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NIA_NGET0085
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| Reference Number | NIA_NGET0085 | |
| Title | UK Regional Wind: Extreme behaviour and predictability | |
| Status | Completed | |
| Energy Categories | Renewable Energy Sources(Wind Energy) 50%; Other Power and Storage Technologies(Electricity transmission and distribution) 50%; |
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| Research Types | Applied Research and Development 100% | |
| Science and Technology Fields | PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics) 25%; ENVIRONMENTAL SCIENCES (Earth Systems and Environmental Sciences) 75%; |
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| UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
| Principal Investigator |
Project Contact No email address given National Grid Electricity Transmission |
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| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 August 2013 | |
| End Date | 01 August 2015 | |
| Duration | 24 months | |
| Total Grant Value | £253,300 | |
| Industrial Sectors | Power | |
| Region | London | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , National Grid Electricity Transmission (100.000%) |
| Web Site | http://www.smarternetworks.org/project/NIA_NGET0085 |
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| Objectives | The objectives of the project are based on five work packages; this includes WP 1 - Obtaining observational data and robustness testing of "UK wide wind" results WP 2 - Predictability: statistical WP 3 - Predictability: case studies WP 4 - "Worst case" scenarios at sub-regional level WP 5 - Dissemination and identification of further research needs The success criteria of this project will be the submission of an academic report providing recommendations to National Grid of improving the process of predicting extreme weather events and understanding the trend once the start of an event is detected. | |
| Abstract | Wind generation plays an increasing role in the energy-mix of Great Britain. Wind is, however, intermittent and, in many cases, difficult to predict. This create significant costs for National Grid in terms of system management and reserve setting. With the increasing levels of renewable wind generation (22 GW expected by 2020) the cost of these errors could be expected to increase substantially. The ability to improve the accuracy of wind-power forecasts and also have confidence in the forecast error will lead to significant reductions in the number of forecasting errors and the associated costs. Research Three classes of wind events have been identified as crucial for reducing the cost (and increasing the security) of power-system management and operation, this includes Rapid changes in wind-speed affecting power output (ramping)Persistent low wind producing low power output (low wind conditions)Very-high wind events (exceeding wind-turbine safety cut-out)This project proposes to investigate the winds properties over spatial scales between Note : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above |
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| Publications | (none) |
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| Final Report | (none) |
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| Added to Database | 17/12/18 | |
