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Details of Grant 

EPSRC Reference: EP/M507155/1
Title: Upside
Principal Investigator: Peskir, Professor G
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Mathematics
Organisation: University of Manchester, The
Scheme: Technology Programme
Starts: 31 December 2014 Ends: 30 June 2016 Value (£): 47,463
EPSRC Research Topic Classifications:
Energy Storage Sustainable Energy Networks
EPSRC Industrial Sector Classifications:
Information Technologies Energy
Related Grants:
Panel History:  
Summary on Grant Application Form
Our research will have three parts. First we will perform state of the art statistical modelling of CO2 intensity in UK

electricity generation. This will provide powerful statistical representations of daily variation in the use of CO2 intensive

fuels (principally coal and gas), taking into account both seasonal and within-day fluctuations.

Second, we will develop a method to generate daily carbon intensity profile predictions (for both average level and

statistical variation).

Third, we will produce a control algorithm to generate UPS recharging schedules optimised for the lowest carbon intensity.

This will provide day-ahead schedules which aim to minimise the CO2 produced in recharging the UPS fleet, by taking into

account the abovementioned statistical models.

The above statistical models and generated control policies will also be published by Upside as part of their open source

approach, adding to the rich real-time UK grid data available to the public.
Key Findings
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Further Information:  
Organisation Website: http://www.man.ac.uk