Modeling and Simulation of Digital Twin Reinforcement Learning Control of AHU Heating
Implementation Plan:
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Step 1: Initially, we will construct the House Heating Model by using a heater and thermostat controlling system in Simulink.
Step 2: Next, we will integrate the subsystem such as supply fan dynamics, Zone temperature feedback loop and value control heating coil models.
Step 3: Then, we simulate the model and collect temperature and AHU based Simulink data.
Step 4: Next, we will train the collected data using PPO based RL agent technique to improve the energy saving and system stability purposes.
Step 5: Next, we analyze the Energy usage, Deviation and Response time based on collected data.
Step 6: Finally, we plot performance for the following metrics:
6.1 : Time vs Temperature (°C)
6.2 : Time vs Energy Consumption (J)
6.3 : Time vs Response time (s)
6.4 : Number of episodes vs Average Reward
Software Requirements:
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1. Development Tool: Matlab-R2023a/Simulink or above
2. Operating System: Windows 10 (64-bit) or above
Note:
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1) If the proposed plan does not fully align with your requirements, please provide all necessary details—including steps, parameters, models, and expected outcomes—in advance.
2) Kindly ensure that any missing configurations or specifications are clearly outlined in the plan before confirming.
3) If there’s no built-in solution for what the project needs, we can always turn to reference models, customize our own, different math models or write the code ourselves to fulfil the process.
4) If the plan satisfies your requirement, Please confirm with us.
5) Project based on Simulation only.
