Energy Assets, one of Britain’s leading multi-utility networks, metering services and control companies, has launched a tactical tool to help industrial and commercial organisations identify energy waste that could potentially be costing them millions of pounds each year.
The analytical tool, developed to complement the company’s AMRdna service, powered by kWIQly, crunches half-hourly metered gas and electricity data to measure actual performance against what is verified to be the best possible consumption profile. This allows multi-site operators to see energy waste issues as soon as they emerge.
“Energy waste results from things as simple as not adjusting building heating or cooling systems to take account of changes in Daylight Saving Time, outside weather conditions and leaving lighting on overnight,” says George Catto, Client Services Director at AMRdna. “Our algorithm uses detailed consumption data to ‘learn’ what optimal performance should look like within individual buildings and across portfolios – and when exceptions occur, for example when equipment is left on accidentally, the system flags a deviation.”
Energy managers have historically used automatic monitoring and targeting systems to benchmark performance, but this does not offer true insight into optimal energy performance, only variation over manually set metrics. AMRdna’s software automatically remodels energy parameters on a daily basis, using half hourly gas and electricity data to spot unusual patterns of consumption.
“When it comes to energy efficiency, energy managers have exhausted most of the easy wins, such as LED lighting, and now what they need is a simple, fast and remote way of identifying energy waste hidden within their portfolio,” says George. AMRdna provides this information through automatic reporting or interactive web pages.
The insight provided by AMRdna is now being augmented by Energy Assets through the company’s Lynkswitch system, which provides energy managers with the ability to remotely control electrical loads, including switching off electrical loads should an unusual consumption pattern be identified.
Says George: “In one instance, our data showed a spike in energy usage in a retail outlet, which turned out to be an extractor fan running continuously. So we fitted a Lynkswitch module – and now the energy manager has remote control over the device if it needs to be switched off. When data-driven control such as this is replicated across entire building portfolios, the savings can be huge.”
Strategic analysis of energy consumption within buildings undertaken using the AMRdna tool has to date revealed potential savings of up to 15% for electricity and 30% for gas.
“Our forensic approach to energy waste is certainly gaining traction in the retail sector and is also creating a lot of interest in the public sector, where energy managers can be responsible for a portfolio of hundreds of buildings. For them, the analysis of existing consumption data provides a very effective and economical way of identifying opportunities for eradicating energy waste.”
