Reading Climate Change Festival Week (9th -15th November 2020)

Reading Climate Festival is a week-long programme of free events to inspire action on climate change, curated by Reading Climate Action Network.

As part of Reading Climate Festival, Professors Tim Dixon and Lorraine Farrelly will be taking part in a Twitter Q&A session on Thursday 12 November, 13:00-15:00. Questions can be submitted on how Reading can become a sustainable city of the future by using the hashtag #Reading2050.

The University will also be hosting three evening sessions throughout the week where members of the public can quiz climate change experts on a wide range of topics. For more information, and to book a place, please click here. Dr Eugene Mohareb will be answering questions on his research in greenhouse gas mitigation from cities and urban influences on the food system.

The new Reading Climate Emergency Strategy to 2030 will also be launched during the Festival week.

A news item about the launch of the Reading 2050 book is now live.

Students, Staff and Residents are all welcome to attend.

Successful funding for Heritage Action Zone Project

Lorraine Farrelly and Sally Lloyd Evans at the University of Reading have been successful in securing funding for the government funded Heritage Action Zone project, a collaboration with Reading Borough Council https://www.reading.gov.uk/planning/reading-high-streets-heritage-action-zone/

This pilot study has proposed a series of art projects along Oxford Road, one project is to look at the high street and propose new ways to engage local communities in these spaces. Another project is to consider the shopfronts as a series of displays for work from local artists  (including the University staff and students).

This initiative links with the School of Architecture’s ambition to develop an urban room at Reading.

Postdoctoral Research Associate (PDRA) for Electricity Derived Transport Fuelling

We are looking for a Postdoctoral Research Associate (PDRA) for Electricity Derived Transport Fuelling.

Sustainable Heavy Duty Truck, Marine and Rail Transport (SMaRT)
An exciting opportunity to contribute to research into decarbonising heavy-duty transport, one of the most pressing yet uncertain challenges in mitigating Climate Change. We are looking for a post-doctoral research fellow for a 2 ½ year post to deliver research for the SMaRT project. Our role is to assess the power system impacts of producing electricity derived fuel, reflecting various motive power options, as well as to examine the implications for each technology’s potential.

Please see more details of the post and how to apply here: https://jobs.reading.ac.uk/displayjob.aspx?jobid=7271

 

Flexibility Reading Room on Seasonality

The Flexibility Reading Room was held on the 1st October 2020 and did not actually read anything on seasonality (partly because we could not find anything suitable.  If anyone out there has any suggestions, do let us know).  Instead we had four short presentations on the topic; one from Mikko Jalas on infrastructures, variations in demand and the ‘shadowy’ sides of these arrangements; one from Elizabeth Shove, who did a quick summary of what seem to be relevant ideas from Marcel Mauss’ work on seasonality amongst the Eskimos; Dale Southerton and Jen Whillans on looking for seasonal variations in UK time use data and Jacopo Torriti, taking a similar approach to energy and time use data.

We then went around the ‘room’ which was quite crowded – some 18 people, from a splendid range of different disciplines and countries. Hearing about which ideas caught the attention and sparked interest from each person in turn resulted in a powerful sense of potential: in different ways and from different angles topics of seasonality are here to stay.

There was so much going on here – as you will discover if you listen to the recording – that we will almost certainly have to return to this topic in the future.  In the meantime, welcome to autumn.

You can listen to the recording here:

 

 

 

 

 

KTP Research Associate in Artificial Intelligence for Healthy, Productive Indoor Environment

The University of Reading is currently looking for a Research Associate with expertise in artificial intelligence/machine learning for healthy productive indoor environment design and assessment collaborating with the industry in the built environment. This is a fixed two-year position.

Previous experience of applying AI and ML in the Built Environment (e.g., smart building, smart grid, smart city, energy etc) is particularly welcome.

Salary: £32,000 – £42,000 pa depending on qualifications and experience

The KTP Research Associate will ideally hold at least a 2.1 (or equivalent) in a Masters degree or higher (PhD) in Computer Science, Mathematics, or another quantitative field (engineering related) with a demonstrated understanding of AI and ML and strong interest to apply them into the real-world problems.

How to apply:  https://www.jobs.ac.uk/job/CBS528/ktp-associate-in-artificial-intelligence-for-healthy-productive-workplaces

Tim Dixon awarded Best Paper for Volume 11 JOSRE

Tim Dixon has been awarded best paper for Volume 11 Journal of Sustainable Real Estate (JOSRE) : Measuring the Social Sustainability of New Housing Development: A Critical Review of Assessment Methods.

The prize ($3000) was awarded by the American Real Estate Society (ARES) (https://www.aresnet.org/), which each year awards a number of manuscript prizes for best papers in key journals. The Journal of Sustainable Real Estate (which is an open access Routledge publication) is published annually.

The paper focuses on social sustainability. Social sustainability is a growing area of debate in the built environment, particularly in relation to housing. Homebuilders in the United Kingdom have responded to organizational and policy drivers by developing ex post assessment frameworks to measure the social sustainability of new housing development. The paper offers a critical perspective of these frameworks by: (1) examining the origins of the concept of social sustainability at the neighborhood level; (2) analyzing the critical challenges and research questions about social sustainability that the underlying methodologies raise; and, (3) how such frameworks might be improved and developed further.

The paper can be downloaded at: https://www.tandfonline.com/doi/abs/10.22300/1949-8276.11.1.16

Newcastle University Whole Energy Systems Webinar Series

Newcastle University Whole Energy Systems Interest Group (NUWIG) are pleased to invite you to their autumn webinar series, starting on the October 8th.

Thomas Morstyn on 8th October at 15:00-16:00
“OPEN: An Open-Source Python Platform for Developing Smart Local Energy System Applications”

Hannah Bloomfield on 22nd October at 11:00-12:00
“Quantifying the sensitivity of European power systems to climate variability and change”

Stephen Haben on 5th November at 11:00-12:00
“Load Forecasting for Low Voltage Distribution Systems”

Kyri Baker on 19th November at 15:30-16:30
“From Transmission to Thermostat: Integrated Building/Grid Operations”

Graeme Hawker on 3rd December at 11:00-12:00
“Drivers and Challenges for Multi-Energy System Analysis”

Register your interest by clicking this link:
https://forms.ncl.ac.uk/view.php?id=9349897

For further details contact:
David Greenwood at david.greenwood@newcastle.ac.uk
Matthew Deakin at matthew.deakin@newcastle.ac.uk.

 

Energy Networks Association – Flexibility Consultation 2020

In this response, CREDS outlines new opportunities in terms of non-DSO flexibility services, including the implications of introducing ‘core capacity’ and interfaces that allow non-DSO (distribution system operators) flexibility markets to flourish, and describes how differing distributed energy resources (DER) types should be subject to different baselining methodologies as opposed to a simple one-size fits all approach. In the context of residential flexibility, CREDS generally agrees with the position that engaging residential flexibility is critical. Further research linking the timing of activities to electricity demand will be key to any intervention aimed at increasing residential flexibility.

Schematic diagram showing the simple links between supply and demand in the existing energy system, and the complexity and flexibility of including aggregators, third parties and training platforms in the system.

Full details of the consultation: Energy Networks Association Flexibility Consultation 2020

Publication details

Torriti, J., Lo Piano, S., Lorincz, J.M., Ramirez-Mendiola, J.L., Smith, S.T. and Yunusov, T. 2020. Energy Networks Association – Flexibility Consultation 2020.

Using Machine Learning and Deep Learning for Energy Forecasting with MATLAB – free seminar

Using Machine Learning and Deep Learning for Energy Forecasting with MATLAB

29th September 2020 from 14:00-15:00 CEST

Overview
AI, or Artificial Intelligence, is powering a massive shift in technical organizations that expect to gain or strengthen their competitive advantage. AI workflows such as deep learning and machine learning are transforming industries with high impact; the power and utilities industries are not exceptional in this regard. The legacy power grid is adopting the concept of smart grid technology, where the role of AI is crucial in multiple aspects.  Grid analytics is one of the key focus areas of smart grid infrastructure, where load forecasting is highly pronounced. Forecasting the load on grid helps power and utility companies to plan their resources and effectively service consumer demands in a profitable way. Medium-term forecasting and long-term forecasting are a key focus of the energy production and utilities industry, as this helps to decide on multiple strategies such as generation planning and demand side management services.

The load on the grid depends on multiple external factors, making the data highly complex in nature. AI can be thought of as a tool to develop the forecast models for this complex data. At present, domain experts spend valuable efforts in cleaning data, searching for the right choice of predictive algorithms and fixing syntax of the code. Manual deployment of developed models is also a cumbersome process and additionally requires IT expertise.

In this webinar, you will learn:

  • How to handle large data
  • How to leverage domain expertise in the AI workflow using MATLAB
  • How to deploy algorithms seamlessly to enterprise scale solutions and integrating with a dashboard

About the Presenter
As an application engineer at MathWorks, Sebastian Bomberg supports customers in implementing artificial intelligence projects. For instance, he develops applications for energy forecasting, predictive maintenance and IoT in general. To this end, he uses techniques from machine learning and deep learning as well as big data algorithms and cloud computing. Sebastian Bomberg holds a Dipl.-Ing. degree in mechanical engineering from Technische Universität München, where he also worked as a researcher at the Thermo-Fluid Dynamics Group.

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