Custom Data Power Acquisition System Using Hobby Electronics
Designed and deployed power-sensing system leading to $500 savings over TED Spyder - led to second author publication to ASHRAE Transactions
This project revolves around creating a power data accquisition system (DAQ) using a the PZEM printed circuit board. It it can measure power when connected directly to the breaker.
The PCB of the PZEM (Left) and the connection to the breaker system
The microcontroller used was the ESP32. C++ was used to process the data and establish serial communication. The main issue was that ESP32 operated on 3.3 V logic and the PZEM operated on 5V logic. Hence a level shifter was needed as per the diagram shown below
The circuit diagram (left) and the PCB for the level shifter (right)
Prior to installation in the breaker box, a 3D model was made in NX seimens to verify the dimensions
3D model for designed data acquisition system
Post installation, our custom DAQ was compared with IoTWatt for accuracy and it yielded very positive results
PZEM vs Iotwatt power measurements as a time series for two different breakers
We then compared the price and error of the custom DAQ with respect to the IotWatt - we found that our DAQ was significantly cheaper for a marginal error
The residential building end-use sector represents one of the world’s most significant CO2 producers and energy consumers. As principal endpoints of an aging power system within the US, these consumers are faced with compounding reliability concerns and necessitate innovative solutions to address ever-increasing power demands. To mitigate these issues, novel systems need to be developed to minimize buildings’ overall impact on the grid in a real-time approach. One such improvement is to retrofit existing buildings with an energy monitoring system which can support such a strategy. In this paper, a design for an IoT based smart monitoring system is developed to achieve reduced overall energy consumption. Economical, low-power current transformer (CT) sensing units are implemented inside an AC load panel within a residential home to monitor the heaviest electrical loads, focusing efforts on the HVAC system and the heat-pump driven water heater. Data from these sensors are collected via IoT microcontroller units (MCUs) and maintained within a real-time database on an in-situ server. This could then be used for “faster than real-time” modeling of the electrical loads of a residential building.
