The tools developed by Guru Systems analyse performance data and apply powerful machine learning algorithms to identify the root causes of inefficiency and propose costed measures to improve heat networks.
Guru Systems' project is among nine schemes to be awarded a share of the Government body's £6 million fund in the second round of the competition, which was set up to encourage innovative solutions to drive down energy bills and boost low carbon heat supplies in the UK. The competition will help to stimulate innovation in heat network technologies and bring the UK a step closer to generating 14% of demand through that method by 2030, while reducing carbon emissions and cutting bills for consumers.
The smart payment and energy-efficiency technology company is developing this new system in part to allow designers to analyse real-time data from the networks they have designed and use the information to develop more efficient networks in the future.
Casey Cole, Managing Director of London-based Guru Systems, said: "Oversizing heat networks is a common pitfall for M&E engineers. They have to predict the peak heat demand from each home as well as the proportion of people on the network that are likely to need heat at the same time. Ask any two engineers and their answers might differ by as much as 500%. And these design choices bring huge consequences: get it wrong and the system will be oversized, expensive and wasteful.
"The technology we have developed as part of this funding programme will ensure that engineers can 'close the information loop' by seeing how their systems perform in the real world, cut wastage and improve running costs for their clients.
"We believe that developers could save 25% on the cost of their M&E package by sizing their networks correctly and their heat networks will actually work better as a result."
In addition to providing data for designers, the innovative algorithms built into the new tools can recognise patterns and identify the likely source of inefficiency on heat networks using data from smart meters, building management systems, M-Bus networks (a system for the networking and remote reading of utility meters) or manual readings.
In the first stage of funding, which was announced at the beginning of the year, London-based Guru Systems carried out a proof of concept on four heat networks across the UK, analysing several million data points.
By using the technology and implementing cost-effective improvement measures, the four networks could reduce input fuel use by between 33 and 51 percent. This equates to an average saving of £179 per home per year. The company has estimated that the software could save UK heat networks £400m in reduced energy costs over the next 10 years.
By capturing and learning from complex Big Data, Guru's machine learning tools uncover hidden energy use patterns and identify untapped energy efficiency opportunities. They also enable companies to increase customer engagement by better understanding their needs.
Guru Systems' project is among nine schemes to be awarded a share of the Government body's £6 million fund in the second round of the competition, which was set up to encourage innovative solutions to drive down energy bills and boost low carbon heat supplies in the UK.
The competition will help to stimulate innovation in heat network technologies and bring the UK a step closer to generating 14% of demand through that method by 2030, while reducing carbon emissions and cutting bills for consumers.
Guru's existing pay-as-you-go and real-time monitoring technology has already been installed in around 4,000 properties on more than 60 district heat networks across the UK. The Guru Hub allows operators to accurately calculate the cost of heat generation and consumer usage in real time.