EPSRC Reference: |
GR/R92271/01 |
Title: |
FARADAY FAST TRACK PROPOSAL: Real-time Modelling of Nonlinear Data-Streams (REMIND) |
Principal Investigator: |
Smith, Professor LA |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Statistics |
Organisation: |
London School of Economics & Pol Sci |
Scheme: |
Faraday (PreFEC) |
Starts: |
01 March 2003 |
Ends: |
28 February 2005 |
Value (£): |
85,827
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EPSRC Research Topic Classifications: |
Information & Knowledge Mgmt |
Non-linear Systems Mathematics |
Statistics & Appl. Probability |
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EPSRC Industrial Sector Classifications: |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
The Nonlinear Signals in Industry project focuses on developing mathematical models with combined advances in nonlinear dynamics and Bayesian methods of estimation, while being sufficiently robust to deploy in the industrial contexts of grid frequency monitoring and the monitoring of rotating machinery. In short, we aim for Real-timE Modelling of Nonlinear Data-streams (REMIND), while tracking sources of uncertainty both in the data and from the model structure. In the context of grid frequency, we will develop structural models (based on estimated generation and its composition, estimated grid inertia, type of demand, and so on) and contrast/combine such models with previously proven purely data based nonlinear models. The mathematical aims are to develop methods for useful real-time parameter estimation within the context of (1) data-streams (too much to store) and (2) model inadequacy (the mathematical structure of the class of models under consideration does not include a correct parameter set consistent with the data). This requires modelling model failure. At various times throughout the project our models will be applied in real-time trials by our industrial partners.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.lse.ac.uk |