India UK

Integrated Urban Model for Built Environment Energy Research (iNUMBER)

Improving Data Granularity

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Improving Data Granularity
Leads: Rajan Rawal (CEPT), Krithi Ramamritham (IITB), Kathryn Janda (UCL)

WP3 enriches the “data poor” contexts through three different modes of high resolution data capture non-intrusive, intensive, and extensive to provide a ‘real world’ context for the urban model’s data analytics. Partners include Zero Energy Developed (ZED) homes and Pilio Group.

Non-intrusive methods of data capture will work toward deploying LiDAR and GIS technology to generate data pertaining to building characteristics over large area. The aim is to develop detailed model which will help to predict future energy demand reduction in the case of various technology deployment, city design alternatives and integration of rooftop solar PV potential. This WP will also identify opportunities which will help to operate buildings in mixed mode comfort operation. Subject to appropriate agreements and licensing, using unmanned aerial vehicles (UAVs) with visible photography and infrared thermography information will be gathered on 3D form of the built environment, building materials, fenestration patterns and heat flows. These data will allow iNUMBER to model and anticipate the benefits of changes to future stock in terms of window placement and shading, natural ventilation opportunities, and solar access, as well as provide opportunities for retrofitting the existing stock with photovoltaic and/or exterior shading.
This will focus on intensive data collection within residential buildings with an objective to capture thermal comfort conditions and energy consumption associated with the use of home appliances and occupant behaviour. This project aims to work in 50-60 multi-family, multi-storey apartment units, covering the three most populated climatic zones in India and different economic cross sections of society. It will gather detailed information using best available techniques, building on ICT tools developed by CEPT and IITB under previous and current grants from DST and Ministry of New and Renewable Energy’s MNRE) Initiative to Promote Habitat Energy Efficiency (I-PHEE) (e.g. CEPT’s DELTA-T).
Extensive data collection will use lower tech participatory tools and methods for gathering energy and water consumption data for homes and municipal energy services. iNUMBER work in this area builds on two EPSRC projects on time of use and energy management: (1) Dr Grunewald’s Measuring and Evaluating Time and Energy use Relationships (METER, EP/M024652/1) which is based on SEEMs, and (2) a project focused on energy strategies in the retail sector (WICKED, EP/L024357/1). Smart  Energy  and  Environmental  Monitors  (SEEMs)  are based on  Android  smartphones +  a  peripheral measurement device. SEEMs were developed and patented through WICKED and an EPSRC Impact Acceleration Account held by Dr Layberry.  The use of SEEMs in India will allow (1) gathering of granular data about technologies, premises, and electricity use in homes and ULBs and (2) exploration of opportunities for demand-response and demand side management, at 10 to 20 times lower cost than conventional monitors. As part of this work package, a trial of new peripheral devices and software dedicated to measuring and displaying the supply  and consumption of water and its energy implications will be developed. It is anticipated that SEEMs and associated new India specific software will be trialled in approximate 10 sites (homes and ULBs) and scaled up to 100 over the course of the project.

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