Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 222222
Loughborough University

Centre for Renewable Energy Systems Technology (CREST)

Multi-scale Energy Systems

UML diagram of the features of an Object Oriented Bayesian Network for solar PV

Managing Risk and Uncertainty

This research aims to enable deeper understanding of energy outcomes at multiple scales whilst effectively managing inherent uncertainty and risk. With support from RCUK, we are working with a number of government agencies at national and local levels, along with industry partners to assess relative risk and impact of renewable energy technologies in comparison with alternative efficiency measures using defined metrics such as return on investment, CO2, fuel affordability, jobs, and local supply chain benefits.

Utilising various stochastic and probabilistic modelling methods such as Graphical Bayesian Analysis together with GIS, we are working towards the development of integrated multi-domain analytical environments for application across a range of domains.

Academics: Paul Rowley, Tom Betts, Ralph Gottschalg, Richard Blanchard

Researchers: Philip Leicester, Nick Doylend, Adam Thirkill, Esther Phiri

 

Top image: 

UML diagram of the features of an Object Oriented Bayesian Network for solar PV