Compact 35 Pellet Boiler Test Rig

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Twin 35kW Pellet Boilers, with Hopper
HIU Test Rig
Buffer Store with Adjustable Volumes

The test rig comprises of:


  • Compact 35 Pellet Boilers with Blown Delivery System
  • 100-500 litre Variable Sized Buffer Store
  • IHIU Monitoring System

The IHIU Monitoring System is connected to:


  • Auger Motor
  • Boiler Fan
  • Blown Delivery Fan
  • Circulating Pump

Data is recorded from all sensors to the SD card every 5 seconds, with data saved to the internet less frequently, typically 1 minute, but sometimes as low as 10 seconds when running tests.


In addition, data is sent at one minute intervals to the Energy Saving Trust's Embed Database where it can also be analysed. The beauty of the Embed database is that it is both powerful and free. It is designed as a platform for storing performance data from installations with a mind to improving efficiency by data collaboration. As far as MMSP goes, this is gold as it enables households and businesses to participate in MMSP without any ongoing costs or contracts.


C35g1.jpg


We have run a series of six auger delivery tests, and these have shown that the auger delivers average 317g (+/- 3g) of pellets in an 80 second period. This equates to 3.9625g of pellets per second.


The wood pellet supplier has confirmed 4800 kWh/1000 Kg, equating to 19.02 Wh/g.


Image Analysis to determine fuel levels

To detect the level of pellets in the hopper we are experimenting with the use of a cheap webcam, plugged into the IHIU controller's USB port. Photos are taken every minute of the auger run-time, and these are then run through some image processing to work out average colour levels, allowing us to distinguish the percentage of pellets from hopper casing in the photo, and hence the fuel level.


The auger data allows us to calibrate the percentages so readings should roughly correspond moving forwards. The hoppers in the boilers are topped up by a blown delivery system fed from a 10m3 main hopper, that is also monitored.


Analysis

To make sense of the data stored from the system we have written a PHP web page that runs through all the data, performs calculations, and generates summaries.


http://heatweb.info/iHIU/analyse_pelletboiler.php?id=58


Findings

The system is proving itself to be very useful at identifying inefficiencies that were previously going unnoticed, as well as sensor inaccuracies.


The following two separate days of data show the system under similar no-load conditions, cycling to keep plant hot.