In our analytical services business, we frequently find significant problems in commercial and industrial building HVAC systems that have probably gone unnoticed for some time. Many of these problems have resulted in wasted energy and other problems that can affect system reliability, performance and efficiency.
When we point out a problem, building managers sometimes tell us: “There haven’t been any comfort complaints or alarms, so we didn’t know that anything was wrong.” HVAC controllers are designed to compensate for varying input conditions and are somewhat tolerant of faults in other parts of the HVAC system, so building occupants may not notice that anything is amiss until a problem becomes acute.
But why don’t building automation systems inform the building operators about common faults? In fact, building automation systems are capable of reporting certain simple fault conditions to building operators or building occupants, but these systems are generally unable to detect or diagnose many important faults that are more complex. Why is this the case? There are two primary reasons:
1. It is common for installed building automation systems to have insufficient sensors to reliably detect or diagnose many important faults.
2. Detecting relatively complex fault conditions typically requires custom automation system programming, which is generally limited to the implementation of customer-specified sequences of operation.
#1 is an important problem in the HVAC industry, and often results from the “minimize first cost” objective on many projects. To illustrate this problem, let’s look at one algorithm frequently implemented in HVAC analytics software. This algorithm is used to detect a leaking heating valve in a built-up air handling unit, a relatively common problem that can result in wasted energy and reduced air handler cooling capacity. The heating valve controls the flow of hot water into the heating coil. If the heating valve has been commanded to be fully closed by air handling unit’s controller, then a significant air temperature increase as air flows across the heating coil indicates that the valve is probably not fully closed, allowing hot water to flow through the coil when it not needed or desired.
An algorithm that can detect this problem typically uses data from an air temperature sensor immediately prior to the heating coil and a temperature sensor immediately after the heating coil in the supply air stream, as well as the commanded position of the heating valve. However, if one of the air temperature sensors is missing (most likely the sensor between the heating coil and the cooling coil), then it will be more difficult to detect a leaking heating valve without a physical inspection. Why would one of the air temperature sensors be missing? Sensors that are not required to control the discharge air temperature and pressure may be omitted so as to reduce the initial cost of the air handler. Such cost cutting can be expensive in the long run because problems such as leaking valves can result in a substantial amount of wasted energy before they are eventually discovered and repaired.
But even if the necessary sensors are in place, reason #2 comes into play: building automation systems are not programmed to detect many important types of faults or to determine the root cause of those faults. To address the need for better system performance analysis, several companies (including my employer, Cimetrics) have developed HVAC analytics software that can perform the fault detection, diagnosis and performance analysis that few building automation systems can do, and the results can be eye-opening to building owners and facility managers.
Thanks in part to pressure from customers and regulators, manufacturers of HVAC equipment are gradually adding improved fault detection into their products. Studies performed over the past two decades in the United States have clearly demonstrated that air conditioning equipment often have significant problems that can be profitably addressed by appropriate maintenance. The energy savings that can be realized by repairing common problems in air conditioning equipment led the California Energy Commission to require that new air-cooled unitary air conditioning equipment with a capacity of 54,000 Btu per hour or greater sold in California be able to detect and report common economizer faults.
What I hope that you will take away from this article is the following: If we improve the transparency of building systems, building owners and facility managers will be able obtain information that will help them to make better decisions about how to operate and maintain those systems.Before making the decision to reduce project first cost by eliminating sensors from a new building automation system, building owners should discuss the benefits of those sensors for fault detection and problem diagnosis with their consulting engineer.
Here are two related articles from the New Deal blog:
Using Data to Improve Facility Operations, by John Petze.
Building Blocks for the New Deal, by Jim Lee.
Leave a Reply