The mechanical ventilation system is one of the most energy-demanding systems in the buildings, which operates on a 12-months basis. Air balancing is a promising technique to ensure the airflow rate evenly distribution to each zone according to its requirements to achieve the purpose of energy saving. The conventional air balancing method is essentially an offline trial-and-error procedure to balance all terminal air-flow to pre-estimated values and may cause unnecessary energy consumption due to the real air demand is not equal to its pre-set value. In order to solve this problem, a very accurate on-line smart air balancing system (OSABS) is proposed to minimize the energy consumption in the air ventilation system. The objective is to realize the balance among the zones in the ventilation system, while at the same time minimizing the energy use. The research findings will be used for the setup of smart air-balancing system for net zero energy building.
1. Artificial intelligence (AI) based hybrid physical/data-driven ventilation model to accurate calculate the minimal required air-flow/energy according to the timely comfort or CO2 index;
2. A three-level hierarchical control platform to realize the air-balancing with minimal energy loss and best control performance;
3. Reliable & accurate fault detection and diagnosis (FDD) strategy with proposed joint distribution adaption for a deep learning model.
As buildings account for 35-40% of total energy use in many countries, and in schools and hospitals the need for energy for building services is audited to be just above 50%, the research outcomes have significant economic potential. The developed on-line smart air balancing system can be applied into both VAV and DOA systems, and all of the existing air-balancing systems can be upgraded to the proposed air balancing system to realize timely air-balancing of the building with minimal energy consumption. Since the developed on-line smart air balancing system is a generic system, it can be applied into the building all around the world. Therefore, the potential for applications will be tremendous.
Singapore is a tropical country with annual average temperature of 27º and annual average relative humidity of 84%. The air-conditioning and mechanical ventilation (ACMV) systems consume about 60% of the total energy in a building, where approximately 60% of the total energy is consumed by treating ventilation air. The research outcomes have significant economic potential as the energy-saving for the building. According to conservative estimates, the proposed solution can bring up to 70% energy saving when used in ventilation system compared to the traditional air-balancing method in VAV systems. Therefore, the research will create a new economic opportunities for energy-saving.
The proposed method and the products address current challenges in VAV system and give a well solution of energy-saving for new building and existing VAV system. The project will give a large potential of energy-saving for the building. Benefits may include the energy-saving, the reduction of the amount of pollution created on-site of at the electricity generating plant, and the reduction of the noise of the ventilation system.