Energy Consumption Innovation

Energy Consumption Innovation

Supply-Side HVAC
Optimisation

Supply-Side HVAC
Optimisation

AI-powered chiller
optimisation and
automation solution

AI-powered chiller optimisation and automation solution

Today, buildings contribute over 60% of carbon emissions in Hong Kong. Inside a building, Heating, Ventilation & Air Conditioning (HVAC) system is the most energy-consuming system accounting for nearly 50% of total energy consumption, of which 65% of energy is consumed in the plant room. An energy-efficient HVAC system is vital to achieving energy reduction and reducing carbon footprints to tackle climate change.

For buildings lacking flexibility in control to respond to external environmental changes, an AI-based chiller plant optimisation solution that can provide complete and continuous control of the chiller plant devices and monitor buildings’ energy consumption in real-time can enhance buildings’ energy efficiency and achieve sustainability in the long run.

How does it work?

How does it work?

Our AI-based chiller plant optimisation solution, PlantPRO, is designed to optimise the operation and maintenance of the chiller plant. It consists of an edge computer embedded with software to deliver comprehensive on-premises control that can fully manage the plant independently.

After installing the hardware that connects to the equipment in the chiller plant, the software runs a continuous performance feedback loop powered by sophisticated control algorithms.

Leveraging its AI and machine learning capabilities, the solution can predict the chiller plant’s cooling load requirements and autonomously control its equipment, to achieve optimal efficiency. With smart sequencing, the solution automatically picks the most optimal combination of chillers and equipment to satisfy the cooling demand of a building, guaranteeing the lowest energy consumption for the appropriate amount of cooling required.

Features

Features

The solution provides complete and continuous control and performance management of all chiller plant devices in buildings with or without a Building Management System (BMS). It also allows users to set their parameters and monitor HVAC status through a powerful and intuitive graphical user interface (GUI).

Combining Machine Learning and AI, this solution automatically builds data models of the chiller operations and picks the optimal combination to optimise equipment staging and sequencing, reducing energy consumption significantly.

The solution offers a dedicated high-end diagnostic engine that turns data into actionable knowledge, allowing property managers to understand how the main components of a plant are performing. The solution also calculates the electrical consumption for the given load and conditions for each chiller and provides detailed analytics. An alarm will be raised if a fault is detected, giving technicians sufficient time to investigate the machinery.

All measurement data is saved in the process. This solution also comes with a measurement and performance module to assist property and facility managers in attaining better data validation. When conducting a M&V project, the solution enables comparisons of the actual measured efficiency versus the designed baseline utilising the International Performance Measurement and Verification Protocol (IPMVP), allowing the facility management team to measure chiller efficiency and assess how much energy is saved.

Benefits

Benefits

Case Studies