skip to content

Department of Computer Science and Technology

 

Energy and Environment Group (EEG)

The Energy and Environment Research Group applies computer science to address renewable energy integration, energy demand reduction, and the assessment and management of environmental impact (e.g. climate change, biodiversity loss, deforestation) from anthropogenic activities.

We operate in an interdisciplinary manner, collaborating with climate scientists, ecologists, engineers, lawyers, regulators, and economists, and conducting wide engagement with external partners to effect evidence-based outcomes.

Goal

Our primary goal is to have a measurable impact on tools and techniques for de-risking our future. To do so, we share recent advances at the intersection of computer science, energy, and the environment through seminars, workshops, and scientific publications. We also help form collaborations between group members to coordinate interdisciplinary initiatives across University departments. 

Membership

EEG members are, in the first instance, faculty members in the Department for Computer Science and Technology and their students. We also invite membership from Postdocs, PhDs, Lab Visitors and Master’s students primarily from other departments, as appropriate.

Seminars

A list of talks for the current term can be found below; talks from prior terms are linked to this page. Seminar details can also be found at Talks.cam. Recordings from the EEG seminar series are available to watch online. We thank the Institute of Computing for Climate Science for their sponsorship of this series.


Partners


Upcoming seminars

Easter term

  • 24May
    Anaïs Berkes - Department of Computer Science and Technology, University of Cambridge

    We address a problem that arises at the confluence of three recent trends: the popularity of storage-coupled photovoltaic (PV) systems amongst homeowners, the rapid proliferation of electric vehicles (EVs) with potential for bidirectional energy storage within PV-enabled single-family homes, and third, the surge in remote working accelerated by the Covid-19 pandemic. In this context, we explore the joint optimal sizing and operation of domestic homes while accounting for different degrees of remote working and the impact of home energy management system (HEMS) operation preferences. This task is complex due to the coupling between sizing and operation and the stochastic and non-stationary nature of solar generation, load, and EV drive cycles. We introduce SOPEVS (Sizing & Operation of PV and EV integrated Single-family homes), a novel framework formulated to tackle this multifaceted challenge. We use SOPEVS to investigate how commuting habits and choices in HEMS operation affect the sizing of domestic PV energy systems.

    Our findings reveal that homeowners who predominantly work from home and possess bidirectional EVs can potentially eliminate the need for separate home storage systems, thereby substantially reducing overall system costs. We also find that configuring a HEMS to maximise charging through solar energy can achieve savings of up to 80% on total system expenditure (excluding the cost of EV), depending on the desired level of grid independence and the preferred State of Charge (SOC) of EV at the time of departure.

    Bio:

    Anaïs Berkes is a first-year PhD Student and Gates Scholar in the Department of Computer Science and Technology at the University of Cambridge.

  • 31May
    Andres Arcia-Moret, AMD - former researcher at UCAM

    Abstract not available

  • 07Jun
    Frank Feng, Independent Researcher

    Abstract not available

  • 14Jun
    Speaker to be confirmed

    Abstract not available

  • 21Jun
    Loïc Lannelongue, Heart and Lungs Research Institute, DPHPC, University of Cambridge

    Bio:

    Dr Loïc Lannelongue is a Research Associate in Biomedical Data Science in the Heart and Lung Research Institute at the University of Cambridge, UK, and the Cambridge-Baker Systems Genomics Initiative. He leads the Green Algorithms project, an initiative promoting more environmentally sustainable computational science. His research interests also include radiogenomics, i.e. combining medical imaging and genetic information with machine learning to better understand and treat cardiovascular diseases. He is a Software Sustainability Institute Fellow, a Post-doctoral Associate at Jesus College, Cambridge, and an Associate Fellow of the Higher Education Academy.

  • 28Jun
    Speaker to be confirmed

    Abstract not available

  • 05Jul
    Anke Weidlich from Albert-Ludwigs-Universität Freiburg

    Abstract not available

  • 12Jul
    Speaker to be confirmed

    Abstract not available

  • 19Jul
    Speaker to be confirmed

    Abstract not available

  • 26Jul
    Speaker to be confirmed

    Abstract not available

Michaelmas term