Activities

Active Projects

Predict 4 Resilience

Predict 4 Resilience (P4R) forecasts how many faults may occur on electricity distribution networks up to 5 days ahead of adverse weather events, enabling networks to pre-emptively allocate engineers, mobile generation, and other resources to the right locations. By bringing forward travel time to faults requiring an onsite presence, P4R helps restore power supply sooner, creating a more resilient network with reduced disruption for customers and lower CO₂ emissions.

Partners: SP Energy Networks (lead), Scottish & Southern Electricity Networks, University of Glasgow, Sia

Funder: Ofgem Strategic Innovation Fund (Discovery/Alpha/Beta phases)

Mortgage Financed Emissions

This project assesses how accurately UK lenders can estimate residential mortgage “financed emissions” under the PCAF framework, using smart meter data linked to EPC records from over 13,000 households from the Smart Energy Research Lab. We’ve found that commonly used PCAF approaches based on EPCs produce large errors with little distinction between data quality tiers, while simple data‑driven models using the same inputs perform far better. The findings demonstrate that modelling choices are as important as data availability and support reforms to PCAF, including quantitative quality metrics and the use of limited consumption data to improve emissions reporting.

Partners: NatWest Group

Funders: EPSRC Impact Accelerator Account and NatWest Group

Border Target Operating Model (BTOM) Trade Forecasting

Working with Defra, we’re developing advanced time‑series modelling to evaluate and monitor the impacts of sanitary and phytosanitary (SPS) regimes under the Border Target Operating Model (BTOM). Using large‑scale trade and border data from Defra, HMRC and related systems, we are developing statistical and machine‑learning methods for anomaly detection, forecasting and hindcasting of import flows, with full uncertainty quantification. The work delivers open‑source, production‑ready tools in the bulktrends R package, alongside validated methods, stakeholder‑driven use cases and decision‑support analytics to help policymakers and operators identify emerging risks, assess policy impacts and improve biosecurity and trade system performance.

Partners: Department for Environment, Food & Rural Affairs

Funders: EPSRC Postdoctoral Pathways (EP/Z534985/1) and Defra

Using Demand Flexing to Transform Indoor Farms into Renewable Energy Assets

We’re exploring how indoor horticulture can support both food production and the transition to a renewable‑dominated electricity system by acting as a flexible energy demand. This work investigates how shifting lighting schedules in controlled‑environment farms to align with renewable energy availability can reduce costs and support grid stability, while maintaining crop yield and quality. By combining demand‑flexing strategies with advanced plant photobiology—including testing genetically engineered “timeless” plants designed to respond uniformly to variable light—the project aims to make indoor farms viable, flexible assets in smart energy systems, delivering commercial, environmental and societal benefits.

Partners: Intelligent Growth Solutions (IGS), UK Urban Agritech, CN Seeds, Donald Danforth Plant Science Center

Funder: BBSCR (BB/Z514469/1)

Selected Past Projects

HEFTcom2024

The latest in a series of global energy forecasting competitions! The purpose of this competition was to develop state-of-the-art forecasting and energy trading techniques to accelerate the global transition to net-zero carbon emission footprint.

The competition was organised by Jethro Browell and the IEEE Power and Energy Society Working Group on Energy Forecasting and Analytics. It was sponsored by Ørsted, one of the world’s largest renewable energy companies, and rebase.energy.

Read about the findings in this IJF paper and in the presentation below.

EPSRC Innovation Fellowship: System‑wide probabilistic energy forecasting

This project developed probabilistic forecasting methods to support reliable and cost‑effective operation of power systems with high levels of renewable generation. It created new statistical frameworks to jointly forecast weather‑dependent electricity demand and generation, explicitly quantifying uncertainty and interdependence across the system under different meteorological conditions. The work also delivered decision‑support tools that translate complex probabilistic forecasts into actionable insights for network operators, generators and suppliers, helping reduce operating costs, manage risk, and maintain reliability as the UK transitions to a low‑carbon energy system.

Funder: EPSRC (EP/R023484/1, EP/R023484/2)

Organisations

IEA Wind Task 51

IEA Wind Task 51, Forecasting for the Weather‑Driven Energy System, is an international research and collaboration initiative under the IEA Wind Technology Collaboration Programme that aims to improve the accuracy, value, and practical use of weather and power forecasts in energy systems with high shares of wind and solar generation. It brings together meteorologists, researchers, forecast providers, and energy system users to advance forecasting from minute‑scale to seasonal timescales, address uncertainty and extreme events, and translate meteorological information into decision‑relevant insights for operations, markets, and planning. The task is organised around improving atmospheric modelling, power and uncertainty forecasting, and the effective use of forecasts, while promoting standards, best practices, and knowledge sharing to support the reliable and cost‑effective integration of weather‑dependent renewable energy.

Editorial

As well as performing peer-reviews for a range of funding bodies and journals, I have served on several editorial boards as Editor of Sustainable Energy, Grids and Networks and Board Member for Renewable and Sustainable Energy Reviews, and Advisor to the F1000 Research Energy Gateway, and Programme Committee for the Probabilistic Methods Applied to Power Systems conference.

Other service

I am also an active member of the following organisations:

International Institute of Forecasters

I regularly organise sessions at the International Symposium on Forecasting, review for the International Journal of Forecasting, and have served on the committee for the Institute’s UK Chapter.

Royal Statisticsl Society

I’m a Fellow and regular at the Glasgow local group and RSS Conference.

KE Hub for Mathematical Sciences

I represent the UofG School of Mathematics and Statistics in this national group that supports KE in our discipline. KE Hub webpage