BSEE The measure of sustainability


The Chancellor is reportedly planning a green industrial revolution to reskill the economy for a net zero future – and among the key areas of focus is likely to be green buildings, including those in industrial and commercial settings.


analytics is climate change and the government’s net zero commitment, for businesses and public sector organisations, taking control of energy delivers an immediate and clear financial gain alongside the environmental benefit. At Energy Assets, we are helping businesses to embrace digitalisation in energy metering, monitoring and analytics to crunch vast amounts of consumption data to take control of energy performance in buildings and reduce their carbon footprint. To date, one of the biggest challenges facing energy managers has been making sense of the sheer volume of half-hourly consumption data delivered automatically by advanced meters. Now though, through energy monitoring portals and the application of artificial intelligence (AI) tools, managers can cut through this information overload to bring clarity where there was fog and automated action where there was human interpretation.


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hile the context for advanced energy metering,


monitoring and intuitive data


Performance monitoring and analytics is available through web portals such as WebAnalyser, which enables managers to create customised reports linked to half- hourly data delivered by gas, electricity and water meters. This includes the ability to set alarms that will flag deviation from defined consumption parameters, rank and compare site efficiency and carbon performance vs benchmarks over defined periods, model the impact of renewables on carbon emissions and filter building reporting by footprint area.


These alerts can be linked to consumption profiles to flag up performance that is over or under a given threshold and interfaced with KPIs to monitor, for example, energy usage per square meter, with results automatically emailed to managers to communicate ranking and any issues. All of which can be delivered via a customisable dashboard with an ability to dive deep into data down to an individual meter point. WebAnalyser can also be used in sub-metering settings, enabling building owners to apportion precise costs for energy to tenanted occupiers, rather than applying blunt consumption formulae.


FEATURE


Digitalisation is also ushering in a new era of artificial intelligence capable of modelling data to drive optimal energy efficiency. For example, our AI data analytics platform – AMR DNA - is enabling complex, multisite organisations, such as retailers, local authorities and universities to analyse years of half hourly consumption data and identify patterns of energy waste that it would take an army of analysts years to find.


By David Sing, group managing director (Assets), Energy Assets


In the case of one local authority, it took just 15 minutes to identify waste valued at £25,000 using this methodology. In another project, the Central England Co-operative generated a 206% return on investment by identifying and eradicating energy waste and implementing evidence-based efficiency strategies.


The core value of this AI system is its ability to assimilate meter data into a performance model and measure this profile against key criteria to identify event exceptions, which could be as simple as leaving lighting on overnight or, more critically, failing to adapt heating schedules to a change to British Summer Time. Over time, the AI platform ‘learns’ what best performance looks like for each building and produces a ‘to-do’ list to optimise efficiency.


It is by combining automated meter reading with advanced monitoring and AI that energy managers can spot the trends and actions that will inform the best ways to save energy, because self-evidently the only way to accurately understand energy consumption and building efficiency is to look at data historically and apply it to models for the future. With all these tools in their armoury, organisations are in better shape than ever before to bear down on energy costs and contribute positively to the wider climate challenge.


At the same time, these increasingly accurate datasets can help contribute to a better understanding of the wider energy network capacity requirements as the country moves towards greater electrification and a low carbon economy. Understanding what is needed to support investment in infrastructure such as EV charging networks, demand side management, ground source heat pumps, peaking plant supply, renewables and battery storage is key in assessing the need for network reinforcement. More than ever in the future, metering and monitoring, coupled with AI and data analytics, will be the measure of our success in meeting our energy efficiency and sustainability goals.


A Case in Point: Merton Council ­ Why We Chose AI to Cut Energy Waste www.energyassets.co.uk/amrdna


The London borough of Merton identified energy waste valued at £25,000 within 15 minutes of employing a new artificial intelligence tool.


Using consumption data for council-run schools, algorithms applied by AMR DNA, an Energy Assets service, quickly flagged unnecessary energy use outside normal operating hours. The cost of energy waste was estimated at £25,000. Now the council is applying the technology across its real estate portfolio, not only to prevent energy waste, but also to leverage continuous data analytics to ensure each building management system ‘learns’ what best energy performance looks like.


“We have been collecting consumption data for many years through automated meter reading, and it has been very useful in identifying the root cause of specific energy-related problems,” said Richard Neil of Merton Council. “We understood the value inherent in the data but analysing the entire portfolio in near real- time would have needed an army of


analysts. Now we can accomplish this and more through AMR DNA.”


The building management industry faces the huge challenge of making best use of existing resources, including data. The approach Merton has taken shows it is possible to embrace these challenges to help meet climate change commitments, George Catto, AMR DNA Client Services Director, commented: “Over half of all London boroughs have now declared a climate change emergency and they, like local authorities all around the country, will likely face challenges around reducing waste energy. AI is set to play a key role in developing the data-driven actions needed to optimise energy consumption in buildings and to help councils move towards carbon neutral operations.” AMR DNA, which is powered by kWIQly architecture, uses AI-driven processes to interrogate energy data, find patterns of energy waste often hiding in plain sight and then provide tailored recommendations. Thereafter, AI tracks the impact of changes, provides an audit


24 BUILDING SERVICES & ENVIRONMENTAL ENGINEER JULY 2020


trail of projects, monitors day to day consumption and automatically flags corrective actions that need to be taken. And because analysis is continuous, the best consumption profile for each building is progressively ‘learned’.


Said Richard Neil: “In the case of the schools, not only were we able quickly to identify sites using gas outside of school time, we were also automatically shown which of our sites we needed to focus on first to get the biggest results and use our resources most effectively.”


Energy Assets is one of Britain’s leading independent metering services, asset management and utility network construction companies, working with utility suppliers, developers, contractors and industrial and commercial end-users to provide a broad spectrum of expert multi- utility metering and energy-related services. The Group also enables customers to collect and analyse energy consumption data and provides a suite of control technologies to help drive energy efficiency and carbon reduction.


Read the latest at: www.bsee.co.uk


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