The chiller consumes 70% of the total energy of the building. This is very essential to optimize the operation of the chiller with high energy efficiency. Monitoring efficiency of the chiller needs a number of parameters to be measured at individual level of each chiller. This is not possible to collect these parameters in a required time period of limited number of resources. Hence, remote connectivity of these chillers can help to collect the entire set of data in short period. Most of the present chiller system has the capability to connect to centralised server, making, it the remote monitoring easy and affordable. In this discussion, we will try to give a present status of the “Remotely Connected Chiller Technology”. The aim of connected chiller technology is to control the system from a central control point.
Introduction to Technology
A traditional building automation system (BAS) provides alarms that identify problems in a chiller after they occurred based on system thresholds. The response thus happens after the fact when the fault already triggered and system effected. The BAS alarm requires further analysis by the facility manager to identify the fault and the way to fix the problem. In addition, BAS alarms primarily focus on critical failures or problems that will lead to significant comfort or repair issues.
Remotely connected and monitoring technique gives customer access to the chiller anytime and anywhere. Remote connection can help determine when maintenance will be required. Maintenance –if it is done preventively at all rather than waiting for the failure. This also helps analysts in monitoring chiller performance and reports any abnormal operating conditions. Remote monitoring can often identify what is wrong with a system before it appears. Connected chillers address opportunities for accelerated growth of service repair and retrofit opportunities by leveraging data and analytics from connected installed base.
The remote analysis and diagnostics is shown in the Figure 1.
Figure 1: Remote analysis and Diagnostic system layout
All the above functions are performed with the customized software that can collect the data and automatically analyze it. The results of the analysis are presented in the customized platform and automated report is generated through the software.
There are three steps in remote analysis of the chiller:
- Data Collection:The data can be collected from the individual chiller with installed communicable card within the chiller or through the BMS. The available data point on the chiller need to be configured with the application software. This data collection requires a physical device to send the data to the server through internet.
- Automated analytic:The automatic analytic of the collected data is performed with the technique “Fault Detection and Diagnostic (FDD)”. This is rule based technology to find out the abnormal condition of the chiller.
- Reporting:With the software, customized report can be generated, which shows the present operating condition of the chiller based on the design or operating data.
Methodology for Remote Analysis
Chillers are remotely analyzed with the help of fault detection and diagnostics (FDD) technique, which detect the future fault based on the logic implemented in the connected chiller platform.
Fault detection and diagnostics (FDD) is a method to monitor a system, identify when a fault has occurred, and point out the type of fault and its location. This method improves comfort, and reduces the operation, maintenance, and utility costs, thus, reducing the environmental impact.
FDD system focuses on identifying non-critical deficiencies in which the chiller still performs. But it is not optimized to minimize energy or maintain expense. The FDD system can recognize when a condition is starting to deviate from the correct values, or when a system is operating sub-optimally, so that the facility manager can see the problem before it actually occurs. It can detect not only a trend in an adverse direction, but also the cause of the trend, so that the facility manager can fix the problem quickly.
FDD software not only detects faults but also it instantly provides information based on analytics (e.g., energy or cost impacts of the fault) to help the building operator screen and prioritize which faults to fix basedon safety, operational implications, code compliance, cost, impact on occupant comfort, and other factors. Without techno-commissioning, a facility manager’s maintenance strategy is strictly schedule-based and is not related to the actual operating conditions of the building and its equipment. With FDD, the analytics tell the manager what needs to be done today based on current system condition and performance, as well as what items can be deferred.
Future Technology
In future, the Internet of Things (IoT) and cloud computing is supposed to dominate the connected equipment monitoring and diagnostic. This technology reduces the initial coat due to non-requirement of local sever and data in store in the cloud. This technology helps to access the data anytime, anywhere and with any device. Energy Management and Internet of Things will go hand-in-hand. Also IoT will play a very important role in making the consumption of resources efficient along with systems. This will eliminate the most of the physical sensor, wiring and sever and will lead to lower investment in connected technology.
The machine learning is one of the upcoming technologies that will leverage the existing connected chiller technology. This will make the present analysis more automated as it will be able to read the data and predict the future faults and failures. The technology has not been extensive used at preset.
Conclusion
The connected chiller technology brings these chillers closer to the experts and helps the service peoples to get an idea before visiting any site. This also reduces the consulting charges of the chiller and no physical visit is required. Apart from many advantages, it is very important to provide the correct information to the expert seating remotely. A gap in the information will lead to misunderstanding of the equipment and its analytics results.
AUTHORS CREDIT & PHOTOGRAPH
Pranjal Dutta
India Engineering Centre,
Johnson Control India Pvt Ltd,
Mumbai
