History of changes to: Part2: Building Management linking Energy Demand, Distributed Conversion and Storage using Dynamic Modelling and a Pervasive Sensor Infrastructure
Date Action Change(s) User
Nov. 27, 2023, 2:13 p.m. Added 35 {"external_links": []}
Nov. 20, 2023, 2:03 p.m. Added 35 {"external_links": []}
Nov. 13, 2023, 1:34 p.m. Added 35 {"external_links": []}
Nov. 6, 2023, 1:31 p.m. Added 35 {"external_links": []}
Aug. 14, 2023, 1:31 p.m. Added 35 {"external_links": []}
Aug. 7, 2023, 1:32 p.m. Added 35 {"external_links": []}
July 31, 2023, 1:34 p.m. Added 35 {"external_links": []}
July 24, 2023, 1:36 p.m. Added 35 {"external_links": []}
July 17, 2023, 1:35 p.m. Added 35 {"external_links": []}
July 10, 2023, 1:26 p.m. Added 35 {"external_links": []}
July 3, 2023, 1:27 p.m. Added 35 {"external_links": []}
June 26, 2023, 1:26 p.m. Added 35 {"external_links": []}
June 19, 2023, 1:27 p.m. Added 35 {"external_links": []}
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June 5, 2023, 1:34 p.m. Added 35 {"external_links": []}
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May 22, 2023, 1:29 p.m. Added 35 {"external_links": []}
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April 24, 2023, 1:35 p.m. Added 35 {"external_links": []}
April 17, 2023, 1:28 p.m. Added 35 {"external_links": []}
April 10, 2023, 1:25 p.m. Added 35 {"external_links": []}
April 3, 2023, 1:26 p.m. Added 35 {"external_links": []}
Jan. 28, 2023, 11:09 a.m. Created 43 [{"model": "core.projectfund", "pk": 29782, "fields": {"project": 7001, "organisation": 2, "amount": 606679, "start_date": "2010-09-29", "end_date": "2014-03-28", "raw_data": 49316}}]
Jan. 28, 2023, 10:52 a.m. Added 35 {"external_links": []}
April 11, 2022, 3:48 a.m. Created 43 [{"model": "core.projectfund", "pk": 21916, "fields": {"project": 7001, "organisation": 2, "amount": 606679, "start_date": "2010-09-29", "end_date": "2014-03-28", "raw_data": 32335}}]
April 11, 2022, 3:48 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 82705, "fields": {"project": 7001, "organisation": 169, "role": "PP_ORG"}}]
April 11, 2022, 3:48 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 82704, "fields": {"project": 7001, "organisation": 312, "role": "PP_ORG"}}]
April 11, 2022, 3:48 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 82703, "fields": {"project": 7001, "organisation": 463, "role": "PP_ORG"}}]
April 11, 2022, 3:48 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 82702, "fields": {"project": 7001, "organisation": 529, "role": "PP_ORG"}}]
April 11, 2022, 3:48 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 82701, "fields": {"project": 7001, "organisation": 42, "role": "LEAD_ORG"}}]
April 11, 2022, 3:48 a.m. Created 40 [{"model": "core.projectperson", "pk": 51261, "fields": {"project": 7001, "person": 9799, "role": "COI_PER"}}]
April 11, 2022, 3:48 a.m. Created 40 [{"model": "core.projectperson", "pk": 51260, "fields": {"project": 7001, "person": 9800, "role": "COI_PER"}}]
April 11, 2022, 3:48 a.m. Created 40 [{"model": "core.projectperson", "pk": 51259, "fields": {"project": 7001, "person": 9819, "role": "COI_PER"}}]
April 11, 2022, 3:48 a.m. Created 40 [{"model": "core.projectperson", "pk": 51258, "fields": {"project": 7001, "person": 2788, "role": "PI_PER"}}]
April 11, 2022, 1:48 a.m. Updated 35 {"title": ["", "Part2: Building Management linking Energy Demand, Distributed Conversion and Storage using Dynamic Modelling and a Pervasive Sensor Infrastructure"], "description": ["", "\nCommercial and residential buildings are responsible for a large proportion of carbon dioxide emissions both in the UK and globally. In 2000, 40% of the UK's total non-transport energy use was for space heating, and space heating and hot water accounted for 82% of domestic and 64% of commercial use of energy. Energy demand reduction by commercial buildings can therefore significantly contribute towards achieving the UK's broader energy consumption goals. In contrast to proposals that directly propose behaviour change interventions for the users of commercial office space, this project proposes to address a key deficit in our understanding of the quantity and nature of energy consumption in commercial settings with a view to developing novel holistic solutions including the optimisation of shared resource usage and energy storage facilities. The proposed research plans to tackle this challenge by designing and developing a sensing infrastructure that consists of networked physical (e.g. presence sensors, power consumption sensors) and virtual sensors (e.g. calendar and room booking sensors, application usage sensors) that will provide fine-grained information about how much energy is being used, for what purpose and by whom. By applying techniques from knowledge engineering, activity recognition and machine learning (e.g. Bayesian classifiers) the first stage of our approach will derive higher-level information (e.g. a meeting taking place in a particular room) and will link usage patterns (such as spikes in power consumption) to real-world activities and workflows (e.g. printing off a series of reports for a meeting). In the second stage, this information will be used to parameterise building models used in building management to more accurately predict energy usage and to optimise (decentralised) energy consumption, generation and storage. Based on these models, we will develop a decision support tool that visualises the collected data as well as the expected impact of energy saving strategies such as organisational changes and policies or the rescheduling of activities. This will enable decision makers to identify where energy is being wasted (e.g. several meeting rooms being heated despite only a few meetings being scheduled) and to formulate and evaluate strategies to reduce energy consumption. The data collected also benefits other building systems using new and emerging ISO standards for inter-operability of appliances and systems in buildings using Internet Protocols. In addition, the data will enable a better understanding of the way the building is used and how heat wasted. Through a combination of physical and virtual sensors a more accurate measurement of thermal comfort of the building's occupants will be established and thus assist in resolving ever occurring complaints and potential conflicts associated with the diverse needs for occupant comfort in buildings which also results in unnecessary overheating.\n\n"], "extra_text": ["", "\n\nPotential Impact:\nThe project is highly relevant to the government of the UK in the context of achieving targets related to energy use and reduction of CO2 emissions on a national, European and international level. According to data published by the UK government, in 2000 40% of the UK's total non-transport energy use was for space heating, and space heating and hot water accounted for 82% of domestic and 64% of commercial use of energy. The research planned for this project will contribute towards a considerably improved understanding of how this energy is used in commercial buildings, thereby paving the way for strategies, policies and other measures to reduce energy usage. The data gathered through the long-term studies will directly benefit other researchers both in academia (e.g. through the IBPSA and SESG) and in industry (e.g. through BRE, KTN MBE and Industry and Parliament Trust), and provide a sound basis for further research and simulations. The impact for the industrial partners is as follows: a) BRE: The novel and validated dynamic model of the building environment and its occupants behaviour is highly valuable to BRE in their quest to improve energy modelling methodologies used in the building regulations, such SBEM and SAP. This can feed new knowledge into existing government funded programmes to improve SBEM and SAP and also provide new tools for use in other BRE Trust funded programmes relating to SBEM development. b) Arup are already engaged in collaborative research with the BRE Centre to research and develop new design tools to assess the feasibility of DC powered buildings which become less reliant on the ever increasing cost of AC grid power supplies. Arup is also keen to establish the potential for CHP and Trigeneration systems being researched in the SWAN Institute and how they can be effectively integrated within Arup's DC building concepts. Again the validated models developed in the project will enable the PhD project to assess the commercial and practical feasibility of these solutions. c) Siemens and Philips Resarch will be significant contributors to the successful exploitation of the newly developed models and data sets. The models can be adapted to test advanced building energy management solutions where physical and virtual sensors could be incorporated with their existing solutions. The project through BRE will engage with the buildings industry through a series of events sponsored by the BRE Trust publications leading edge and best practice in open protocol advanced building energy management and electricity load management solutions. In addition to a highly active publications plan in internationally recognised conferences, journals and industrial best practice publications, the project partners will set up a dedicated project website. Furthermore, a collaborative research relationship will be established between the research groups at Newcastle and Glasgow. These groups have 'complimentary' skills and expertise from different areas in energy related research and Computer Science: Newcastle provides expertise in energy storage and generation as well as sensor networks, pervasive technology and human-computer interaction; ESRU/BRE Centre in Strathclyde is a recognised leader in building simulation, management and control. The BRE Centre has already engaged with BRE Ventures to establish an exploitation route for IPR arising from the research. This could involve licensing data and models to the building industry corporate sector or the set-up of spin-out groups within BRE to sell consultancy services or even a new spin-out company. The project will also actively engage standardisation bodies, (e.g. BRE, IEEE, EN and ISO) and use results and data obtained within the project to drive the development of standards in the area of interoperable sensor networks for energy monitoring, e.g. with respect to protocols, notations and anonymisation of personal data.\n\n\n"], "status": ["", "Closed"]}
April 11, 2022, 1:48 a.m. Added 35 {"external_links": [25430]}
April 11, 2022, 1:48 a.m. Created 35 [{"model": "core.project", "pk": 7001, "fields": {"owner": null, "is_locked": false, "coped_id": "fdfb1531-9e5c-4426-8e87-a531f7cd0b0b", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 32320, "created": "2022-04-11T01:44:28.177Z", "modified": "2022-04-11T01:44:28.177Z", "external_links": []}}]