Monitoring Building Energy in Real Time – A Solution

Table of Contents

Introduction to Real-Time Energy Monitoring
A Typical Week Energy Consumption
Energy Saving
Wireless Remote Monitoring
Typical Maintenance Cost Savings Achieved with Clients
Energy Accountability

Introduction to Real-Time Energy Monitoring

Alerta provided real time energy consumption condition for a fast food restaurant. Six distribution points were constantly monitored at the restaurant. The figure below illustrates the consumption data for distribution switch DBK1 that feeds a majority of the process related equipment.

A Typical Week Energy Consumption

A Typical Week Energy Consumption

The daily energy consumed can be split into three focused sections:

1) Energy waste consumption during closure

a) Is all cooking equipment switched off
b) Are the Franke Island units turned off
c) Is all ancillary equipment turned off (computers, monitors, lights, tills, staff room)
d) Are there critical items required in closure time, this will provide base load level

2) Unexplained peak demands

a) Identify why equipment is switched on, if not needed for current transactions

3) Transactional energy waste

a) The energy consumption of the pressure fryers, process equipment, etc., should reflect the transactional demands

A Typical Week Energy Consumption

Energy Saving

By concentrating on these three sections of potential waste energy, total energy consumption is expected to reduce by 10% to 15%. Moreover, assuming an average period energy cost of £6,200 (£80,600 annually), this would equate to a saving of between £8,060 and £12,090.

The graph below shows the top 35 restaurants electricity costs for period 4.

Energy Saving

Considering £3,500 as a period spend, potential saving that can be attained per restaurant across 13 periods is in the range of £4,550 and £6,825. For all 35 restaurants, the possible saving would be in the range of £60,000 and £75,000. This graph shows the top 10 worst performing stores with regards to sales per period versus electricity consumption per period.

Period 4 sales are on the vertical axis and energy costs are on the horizontal axis. Restaurants with similar period sales are predicted to have similar energy consumption. A difference of about £500 per period is seen in the chart given below.

top 10 worst performing stores

The graph below illustrates the average daily sales versus energy costs for the same top ten restaurants. The lower scale signifies daily spend and the upper scale signifies daily energy costs as a percentage of daily sales.

Shop 44 is the worst performing restaurant with energy costs making up for 6.31% of sales, through to shop 240 when the energy costs are 4.11%. The average value for all stores is 2.4%, (further comprehensive analysis should reveal extra insights).

average daily sales versus energy costs

Energy savings in isolation should provide adequate saving with pay back within a year, allowing restaurant assets to be monitored for additional cost reduction.

A site survey and visual inspections were performed by Alerta to emphasize the other opportunities available for business improvements.

It is possible to monitor the asset health in real time to enable a predictive management regime and a pro-active maintenance system to be installed to acquire critical asset health data.

1. Asset health

a. Lift performance to minimize asset catastrophic failure during operational hours
b. Cold room refrigeration monitoring
c. Pressure fryer oil filtration process and equipment

2. Risk reduction

a. Extraction blockage or film build up to be identified
b. Refrigerant cooling system performance
c. Identify grease contamination in water drainage pipework

3. Quality

a. Real-time monitoring of air temperatures in cold rooms
b. Cold room door open real-time alarm
c. The defrost cycle frequency

Normally, business benefits are projected to be realized across a number of activities.

business benefits

Wireless Remote Monitoring

  • The installation of wireless remote asset monitoring has a significant and positive impact on asset availability, and decreasing maintenance costs by creating a predictive maintenance regime. Using real time data risks of asset failure can be regulated reducing risk exposure and maintenance costs.
  • Continuous monitoring of the potential failure points on assets and measurement of the asset operating condition against three parameters
  • Green – Asset running and no action needed
  • Amber – Potential failure mode has been established and requires maintenance action in engineering hours
  • Red – Significant failure mode has been noticed and demands immediate maintenance action

The business drivers for the installation of asset monitoring are as follows:

  • Decreasing downtime through the combined planning and scheduling of repairs specified by CBM methods
  • Enhance equipment performance and output
  • Maximize component life and thereby lower life cycle costs
  • Reduction in secondary damage
  • Reduction in critical spares holding
  • Potentially 100% asset utilization
  • Time-based maintenance routines are typically reduced by 40% to 60%
  • Establishment of a full and detailed asset register
  • Delivered ‘Best Practices’ subsequent to FMEA analysis
  • ‘Best Practices’ fed into client design performance standards for future asset procurement
  • Established financial business cases on all projects

Typical Maintenance Cost Savings Achieved with Clients

Savings achieved on previous annual costs:

  • Energy savings – 22%
  • Planned maintenance reduction – 43%
  • Material cost savings – 24%
  • Corrective maintenance reduction – 18%
  • Statutory maintenance reduction – 80%
  • ROI less than one year for business critical assets

Energy Accountability

  • Allocate energy costs to outputs, to components and to people
  • Extracting data from Legacy, BMS and metered systems
  • Pin point major energy users
  • Cost avoidance through early degradation detection
  • Reduce carbon emissions measured in real-time

H3S Ltd

This information has been sourced, reviewed and adapted from materials provided by H3S Ltd.

For more information on this source, please visit H3S Ltd.

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