METER addresses a fundamental research question: "What is the temporal relationship between electricity consumption and household activities?". To date this relationship is still poorly understood. METER will address this gap by collecting electricity consumption data in parallel with time-use information using adapted smart phone technology. A detailed understanding of 'what electricity is used for', especially during peak demand periods, is important in addressing emerging system balancing challenges and to develop appropriate policy frameworks and business models leading to the cost effective integration of low-carbon generation. At present electricity is supplied based on a 'predict and provide' paradigm - so long as we can forecast 'how much' electricity is required at any one time, the fleet of mostly fossil fuel based plants can be scheduled to deliver. Little knowledge about the end-uses of energy has been required for this approach. With low carbon sources, such as nuclear, solar and wind, more flexibility may be required from the demand side. Understanding the end use activities supported by electricity becomes more important when seeking to reduce or shift the timing of consumption. Studies attempting to measure electricity use at the appliance level have so far been limited in their scale by the cost and complexity of instrumentation. The absence of statistically robust consumption data has been noted as limiting the UK's world leading research in this area. METER develops a new approach to collect electricity consumption in parallel with time-use information. Smart phone technology, developed by colleagues at Oxford, will be deployed to measure electricity consumption at 1 second resolution and ask participants about the activities they undertake at critical times of the day. The use of smart phones allows this process to be performed at unprecedentedly low costs, such that over 2000 households can be included in the study. This scale is important, because electricity uses are highly diverse and only a sufficiently large sample allows to develop statistically significant evidence for researchers and policy makers. The concurrent collection of time-use and electricity consumption can improve the accuracy of time-use research and provide new insights into the use and timing of electricity consumption and its relationship with household activities. The data and the analytical tools developed by METER will provide much needed insights into the timing of electricity uses, which can underpin a wide range of future research priorities. Among them are emerging energy system balancing challenges and broader policy challenges relying on statistically robust information about the relationship between energy use, demographics, lifestyles and their transitions over time. Findings and insights from METER trials will become publicly available as part of a public outreach campaign, including interactive online tools to explore how Britain uses its electricity and what the public can do to support the transition towards a lower carbon future.

Sustainable urbanisation requires the provision of secure energy for health and comfort. Key to planning sustainable energy services is an understanding of how energy demand changes over time and space and tools to help plan for its reduction. iNUMBER is a research programme to develop: 1. A building stock and municipal service energy model to help plan a secure energy supply for urban populations to be thermally comfortable and healthy (via the provision of clean water and sanitation). The model will estimate total and disaggregated (in use, time and space) energy demand. Plus, assess the impacts of different mechanisms (e.g. shading, occupant behaviour and insulation) to reduce energy demand and the capacity to provide locally generated clean energy. 2. Linked new and existing data sets. Developing models is relatively simple, the challenge is acquiring the data to input and test the validity of models. iNUMBER tackles this challenge head on by developing state of the art data collection and analytic methods to overcome this challenge in a range of scenarios with different data availability. 3.Tools to help support the urban energy management process iNUMBER supports Indian municipalities and local partners to develop a data-driven intelligent urban model for built environment energy research and municipal planning. It supports India's deep decarbonisation pathway by mapping current and future energy demand reduction opportunities in the built environment. It will diagnose urban energy problems, test solutions, verify progress, and improve policy decisions utilising state of the art monitoring, data science and analytics. iNUMBER primarily focuses around meeting the India/UK Newton research topic "Integration of information, communication and renewable energy technologies at building, community, and city level interventions." and will also meet elements of the other two areas of the call "peak demand reduction" by contributing new high resolution data and "city and community technologies" by providing guidance to urban planners iNUMBER will: -Undertake innovative research into: urban data collection (e.g. laser ranging combined with IR and visible images from unmanned vehicles), big data analytics, and innovative modelling. -Promote the economic development of and welfare of developing countries, as required by Newton funding, by helping India to transition to a smart sustainable energy system which is critical to economic development. -Engage users of different types. Our initial project partners include urban local bodies, energy software developers, energy meter hardware suppliers, residential construction companies, architectural firms, and user experience experts. Beyond these immediate partners, we will coordinate and collaborate with other research groups in the field, engage with policymakers, and benefit the public. -Leverage Newton and DST funding by ~£1m, with support from host universities and project partners who will provide data, test sites, equipment, and provide sector expertise. -Demonstrate usable solutions: online energy information systems; benchmarking backed up by large data sets; low-tech "smart-er" retrofits for electricity meters and sub-meters; reduction strategies for energy and the energy-water nexus tailored to cities of different shapes and sizes. -Build a collaborative India/UK interdisciplinary research project: This proposal builds on the strengths of India in Information Technology and the strengths of the UK in energy epidemiology to build a best with the best collaboration. The team includes leading academics from engineering, data science, information technology, energy analysis, architecture, building science, urban science, urban planning, energy management from leading institutions in India and the UK. All work packages will be delivered via teams from both UK and India and many work packages involve interdisciplinary collaboration.

Innovative energy saving measures in non-domestic buildings- e.g., enhanced information due to sensors and meters; better management due to controls; and more efficient lights and HVAC equipment -could save 18 MtCO2 by 2020 and 86 MtCO2 by 2050, depending upon the rate at which the measures can be deployed. The deployment of energy efficiency technologies and management techniques depends on the physical conditions present in the existing building stock, as well as the ownership characteristics and management practices in each building. That is, adopting better technologies and practices depends on what fits, where, and for whom. The Working with Infrastructure, Creation of Knowledge, and Energy strategies Deployment (WICKED) project uses a segmented socio-technical approach to work with and learn from different configurations of building energy data and ownership in the existing UK non-domestic stock. The project develops and implements the concepts of "data rich" and "data poor" to identify and map energy-related technical and organizational infrastructure, as well as barriers to and opportunities for change. Top-down analytics on large anonymized non-domestic data sets from energy provider partners will be combined with middle-out case studies of landlord and tenant fleets and bottom-up empirical work in SME buildings, focused predominantly on the retail sector. The project will use this information to engage with and co-create appropriate knowledge for different types and scales of stakeholders: owners, occupiers, landlords, tenants, and energy providers. Through this knowledge and interaction, the project enables adoption of energy efficiency technologies and management techniques appropriate for each stakeholder segment. Based on our findings, our project will develop an action toolbox oriented towards the different needs of different market segments. Indicative innovative products to emerge from this work are: online energy advisor backed up by large data sets, "smart-er" technologies to retrofit legacy gas and electric meters, new forms of leasing agreements, and effective energy management procedures tailored for different stakeholder groups. Analyzing this complex landscape and its many opportunities and challenges requires a broad based, problem-directed and interdisciplinary approach. The University of Oxford academic team brings together expertise in social and technical aspects of energy demand (Dr. Kathryn Janda and Dr. Russell Layberry), information technologies (Dr. David Wallom), mathematics (Professor Peter Grindrod) engineering (Dr. Malcolm McCulloch), and law (Professor Susan Bright). Non-academic partners for this project are energy suppliers, retailers, local and national government stakeholders, landowners, tenants, and energy advice companies. These partners will leverage the EPSRC funding requested by the provision of data, management practices, lease agreements, test sites, and equipment.