Past sessions are available to view online

• OPEN: An Open-Source Python Platform for Developing Smart Local Energy System Applications Thomas Morstyn
• Quantifying the sensitivity of European Power Systems to Climate Variability and Change Hannah Bloomfield 
• Load Forcasting for Low Voltage Distribution Systems Stephen Haben 
• From Transmission to Thermostat: Integrated Building/Grid Operations Kyri Baker
• Drivers and Challenges for Multi-Energy System Analysis Graeme Hawker
• Co-innovating the development of distribution systems to enable decarbonisation Pádraig Lyons
• The future of cooling and its links to the Sustainable Development Goals Nicole Miranda 
• Open energy system models: overview, community, legal contect, emerging infrastructure Robbie Morrison 
• Decarbonising heat and shipping Olivia Carpenter-Lomax 
• Model-based decision-support for the energy transition with Calliope Stefan Pfenninger 
• Smart Energy Network Demonstrators and Digital Twins Ian Lloyd
• A decision tool for real-time operation of public sector multi-energy systems Sathsara Abeysinghe 
• CESI Operational model: Introduction and instances of application Hamid Hosseini and Adib Allaham
• Operating low-inertia grids: challenges and solutions Dr Luis Badesa

(13:00 - 15:00)

The first session in the series featured speakers from Academia and Industry discussing their career journeys, their challenges and successes from leaving their home countries through to establishing careers in UK Energy. The recorded session is available to view for a limited time:

Speakers from Session 1:

Professsor Jihong Wang - Head of Power and Control Systems Research Laboratory, Warwick University

Professor Zhongdong Wong – Pro Vice Chancellor and Executive Dean, University of Exeter

Dr Panos Papadopolous – Lecturer at Strathclyde University

Dr Richard Oduro – Research Fellow, Leeds University

Dr John Nwobu – Research Engineer, Offshore Renewable Energy Catapult

Pavlos Trichakis – Baringa Partners

Speakers: Jethro Browell  and Thomas Alexander (University of Strathclyde)

Energy FORecasting and analytics for Market-led Multi-vector networks

Project Summary

EnFORMM will develop forecasting tools for efficient operation of multi-vector energy networks and markets. New methods based on data science and machine learning will be developed to predict electricity and gas market prices and volumes, and to quantify risk. A key aspect of EnFORMM is the explicit consideration of interdependencies between energy vectors. This technology will enhance new and existing business models, such as distributed resource aggregators and heat/energy-as-a-serve, in support of the transition to a zero-carbon energy system. EnFORMM is promoting excellence in UK energy research by supporting outstanding Early Career Researchers at the University of Strathclyde. 

Further information and project partners

Speaker: Yuankai Bian (Bath University)

Challenges for the changing system inertia and implications to frequency response market design

(14:45 - 15:45)

The session is available to view

Speakers: Adriano Sciacovelli (University of Birmingham), Hossein Ameli (Imperial College), Alejandro Gallego Schmid (Manchester University)

Project Summary

The overarching aim of this project is to develop fundamental understanding of the role and impact of thermal energy storage (TES) technologies in future UK low carbon energy networks. The focus of this research will be on advanced TES: latent heat TES based on phase change materials (PCMs) and reversible reaction based thermochemical storage (TST). We will investigate the role, environmental impacts and value of TES in future heat and electricity networks, facilitating TES technological development, business models and inform key decision makers.

Further information on the project is available.

(14:00 - 15:00)

Speaker: Panos Papadopoulos (University of Strathclyde)

The session is available to view.

Project Summary

The ever increasing integration of variable output renewable energy sources (mainly wind and solar) as well as various other power electronic interfaced devices (e.g. electric vehicles, HVDC interconnectors, potentially battery storage, heat pumps, etc.) to achieve decarbonisation targets, significantly increases the uncertainty and complexity in the dynamic behaviour of electrical power systems. Machine learning has shown great potential in dealing with complex nonlinear systems in various domains. This project envisions bringing together the artificial intelligence and power engineering research communities to work on the very computationally demanding and complex problem of representing the power system dynamic behaviour.

Further information on the project is available.

This session is now available to view. Please use passcode:$cjzw5j5

Speaker: Professor Kerstin Eder (Bristol University)

Abstract:

Energy efficiency is now a major, if not the major, constraint in electronic systems engineering. Significant progress has been made in low power hardware design for several decades. The potential for savings is now far greater at the higher levels of abstraction in the system stack. The greatest savings are expected from energy consumption-aware software. Promoting energy efficiency to a first class software design goal is therefore an urgent research challenge.

Designing software for energy efficiency requires visibility of energy consumption from the hardware, where the energy is consumed, all the way through to the programs that ultimately control what the hardware does.

This visibility is termed energy transparency. Energy transparency enables a deeper understanding of how algorithms and coding impact on the energy consumption of a computation when executed on hardware. It is a key prerequisite for informed design space exploration and helps system designers to find the optimal trade-off between performance, accuracy, security and energy consumption of a computation.

In this seminar I will outline recent research advances that will give "more power" to software developers. We will investigate why software is key to energy efficient computing, what energy transparency is, how to monitor and measure the energy consumed by software, how to model energy consumption at different abstraction levels, how data affects the energy consumption of a computation, and how to statically estimate the energy consumed by software.

Bio:

Kerstin Eder is Professor of Computer Science and heads the Trustworthy Systems Laboratory (http://www.bristol.ac.uk/tsl) at the University of Bristol, UK. She also leads the research theme on Verification and Validation for Safety in Robots at the Bristol Robotics Lab. Her research is focused on specification, verification and analysis techniques that allow engineers to design a system and to verify or explore its behaviour in terms of functional correctness, security, performance and energy efficiency. Kerstin has gained extensive experience of verifying complex microelectronic designs while working with leading semiconductor design and Electronic Design Automation companies. In her research she seeks novel techniques and fundamental theoretical contributions to achieve solutions that make a difference in practice. Kerstin is a Royal Academy of Engineering ‘Excellence in Engineering’ prize winner. She holds a PhD in Computational Logic, an MSc in Artificial Intelligence and an MEng in Informatics.

This session is available to view, please use passcode: wF8@8C?m

Speaker: Kumar Biswajit Debnath (Heriot- Watt University)

Project Summary

South Asian countries such as India, Nepal and Bhutan are currently developing plans for increasing renewable energy penetration. However, other rapidly developing countries, such as Bangladesh, appear to be moving towards a fossil fuel-based model of development. Recent policy change in India has opened the avenue towards regional energy collaboration between Bangladesh, India, Nepal and Bhutan. The objective of this research is to explore the potential of electricity import from India, Nepal and Bhutan from renewables to aid the decarbonisation of Bangladesh’s rapidly accelerating electricity sector.

Further information on the project is available.

Speaker: Xin Zhang (Cranfield University)

This session is available to view, please use passcode: R5@Kskd1

Project Summary

The project will investigate the electricity network infrastructure for the electrification of airports with electric aircrafts (EAs) and electric vehicles (EVs). The project aims to include electrified aviation into a whole energy systems approach. An electricity network model will be developed for airports, by considering temporal power consumption, and charging requirements of EAs and EVs. Electricity network operating strategies will be studied with electric charging schemes, and to explore airport energy networks that interact with power girds. A feasibility study will be conducted to investigate demand side response through ‘airport to grid’ using aggregated EAs and EVs.

Further information on the project is available.

Speaker: Fei Teng (Imperial College, London)

This session is available to view, please use passcode: T9@ZV8CQ 

Project Summary

Recent advances in data analytics of energy system highlight the need to collect large volume of data, which causes concerns over privacy and security. Existing protection schemes, such as encryption, can not address the privacy concerns over the lifetime of the data, as evidenced by the data breach of British Airways. This project aims to explore and expand a new concept of differential privacy, recently developed in data science, into the energy system and develop a novel consumer-centric privacy-preserving mechanism that provides tailored protection for consumer-chosen sensitive information, while minimising the utility loss of the data.

Further information is available on the project.

Speaker: Camilla Thomson and James Robertson (Edinburgh University)

The recording of the webinar is available to view, please use passcode: Mum57aw@

Project Summary

There is some evidence that hybrid heating systems - heat pumps coupled with conventional technologies - can achieve significant carbon reductions when actively-controlled. There is a need, however, to better understand the interdependencies between this hybrid heating and the wider energy system of different vectors at different scales. Also, the consequential impacts of hybrid heating on network constraints and regional, time-varying, marginal carbon emissions needs to be identified. This project addresses these by soft-linking dispatch models across scales and vectors with carbon analysis to examine the opportunities and costs of emissions-led dispatch of hybrid heating.

Further information on the project is available.