Compute Linear Response Characteristics

This example shows how to compute the linear response characteristics of the storing tank temperature of a solar water heater.

Read Data

ThingSpeak™ channel 29633 contains the storing tank temperature data (in degree Celsius) of a solar water heater in Cambridge, UK. The temperature data is collected once every 15 seconds. Read the data for 2 hours from channel 29633 using the thingSpeakRead function. Convert the timestamps to elapsed minutes from the start.

start = datetime('September 12, 2017 06:09:00 AM');
stop = datetime('September 12, 2017 8:09:00 AM');
data = thingSpeakRead(29633, 'Fields', 5, 'DateRange', [start stop], 'OutputFormat', 'table');
data.Timestamps = 24*60*(data.Timestamps-data.Timestamps(1));

Linear Response Characteristics

Assuming that solar water heater is a linear system, calculate the related performance indicators using the temperature as the response data of the system.

perfIndicators = lsiminfo(data.StoreTopTemp, days(data.Timestamps))

perfIndicators = 

  struct with fields:

    TransientTime: 119.1970
     SettlingTime: 78.2707
              Min: 47.2000
          MinTime: 106.4500
              Max: 49.9000
          MaxTime: 20.4333

Send Performance Indicators to ThingSpeak

Send the minimum, minimum time, maximum, and maximum time performance indicators to a ThingSpeak channel using the thingSpeakWrite function. Change the channelID and the writeAPIKey to send data to your channel.

channelID = 17504;
writeAPIKey = '23ZLGOBBU9TWHG2H';
thingSpeakWrite(channelID,[perfIndicators.Min,perfIndicators.MinTime,perfIndicators.Max,perfIndicators.MaxTime],'WriteKey',writeAPIKey);