Air Conditioning Units

5 Reasons You Need Visibility Into Your HVAC Systems

In today’s world, commercial buildings account for more than 35 percent of the total energy consumption. In most commercial buildings Heating, Ventilating and Cooling (HVAC) consumes more than 30% percent of the total energy use.

Commercial buildings owners and facility managers are challenged with getting financial returns from their investments while providing a building that is energy efficient.

Improving efficiency of HVAC systems has been a focus point by energy industries and academicians. Traditional methods of using statistical approach no longer work as HVAC systems have become complex, non-linear and dynamic.

The rapid development of Internet of things (IoT) technology, sensors, big data solutions, wireless and network solutions, cloud computing has led to the collection of large amounts of data that has created many data analytics solutions that are replacing traditional solutions.

Data analytics and big data solutions have gained popularity with the advent of smart equipment and digitization of HVAC systems. This data can be used for optimizing and controlling the HVAC systems.

Data analytics done right for the HVAC systems could help owners save energy consumption and money that would have been otherwise used in purchasing unnecessary equipment or to replace outdated equipment.

Data analytic tools help facility managers make informed decisions on how to fix their equipment before it breaks down completely.

Issues such as faulty equipment, poorly tuned loops, and additional equipment operations in most commercial buildings can be addressed using the right data analytics tools.

Facility managers are increasingly using Building Management Systems (BMS) to collect data about the performance of the building as well as energy consumption by individual equipment such as HVAC.

According to Cara Ryan, offer manager, building performance center at Schneider Electric, through data analytics, facility managers can make informed and actionable decisions in solving problems and also save energy costs. She mentions that data analytics could help facility managers save more than 20 percent yearly which could be used for maintenance of equipment and achieve optimal building performance.

According to Sudhir Sinha, Snehil Taparia and Swarup Biswas of Johnson Controls, data analytics helps to better understand various aspects of a commercial building and the performance of all equipment located in it. Data analytics helps with historical trending, pattern recognition and correlation between cause and effect of issues of events occurring in the HVAC subsystems. It also helps in benchmarking HVAC system performance against industry standards.

The most important step is deciding to use data analytics effectively by identifying the processes that need to be improved or worked upon.

Let us look at some of the reasons that visibility into this data can help driving the maximum efficiency of your HVAC systems.

1. Comfort of Indoor Environment:

The importance of HVAC system in commercial and residential buildings cannot be overemphasized.

The fact remains that fresh air is good for the body and in commercial buildings it helps improve productivity.  A good ventilation system helps to reduce the number of pollutants, bacteria, and odor in a building.

Data analytics of your HVAC systems helps in regulating the temperature of a building and lowering humidity, by ensuring that moisture in a building is kept under control. Good ventilation systems remove breeding grounds for dust mites, which contribute to causing eczema.

The American Society of Heating, Refrigeration, and Air Conditioning Engineers (ASHRAE) conducted research that led to Standard 55: Thermal Environmental Conditions for Human Occupancy. Standard 55 describes how to assess comfort from specific measurements and predict when most people will be comfortable.

Data analytics of your HVAC system provides real-time data that helps in maintaining this standard and prevent any setbacks.

2. Energy Efficiency:

Operating a HVAC system at optimum efficiency is a challenging endeavor. The number of set points, levels, and feedbacks of boilers, chillers, pumps, fans, air delivery components and more can cause costly inefficiencies. Add to that the fact that weather variables affect the heat transfers in a building and increase loads on the HVAC.

Data analytics will provide visibility into your HVAC system with sufficient accuracy that will help you take corrective action and reduce the energy demands and peak load distribution of your HVAC systems.

Facilities Net states that HVAC system maintenance in commercial buildings is responsible for saving more than 40 percent of energy, therefore it is essential to utilize data analytics in understanding the effects of malfunctioning HVAC systems on energy use, energy consumption and energy demand.

3. Improve indoor air quality:

According to Environmental Protection Agency (EPA), poor indoor air quality is among the top factors of environmental risk. Pollutants in the air can aggravate allergies and asthma in some people and cause dizziness and headaches in others.

Air quality depends on various factors like people entering the facility, use of other equipment and presence of electronics. With the proliferation of cheap sensors, air quality data is now being accurately measured.

This visibility into the data can help adjust your HVAC system to improve the air quality. You can develop a maintenance plan that includes the following for your HVAC system:

  • Inspection, serving, and cleaning
  • Replacement of parts
  • Documentation of procedures and
  • the Calibration of components control system

Combine this with the data analytics of the performance of the ventilator and air handler in your HVAC, to produce indoor air quality results that are essential for your building size.

4. Preventive Maintenance:

HVAC systems are often operating at suboptimal levels at least 40% of the time in buildings. This is due to the complexity of the buildings as well as many moving parts like fans, pumps, air-conditioners, ventilators, dampeners and many more.

Faulty HVAC systems lead to occupant discomfort, increase energy consumption, reduced air quality and equipment deterioration.

Building management systems (BMS) use simple detection techniques producing too many alarms that are often ignored.

Hence data driven techniques for HVACs is increasing becoming popular.

Data analytics uncovers the following problems of your HVAC system:

  • Additional HVAC runtime
  • Poor control settings and programming errors
  • Stuck dampers causing excess outside air intake
  • Valve leakage leading to uncontrolled supply-air temperatures
  • Outright equipment failure

The two types of analytics are:

  • Predictive Analytics: This is used to inform you about what will happen, for example, a predicted increase in the entire building’s power consumption, i.e. a demand risk.
  • Prescriptive Analytics: This informs us about what should happen and often give recommendations for the best course of action for a given situation.

5. Actionable Insights:

Data analytics provide essential insights to help with monitoring, controlling and maintaining your HVAC systems.

In the absence of this type of information, facility managers physically perform manual audits that are inefficient and time-consuming.

With the advent of Internet of things (IoT), more sensors are being used in buildings for various equipment. The data analytics out of this ocean of data can help you determine the best course of action to take to maximize efficiency from your HVAC system.

You can also analyze the information in various ways to better understand the opportunities it presents. For example, you can look at the normalized data for your building type, square footage, schedule and climate.

You can also slice and dice the data to better understand energy consumption based on building occupancy and time, thereby identifying peak demand reduction opportunities.

You can prioritize the HVAC activities by comparing normalized energy usage with respect to industry standards as well as by calculating various energy conservation measures.

 

Conclusion:

In summary, the use of data analytics is on the rise for managing and maintaining energy efficiency in buildings.

Since HVAC is the largest consumer of a building’s energy, data analytics can be used to optimize their performance and make a huge impact on your building’s energy goals.

Data analytics is the key to unlock various insights of your HVAC like comfort of indoor environment, energy efficiency, improving indoor air quality, preventive maintenance and achieving actionable insights.

It is powerful because it enables you to better understand your HVAC performance and improve your return on investment on this expensive equipment.

 


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