Case Study – Smart Watts AI x Guanyu Group

Project Background

Guanyu Group

Zhuhai Guanyu Power Co., Ltd. Jinwan Branch is a PACK manufacturing facility under the Zhuhai Guanyu Group (Stock Code: 688772), located in the Qingwan Industrial Zone, Sanzao Town, Jinwan District, Zhuhai City. The branch specializes in the research, development, production, and sales of consumer-grade polymer pouch lithium-ion batteries, which are widely used in laptops, smart wearable devices, and other applications.
To support its battery R&D and manufacturing processes, the Jinwan Branch maintains strict environmental controls, requiring a temperature range of 25°C ± 3°C and a humidity range of 50% ± 20%. To meet these requirements, the facility is equipped with a centralized air conditioning system that provides cooling for both the R&D laboratories and production workshops, ensuring optimal conditions for high-quality battery production.

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Energy Saving Effect

Without altering the normal operation of the central air conditioning system—including chillers, pumps, and cooling towers—or changing existing control practices, and while maintaining the required indoor temperature and humidity levels, the project achieved a significant energy saving rate of 18.76%.
This translates to:

235,000 kWh of electricity saved annually
Approximately $25,800 USD in electricity cost savings per year
A reduction of 130,848 kg of CO₂ emissions, contributing to the company’s sustainability goals

Energy Saving Rate (%)

Annual power savings (KW/h)

Save on electricity bills (10K USD)

Reduction of carbon dioxide emission equivalent (kgCO2)

Challenges

Challenges in Equipment Operation & Maintenance Management

The central air conditioning system at Guanyu Jinwan Branch currently operates without a Building Automation (BA) group control system. As a result, routine management tasks—such as starting and stopping equipment, adjusting settings for chillers, pumps, and cooling towers—must be performed manually by personnel in the equipment room.
This manual approach presents several challenges:
Lack of real-time monitoring: Managers are unable to track equipment performance or status remotely.
Delayed fault detection: In the event of equipment failure, identifying and resolving issues is slow due to the absence of automated alerts or diagnostics. Reliance on manual inspections: The system depends heavily on human oversight, leading to inefficiencies and lagging response times in maintenance and troubleshooting.
These limitations highlight the need for a more intelligent and automated O&M solution to improve operational efficiency and reliability.

Lack of Itemized Energy Consumption Data

The central air conditioning system at Guanyu Jinwan Branch lacks sub-metering for key components such as chillers, cooling water pumps, and cooling towers. Without individual energy meters, it is impossible to accurately track the energy consumption of each piece of equipment.
This limitation presents several operational challenges:
No granular energy data: Managers cannot identify which equipment consumes the most energy or assess efficiency at the component level. Limited support for real-time monitoring: The absence of detailed data hinders the ability to monitor energy usage dynamically. Ineffective O&M decision-making: Without precise consumption data, it’s difficult to optimize operations or implement targeted energy-saving measures.
Implementing sub-metering would provide the necessary data foundation for smarter, more efficient energy management.

Lack of Real-Time Monitoring of Ambient Temperature and Humidity

Based on on-site investigations, while key indoor temperature zones at Guanyu Jinwan Branch are equipped with temperature and humidity sensors, these sensors are not connected to a real-time monitoring system. As a result:
Air conditioning management personnel cannot view live temperature and humidity data.
Operational decisions are made without immediate feedback on environmental conditions.
System performance cannot be verified in real time, making it difficult to ensure that the central air conditioning system is meeting the required environmental standards.
This gap in monitoring limits the ability to respond quickly to environmental changes or equipment issues, reducing overall system efficiency and reliability.

Energy-Saving Potential Analysis

Currently, the operation of the central air conditioning system at Guanyu Jinwan Branch is entirely based on the experience and judgment of management personnel, without the support of intelligent or automated control systems. This manual approach presents several limitations:
No dynamic adjustment based on real-time indoor temperature and humidity data
No responsiveness to outdoor climate changes, which affects cooling demand Limited optimization opportunities, resulting in unnecessary energy consumption
These gaps indicate significant potential for energy savings through the implementation of intelligent control systems that can adapt to environmental conditions in real time and optimize equipment operation accordingly.

Solution Overview

Information Collection：

Leveraging Internet of Things (IoT) technologies, the system collects:

Temperature and humidity data from each temperature zone
Outdoor weather information
Operational data from each equipment unit, including:

Current
Voltage
Load rate
Return water temperature (for chillers)

This real-time data forms the foundation for intelligent analysis and control.

Data Modeling:

Using the collected data, a targeted data model is built to:

Analyze equipment performance
Support energy-saving algorithm development
Enable predictive insights for system optimization

AI Algorithms:

After a period of data collection and self-learning, AI algorithms:

Analyze equipment operating conditions
Factor in environmental requirements and weather forecasts
Continuously optimize control logic for chillers, pumps, and other components
Output the optimal control parameters for specific working conditions

This ensures efficient operation while maintaining environmental standards.

Real-Time Monitoring System:

A large-screen monitoring interface provides:

Live equipment status
Real-time temperature and humidity data
Early warning alerts
Energy consumption statistics and analysis

This empowers managers with full visibility and control, improving responsiveness and operational efficiency.

Smart Watts AI: Professional Energy-Saving Solutions

Smart Watts AI specializes in delivering intelligent energy-saving solutions, with core expertise in Internet of Things (IoT), artificial intelligence (AI), and automation technologies. The company serves a wide range of industries—including industrial manufacturing, construction, and environmental protection—through applications in:

Energy conservation and carbon reduction
Energy management
Environmental monitoring

Smart Watts AI offers end-to-end services that span:

Hardware equipment R&D
Algorithm model optimization
Engineering implementation and support

By integrating advanced technologies across the entire value chain, Smart Watts AI empowers clients to achieve greater operational efficiency, sustainability, and data-driven decision-making.

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