Node-Red AHU PID Control Training System with Interactive UI c/w Step by Step Guide to Create Bespoke Dynamic Graphics.
GUI (Graphical User Interface) or HMI (Human Man Interface) Supervisor Systems for BMS (Building Management Systems) and SCADA (Supervisory Control And Data Acquisition) can be very expensive. This course will provide a detailed yet easy to follow step by step guide on how to create bespoke professional level HMI using easily available and free software applications.
The course will teach you how to create and use a simulated graphical AHU (Air Handling Unit) with animated equipment items that responds to user inputs for Temperature Sensors and Setpoints to a Node-Red PID (Proportional, Integral and Differential) loop controller node running on a Raspberry Pi (RPi) mini computer. By altering the setpoint and various temperature sensors you will learn how the PID controller reacts in real-time to the various parameter changes recorded and displayed on the HMI chart trend logs. In this way you will learn the dark art of 'Tuning' a PID controller.
Although this is a simulated AHU system it is perfectly applicable to any installed building AHU system in conjunction with a typical BACnet or Modbus BMS controller. The AHU simulation includes Heating and Cooling PID control and energy saving strategies such as utilizing cool OAT (Outside Air Temperature) sensor in Cooling mode and warm RAT (Return Air Temperature) sensor recirculation in Heating mode.
In fact, as this is a very economical solution, it opens up a potentially huge market for converting 100s of thousands of existing SMCP's (Small, Medium, Commercial, Properties) from 'Dumb Thermostat' systems to 'Smart IoT' buildings, leading to potential energy savings of up to 30% for the property owners. A fantastic business opportunity for BMS System Integrators, tech entrepreneurs and facility management companies.
To learn how to make your system IoT, or you have limited or no knowledge of Node-Red or the RPi, I strongly recommend my Udemy published course, "Practical Home Automation Using Node-RED and Raspberry Pi."
