Building data may be the key to alleviating grid strain

With the nationwide phase-out of fossil fuel hitting capacity-related stumbling blocks, better use of existing building data can reduce industrial demand-side energy consumption and hasten the transition to renewable sources.

Paul Walsh, General Manager at building analytics specialists CIM, made the observation following recent news that Scottish wind turbines were forced to stop due to grid constraints despite a record day for output. He believes this shutdown demonstrates a nationwide grid strain problem heavily driven by inefficient industrial energy usage, which is hampering adoption of green technologies in favour of fossil fuels.

“The latest turbine shutdown may have been comparatively small when compared to the national grid and UK wind power production as a whole, but it tells a much larger story,” explains Paul. “We need to free up capacity in our energy infrastructure to adopt more sustainable solutions, and in order to do so, we must identify where inefficiencies exist.

“Demand side consumption from industry is one such area, as though the country has made excellent progress bringing renewable technologies onto the grid, issues still exist in eliminating waste at the point of use. Making these operations more efficient, through insights and actions driven by building data analytics, will lower the base load typically required from fossil fuel-powered generation stations, enabling wider uptake of eco-conscious energy sources.”

CIM’s latest report, The Energy Blind Spots, identifies further concerns around industry, sustainability and energy consumption, with only 30% of facilities managers surveyed within admitting to continually monitoring CO₂ emissions. This is despite 63% of respondents’ sites being certified to the ISO 50001 energy management standard, painting a further picture of energy-efficient demand side practices being neglected due to time pressures on facilities and maintenance teams.

“Our own research has demonstrated that sustainability and efficiency efforts continue to be hampered in the industrial sector by struggles to collect, analyse and respond to critical utility performance metrics,” concludes Paul. “The introduction of data-informed plant maintenance processes, fed through innovative data analytics tools such as CIM’s PEAK Platform, can help tackle these issues at the source.

“Indeed, we estimate that if data analytics were able to deliver a 15% reduction in demand side electrical energy, which is a low estimate of reductions currently being experienced by our complex manufacturing clients. Importantly, it would free up capacity on the existing grid for an additional 1600 x 4MW wind turbines, with no capital upgrades to the grid required. The comparatively small step of using data smartly really is a great example of how doing a little can go a long way when it comes to easing grid pressure.”