Department of Meteorology, University of Reading
EnergyMet-Research



Current Projects


PRIMAVERA - high-resolution global climate modelling for energy applications

Paula Gonzalez and David Brayshaw

The Horizon 2020 PRIMAVERA project is a major international research programme developing a new generation of advanced high-resolution global climate models, capable of simulating and predicting regional climate with unprecedented fidelity for the benefit of governments, business and society. As part of this international research team (involving 19 institutions across Europe), the energy-meterology group are developing process-based understanding of how climate variability and change will impact on the energy sector.


ECEM - Climate Services for Energy

Emma Suckling and David Brayshaw

The European Climatic Energy Mixes (ECEM) project is an EU Copernicus Climate Change Services Project (C3S) seeking to develop a proof-of-concept model – or demonstrator - for the provision of climate services for energy applications. Working closely with sectoral stakeholders, its purpose is to enable the energy industry and policy makers to assess how well energy supply will meet demand in Europe over different time horizons, focusing on the role climate has on energy supply and demand. The energy-meteorology group is developing a series 'case studies' to demonstrate the value and use of this service.


Future climate future energy

Hannah Bloomfield, David Brayshaw, Len Shaffrey, Phil Coker, Hazel Thornton (UK Met Office), Jason Lowe (UK Met Office)

A NERC funded PhD project (CASE partnered with the UK Met Office) which aims to understand the effects of increased weather dependent renewable generation on national and international power systems. A key goal is to understand the multiple sources of meteorological sensitivity of the power system (e.g., demand response to temperature, wind-power, solar) and how weather events effect the power system as a whole through these pathways. Meteorological reanalyses (e.g., NASA MERRA) and state-of-the-art climate model data will be used to create a long baseline to simulate the impacts of weather on the UK and European power systems both now and into the future. Power system behavior will be understood using both a mixture of models from a classical "load duration curve" approach to simplified integrated power system "dispatch" models.​

An introduction to the impact of inter-annual variability on the GB power system is available here.


Clustering effects of major offshore wind developments

Daniel Drew, Janet Barlow, Omduth Coceal, Phil Coker and David Brayshaw

The expansion in offshore wind generation coming with the round 3 projects is bringing particular uncertainty for strategic and operational planning of the power system. Wind farms of the scale now planned influence the lower atmosphere sufficiently to impact the performance of adjacent farms, therefore the power generation characteristics of a cluster of wind farms (such as that planned for Dogger Bank) are largely unknown. This project aims to determine the power characteristics of a cluster of large offshore wind farms for a range of meteorological conditions, taking into account the wake effects of the individual turbines and the shadow effect of neighbouring farms.

This project is funded by National Grid.


Solar PV Forecasting

Daniel Drew, Janet Barlow and Phil Coker

A recent, dramatic increase in installed photovoltaic generation is now impacting the electricity demand profile. This influence has been challenging to predict and is currently leading to significant demand forecast errors.  The total solar capacity in Great Britain is  now in excess of 9.3 GW, and is forecast to rise to 15.7 GW by 2020.  Owing to the size of the individual installations (the largest  solar farm in the UK is just 48 MW) all of this capacity is embedded within the distribution networks.

The purpose of this project is to

  • derive datasets and specific knowledge of characteristics of solar PV generation in terms of variability, ramping and persistence, and the joint characteistics of how the solar resource interacts with the wind resource.
  • develop new models for converting solar irradiance into generated solar PV power.
  • improve short term solar generation forecasts

This project is funded by National Grid.


Climate and energy balancing: variability, mechanisms, predictability and impacts

Hazel Thornton (Met Office), Brian Hoskins, David Brayshaw and Adam Scaife (Met Office)

A PhD project, funded by the Met Office to investigate the influence of weather and atmospheric circulation on energy extremes and their predictability. The weather is known to play an important role in the management of the energy system, as demand and wind power generation are strongly influenced by atmospheric conditions. This PhD aims to quantify how both temperature and the driving weather pattern affect demand and wind power generation, to help understand the climatological risk of extreme demand periods and the availability of wind power during peak demand conditions. The predictability of key weather types on the monthly to seasonal timescale will also be explored.


Subseasonal predictability for energy

David Livings, Andrew Charlton-Perez, Steve Woolnough, Nick Klingaman, David Brayshaw

This project explores new opportunities to exploit subseasonal predictability and forecasting in the energy sector.


RE-SAT

Colin McKinnon, Jon Blower, Alan Yates, Ben Lloyd-Hughes, Neil Parley, Barbara Percy, Maria Noguer, David Brayshaw

RE-SAT: Renewable Energy Spatial Tool. Informing the deployment of renewable energy in Small Islands Development States using space data.


Forecasting weather impacts on the UK telecommunication network

Alan Halford, David Brayshaw, Stefan Smith

An EngD project joint funded by the EPSRC and the BT group with the aim of understanding the effects of weather on the UK telecommunication network to minimise weather related impacts. The telecommunication network as with other infrastructure are exposed to the weather and can be damaged by adverse conditions. Establishing statistical relationships between weather and fault numbers allows future fault numbers to be predicted using numerical weather prediction techniques. With the knowledge of future fault numbers, network management decisions can be optimised.


Climate changing renewable power outputs

Daniel Hdidouan (Imperial College London), Iain Staffell (Imperial College London), David Brayshaw, Rob Gross (Imperial College London).

A NERC funded PhD project (via the Science and Solutions for a Changing Planet, SSCP, DTP) based at Imperial College. The research aims to develop a framework to value the potential impact climate change may have on the European and North African power system. The framework focuses on two key aspects of climate-energy interaction at the power system scale: energy generation from wind and solar resources, and power system performance due to temperature (hot and cold extremes). Meteorological reanalyses datasets will be used with CMIP5 simulations and simulations (see Hdidouan and Staffell, 2017) and then coupled with a virtual wind/solar farm model to calculate capacity factors. These then form the inputs to a techno-economic model which analyses the impact of climate forcing on the levelised cost of energy from renewables.



Completed Projects