Browsing by Subject "energy management system"

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    Demand-Controlled Ventilation Energy Savings for Air Handling Unit
    (Energy Proceedings, 2021) Blubaugh, Matthew; Razban, Ali; Chen, Jie; Mechanical and Energy Engineering, School of Engineering and Technology
    Heat, cooling, and ventilation units are major energy consumers for commercial buildings, consuming as much as 50% of a building’s total annual power usage. Management of an air handling system’s energy is a key factor of reducing the energy costs and carbon dioxide (CO2) emissions that are associated with the demand when ventilating and conditioning the air in a building. One issue is that buildings are frequently over ventilated as a full assessment of the air handling unit (AHU) data is not evaluated by building operators. There are multiple variables that account for energy consumption of the AHU which need to be monitored by building operators. In order to assess the demand, it is required that the CO2 levels of the occupied zones be measured, and the outdoor air ventilation rate be adjusted based on real-time CO2. The concept of an energy management system and its characteristics are defined in respect to use with an AHU system. The prototype system used for the research is demonstrated and key data analyzed using real-time data collection. The goal of the research is to assess the number of CO2 sensors needed to accurately measure the demand-based needs for ventilation and provide review of the data required to monitor the AHU energy. Findings indicate that no more than one CO2 sensor would be required for a large lecture hall.
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    Enhancing Energy Management System using Internet-of-things Sensors and Energy Simulation -A Case Study of Industrial Ventilation
    (Taylor & Francis, 2023-01) Wu, Da-Chun; Movahed, Paria; Razban, Ali; Chen, Jie; Mechanical and Energy Engineering, Purdue School of Engineering and Technology
    There is a need for energy conservation in order to achieve the 2030 Sustainable Development Goals. Many studies have demonstrated that delivering real-time assessment and energy saving goals are some of the most effective practices to reduce energy consumption and can be achieved by utilizing energy management. However, there remains a sizable gap in the development of the energy management and energy-efficiency evaluation for complicated manufacturing processes. With the current development of new technologies such as Internet of Things, big-data analytics, and machine learning, improvements can be made to further enhance the effectiveness of the energy management system. In this study, a real-time monitoring system that utilizes IoT sensors, cloud-based big data, and grey-box modeling is proposed. This paper describes the ongoing study of using the proposed energy management system in an electroplating manufacturer to reduce its ventilation energy consumption.