Uncover hidden opportunities with energy data analytics

What springs to mind when you hear the words energy data analytics? To me, I feel like energy data analytics is not my thing. Energy data analytics, however, is of great importance to any organisation or business that wants to run more efficiently, reduce costs, and increase productivity. Energy efficiency is one of the best ways to accomplish these goals.

Energy efficiency is not about investment in expensive equipment and internal reorganization. Enormous energy saving opportunities is hidden in already existing energy data. Given that nowadays, energy data can be recorded from almost any device, a lot of data is captured regularly and therefore a lot of data is readily available.

Organisations can use this data to convert their buildings’ operations from being a cost centre to a revenue centre through reduction of energy-related spending which has a significant impact on the profitability of many businesses. All this is possible through analysis and interpretation of data to predict future events with greater accuracy. Energy data analytics therefore is about using very detailed data for further analysis, and is as a consequence, a crucial aspect of any data-driven energy management plan.

The application of Data and IT could drive significant cost savings in company-owned buildings and vehicle fleets. Virtual energy audits can be performed by combining energy meter data with other basic data about a building e.g. location, to analyse and identify potential energy savings opportunities. Investment in energy dashboards can further enable companies to have an ongoing look at where energy is being consumed in their buildings, and thus predict ways to reduce usage, not to mention that energy data analytics unlock savings opportunities and help companies to understand their everyday practices and operating requirements in a much more comprehensive manner.

Using energy data analytics can enable an organisation to: determine discrepancies between baseline and actual energy data; benchmark and compare previous performance with actual energy usage. Energy data analytics also help businesses and organisations determine whether or not their Building Management System (BMS) is operating efficiently and hitting the targeted energy usage goals. They can then use this data to investigate areas for improvement or energy efficient upgrades. When energy data analytics are closely monitored, companies tend to operate more efficiently and with better control over relevant BMS data.

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What Sub-Metering did for Nissan in Tennessee

When Nissan built its motor manufacturing plant in Smyrna 30 years ago, the 5.9 million square-foot factory employing over 8,000 people was state of art. After the 2005 hurricane season sky-rocketed energy prices, the energy team looked beyond efficient lighting at the more important aspect of utility usage in the plant itself. Let’s examine how they went about sub-metering and what it gained for them.

The Nissan energy team faced three challenges as they began their study. They had a rudimentary high-level data collection system (NEMAC) that was so primitive they had to transfer the data to spread-sheets to analyse it. To compound this, the engineering staff were focused on the priority of getting cars faster through the line. Finally, they faced the daunting task of making modifications to reticulation systems without affecting manufacturing throughput. But where to start?

The energy team chose the route of collaboration with assembly and maintenance people as they began the initial phase of tracking down existing meters and detecting gaps. They installed most additional equipment during normal service outages. Exceptions were treated as minor jobs to be done when convenient. Their next step was to connect the additional meters to their ageing NEMAC, and learn how to use it properly for the first time.

Although this was a cranky solution, it had the advantage of not calling for additional funding which would have caused delays. However operations personnel were concerned that energy-saving shutdowns between shifts and over weekends could cause false starts. ?We’ve already squeezed the lemon dry,? they seemed to say. ?What makes you think there?s more to come??

The energy team had a lucky break when they stumbled into an opportunity to prove their point early into implementation. They spotted a four-hourly power consumption spike they knew was worth examining. They traced this to an air dryer that was set to cyclical operation because it lacked a dew-point sensor. The company recovered the $1,500 this cost to fix, in an amazing 6 weeks.

Suitably encouraged and now supported by the operating and maintenance departments, the Smyrna energy team expanded their project to empower operating staff to adjust production schedules to optimise energy use, and maintenance staff to detect machines that were running without output value. The ongoing savings are significant and levels of shop floor staff motivation are higher.

Let’s leave the final word to the energy team facilitator who says, ?The only disadvantage of sub-metering is that now we can’t imagine doing without it.?

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Disadvantages of Spreadsheets

Spreadsheets are flexible, inexpensive and easy to use. They are especially handy when it comes to beating report submission deadlines or making impromptu data computations. That’s why office workers, managers and even executives have made spreadsheets their go-to solution for such undertakings and more.

Spreadsheets have become so ubiquitous, that they’ve found their way into a wide range of applications including complex modelling, accounting reconciliations, market data analysis, work flow tracking and monitoring, analytical review and financial reporting.

Unfortunately, organisations heavy reliance on spreadsheets have made these User Developed Applications (UDA) into high-risk office tools. Simple spreadsheet errors like leaving out a negative sign or a cut-and-paste mistake have already caused million-dollar discrepancies. Also, when a fraudulent employee enters into the picture, the risks become unimaginable.

Think TransAlta?s spreadsheet cut-and-paste glitch (the company later called this a ?simple clerical error?) which caused the energy firm a whopping $24 million loss or Fidelity?s overstatement of its earnings owing to the omission of the minus sign on the spreadsheet of a $1.3 billion net capital loss.

In both cases and in many other similar spreadsheet fiasco, the errors played a major role in the organisation’s decision-making, leading to disastrous results including, but not limited to financial loss, shattered investor confidence and public embarrassment.

If these are scenarios your organisation can ill afford, then it’s time to ask yourself: Do the disadvantages of spreadsheets far outweigh their benefits to merit a call for total liberation from them?

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FUJIFILM Cracks the Energy Code

FUJIFILM was in trouble at its Dayton, Tennessee plant in 2008 where it produced a variety of speciality chemicals for industrial use. Compressed-air breakdowns were having knock-on effects. The company decided it was time to measure what was happening and solve the problem. It hoped to improve reliability, cut down maintenance, and eliminate relying on nitrogen for back-up (unless the materials were flammable).

The company tentatively identified three root causes. These were (a) insufficient system knowledge within maintenance, (b) weak spare part supply chain, and (c) generic imbalances including overstated demand and underutilised supply. The maintenance manager asked the U.S. Department of Energy to assist with a comprehensive audit of the compressed air system.

The team began on the demand side by attaching flow meters to each of several compressors for five days. They noticed that – while the equipment was set to deliver 120 psi actual delivery was 75% of this or less. They found that demand was cyclical depending on the production phase. Most importantly, they determined that only one compressor would be necessary once they eliminated the leaks in the system and upgraded short-term storage capacity.

The project team formulated a three-stage plan. Their first step would be to increase storage capacity to accommodate peak demand; the second would be to fix the leaks, and the third to source a larger compressor and associated gear from a sister plant the parent company was phasing out. Viewed overall, this provided four specific goals.

  • Improve reliability with greater redundancy
  • Bring down system maintenance costs
  • Cut down plant energy consumption
  • Eliminate nitrogen as a fall-back resource

They reconfigured the equipment in terms of lowest practical maintenance cost, and moved the redundant compressors to stations where they could easily couple as back-ups. Then they implemented an online leak detection and repair program. Finally, they set the replacement compressor to 98 psi, after they determined this delivered the optimum balance between productivity and operating cost.

Since 2008, FUJIFILM has saved 1.2 million kilowatt hours of energy while virtually eliminating compressor system breakdowns. The single compressor is operating at relatively low pressure with attendant benefits to other equipment. It is worth noting that the key to the door was measuring compressed air flow at various points in the system.

ecoVaro specialises in analysing data like this on any energy type.?

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