micropython-samples/power
Peter Hinch 15fa69d0bf Fix document backlinks. 2018-02-21 06:10:37 +00:00
..
images Minor change to power meter docs. 2017-11-29 09:05:18 +00:00
README.md Fix document backlinks. 2018-02-21 06:10:37 +00:00
SignalConditioner.fzz Add power meter. 2017-11-03 12:11:31 +00:00
mains.py Add power meter. 2017-11-03 12:11:31 +00:00
mt.py Add power meter. 2017-11-03 12:11:31 +00:00

README.md

A phasor power meter

This measures the AC mains power consumed by a device. Unlike many cheap power meters it performs a vector measurement and can display true power, VA and phase. It can also plot snapshots of voltage and current waveforms. It can calculate average power consumption of devices whose consumption varies with time such as freezers and washing machines, and will work with devices capable of sourcing power into the grid. It supports full scale ranges of 30W to 3KW.

Images of device

Main README

Warning

This project includes mains voltage wiring. Please don't attempt it unless you have the necessary skills and experience to do this safely.

Hardware Overview

The file SignalConditioner.fzz includes the schematic and PCB layout for the device's input circuit. The Fritzing utility required to view and edit this is available (free) from here.

The unit includes a transformer with two 6VAC secondaries. One is used to power the device, the other to measure the line voltage. Current is measured by means of a current transformer SEN-11005 from SparkFun. The current output from this is converted to a voltage by means of an op-amp configured as a transconductance amplifier. This passes through a variable gain amplifier comprising two cascaded MCP6S91 programmable gain amplifiers, then to a two pole Butterworth low pass anti-aliasing filter. The resultant signal is presented to one of the Pyboard's shielded ADC's. The transconductance amplifier also acts as a single pole low pass filter.

The voltage signal is similarly filtered with three matched poles to ensure that correct relative phase is maintained. The voltage channel has fixed gain.

PCB

The PCB and schematic have an error in that the inputs of the half of opamp U4 which handles the current signal are transposed.

Firmware Overview

Dependencies

  1. The uasyncio library.
  2. The official lcd160 driver lcd160cr.py.

Also from the lcd160cr GUI library the following files:

  1. lcd160_gui.py.
  2. font10.py.
  3. lcd_local.py
  4. constants.py
  5. lplot.py

Configuration

In my build the above plus mains.py are implemented as frozen bytecode. There is no SD card, the flash filesystem containing main.py and mt.py.

If mt.py is deleted from flash and located on an SD card the code will create simulated sinewave samples for testing.

Design

The code has not been optimised for performance, which in my view is adequate for the application.

The module mains.py contains two classes, Preprocessor and Scaling which perform the data capture and analysis. The former acquires the data, normalises it and calculates normalised values of RMS voltage and current along with power and phase. Scaling controls the PGA according to the selected range and modifies the Vrms, Irms and P values to be in conventional units.

The Scaling instance created in mt.py has a continuously running coroutine (._run()) which reads a set of samples, processes them, and executes a callback. Note that the callback function is changed at runtime by the GUI code (by mains_device.set_callback()). The iteration rate of ._run() is about 1Hz.

The code is intended to offer a degree of noise immunity, in particular in the detection of voltage zero crossings. It operates by acquiring a set of 400 sample pairs (voltage and current) as fast as standard MicroPython can achieve. On the Pyboard with 50Hz mains this captures two full cycles, so guaranteeing two positive going voltage zero crossings. The code uses an averaging algorithm to detect these (Preprocessor.analyse()) and populates four arrays of floats with precisely one complete cycle of data. The arrays comprise two pairs of current and voltage values, one scaled for plotting and the other scaled for measurement.

Both pairs are scaled to a range of +-1.0 with any DC bias removed (owing to the presence of transformers this can only arise due to offsets in the circuitry and/or ADC's). DC removal facilitates long term integration.

Plot data is further normalised so that current values exactly fill the +-1.0 range. In other words plots are scaled so that the current waveform fills the Y axis with the X axis containing one full cycle. The voltage plot is made 10% smaller to avoid the visually confusing situation with a resistive load where the two plots coincide exactly.

Calibration

This is defined by Scaling.vscale and Scaling.iscale. These values were initially calculated, then adjusted by comparing voltage and current readings with measurements from a calibrated meter. Voltage calibration in particular will probably need adjusting depending on the transformer characteristics.