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In the case of a HVAC system, there are a number of thermal loads that change the temperature of a room.
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When these forces add up to zero, the bicycle travels at constant speed. There are also various other forces, such as friction and gravity, pulling the bicycle backward. When an individual pedals, there is a force pushing the bicycle and the rider forward. In the case of riding a bicycle, there are a number of forces that change the speed of the bicycle. Considering the simple thermal model presented here, the dynamic equations of the two problems are almost identical. the cooling factor changes with outdoor air temperature (OAT) in a threshold linear equation.Ĭontrolling room temperature is almost like controlling speed when riding a bicycle.the HVAC power is the product of the absolute value of the HVAC thermal load and a cooling or heating factor.The stochastic processes and the parameter values of the thermal model are chosen to correspond to a realistic building.the thermal loads on this zone are treated as signals that generate from stochastic processes.the model considers the whole building as a single zone, in which the building façade, the internal air, the furniture, etc., are always in thermal equilibrium.This simulation can show how energy, the price of energy and peak demand can be reduced by optimizing the room temperature setpoint. The ability to optimize the amount of energy used, the amount spent on energy and energy used during times of peak demands will greatly impact operating costs.īelow is a thermal model of a building that is probably the simplest HVAC simulation. Some utilities also use a building’s highest peak in energy usage to set rates and apply costly demand fees.
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Times of peak demand are often the most expensive times to use energy and occur during the hottest hours of the day – when HVAC is need the most. Depending on the local utility, the price of energy for commercial buildings changes depending on time of day and season. The goal to creating an HVAC simulation and eventually applying AI is to reduce the amount of energy used, the cost of energy and peak demand – the period in which energy is expected to be consumed at significant higher than average rate. So, is there a way to apply the same smart control algorithms that have proven efficient in playing games to a commercial HVAC system that requires coordination of hundreds of control loops? To answer this, let’s start with simulation. It falls into the category of technology that a person uses every day and would hate to live without. HVAC systems are under-appreciated technologies. One space that may not sound sexy, but there is huge potential to apply AI is the field of HVAC – that’s right heating, venting and air-conditioning. In some ways AI is catching up and overtaking us. It’s been tested and has proven efficient by using it to play backgammon, the game of go and even Atari games. Nowadays, Artificial Intelligence seems to be everywhere.