishes forecasts to the gas market. This project investigates using local predictor techniques, which automatically identify similar days in history to the forecast day, to make a top-down forecast of total demand. This is a different approach to the fixed regression formula currently used, and initial tests have indicated a significant increase in accuracy over the current models. The Method is as follows: Develop initial day-ahead model and test as live trial Improve day-ahead model and further test as live trial. Report on model Continue support for live trials Refine local search for day ahead model and test as live trial Develop initial models for 5 to 2 days ahead, and test as live trial Enable implementation Further improve forecasts for 5 to 2 and day ahead, through emerging drivers and alternative modelsNote : 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 | |
