How are you using data to improve your energy efficiency?

How are you using data to improve your energy efficiency?

As we head towards winter, our attention will inevitably focus even more on energy efficiency…and how to bear down on gas and electricity costs.

October is traditionally a month for awareness days and events that provide hints and tips to help optimise energy consumption, mostly focused on households. As we know, though, industrial and commercial (I&C) organisations also face significant cost pressures for energy, so we asked Dave Sing, Managing Director, Energy Assets Metering & Data, for his advice on driving efficiencies.

Here’s what he had to say:

“Government support for I&C sectors is to be welcomed, but I would urge all businesses and public sector organisations to take a fundamental look at how they are monitoring and reporting their energy usage. There are lots of digital tools available here and now to help managers bear down on consumption – the question is where best to invest time and resources to create maximum value.

“For me, at a basic level, this means focusing on energy metering, consumption monitoring and setting up automatic alerts for unusual spikes in usage. At another, it means investigating advanced technologies, such as machine learning and artificial intelligence that can help to drive out waste.   

“Getting all these systems working in harmony could potentially be very beneficial in optimising efficiency and bearing down on cost.”

In practical terms, this means:

•    Ensuring that half hourly consumption data is captured in granular detail via automated meter reading systems.

•    Monitoring and analysing consumption data through an advanced AM&T portal, such as WebAnalyser, which provides sophisticated analytics down to individual meters and enables automated alerts to be set to spot and address unusual usage spikes quickly.

•   Investigating how new generation digital tools such as AMR DNA can apply machine learning and artificial intelligence to progressively learn what best performance looks like to drive our costly energy waste.

Optimising the value of consumption data

Says Dave Sing: “AMR DNA assimilates half-hourly meter data and interprets it in the context of building operations, taking account of external factors, like weather and occupancy levels. This creates ‘fingerprints’ of consumption – and, using AI, will create a checklist of actions that will progressively lead to optimal building energy efficiency. And because the system is smart, it can learn to ignore outcomes that are irrelevant, mistaken or due to bad data. 

“Crunching data on this scale manually would require an army of analysts – but with machine learning, this can be achieved in quick time, and create a direct line to actions based on real world data and comparative building analysis. 

“The message here is to collect, monitor and analyse data. Even a basic approach can yield surprising results, because often it’s a question of spotting improvement opportunities hiding in plain sight, whether that’s equipment running needlessly or heating controls incorrectly set.”

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