Let us first look at what an energy management system really is and why do we need to move away from it. Simply put, an energy management system or (EMS) is a system of computer-aided tools used by operators of electric utility grids to monitor, control, and optimize the performance of the generation and/or transmission systems.
Such systems are also often used by individual commercial entities to monitor, measure, and control their electrical building loads. Energy management systems can be used to centrally control devices like HVAC units and lighting systems across multiple locations, such as retail, grocery and restaurant sites or any offsite store. Energy management systems can also provide metering, sub metering, and monitoring functions that allow facility and building managers to gather data and insight that allows them to make more informed decisions about energy activities across their sites, including things like managing overheads, safety and savings.
However, such systems have not evolved through time and thus they are in some sense, quite obsolete. EMS was around since 1990 but till now, not much has changed. EMS providers have not been able to keep pace with the evolution of technology, more specifically, the birth of cloud computing and the Internet of Things. Additionally, EMS was an effective tool as far as consolidating information and reviewing energy usage trends is concerned, however, they lack localization knowledge. For example, EMS knows the address of your building, but does not know its orientation, building usage pattern, or local weather.
Furthermore, EMS is limited in scope. It does allow remote control and consolidation but it is based on simple parameters. If you are genuinely seeking energy efficiency beyond that of scheduling or receiving alarms based on fixed parameters, you need a smarter system. EMS is a poor version of an automation system and it is not a self-learning system. It does not consider the energy efficiency ratio (EER) of any particular unit and thus, is not smart enough to consider how the actual performance compares to the expected performance.
We all know for a fact that many building owners today invest significant resources in environmental and building control systems. These systems can be very expensive to operate, yet essential for occupant comfort, productivity, and safety. Keeping systems operating at peak performance also reduces energy use and lowers utility costs, a growing concern for building owners worldwide. There exist efficient mediums to incur minimal costs and achieve maximum availability. The secret lies in the use of proactive and predictive maintenance based on the actual condition of equipment rather than a predetermined schedule.
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As the name suggests, with this approach in place, all equipments are consistently maintained at a continuously high level of performance. In addition, a predictive approach can be used to prioritize repairs and maintenance so that the most important systems are repaired first, so as to ensure the most effective return on investment (ROI). For example, in a predictive maintenance program, key operating parameters of equipment are quality checked regularly by staff or monitored automatically by sensors. The readings are then analyzed and used to evaluate the condition of the equipment and predict the future performance or likelihood of failure.
The key to predictive maintenance is that equipment and system condition determines what maintenance is performed, rather than a preset calendar or schedule. In predictive maintenance, there are no preset time frames at disposal when equipments are to be quality checked. This implies that repairs and maintenance are performed at the ideal time, resources are not wasted unnecessarily and equipments are maintained at a higher level of performance. This can extend the lifetime of a building by many years, increase safety from properly maintained equipment, ensure greater comfort and productivity for occupants, and better compliance with efficiency requirements.
Proactive and predictive maintenance score over EMS on multiple aspects and thus, this form of approach is a whole lot smarter and ensures real and measurable energy management. For example, a typical EMS takes into account 15-20 control points, typically within a 5 – 15 minute segment. However, a predictive solution that leverages cloud based algorithms can log hundreds of variables every minute! It’s not just building automation, its building intelligence.
Moreover, it is to be noted that predictive maintenance is not a tool, technique or certification but rather a philosophy that leverages the equipment’s operating condition to make data-driven decisions in real time and improve quality, productivity and profitability. The key promise of Predictive Maintenance is that it allows for convenient scheduling of corrective maintenance, and to prevent unexpected equipment failures. By knowing which equipment needs maintenance, maintenance work can be better planned. Other potential advantages include increased equipment lifetime, increased plant safety, fewer accidents with negative impact on environment, and optimized spare parts handling.
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Cloud technology and IoT has been a real game changer as it allows more data points to be collected, stored and analyzed in a meaningful timeframe. All these technologies are poised to play an instrumental role in building better predictive and proactive systems which will in turn make buildings more energy efficient.
Also, predictive solutions can increase your bottom line in more ways than one. Let’s take the HVAC system of a commercial building as a primary example. Making up more than 40% of the energy usage within a commercial building, HVAC represents the largest opportunity to increase efficiency and your bottom line.
A predictive solution that leverages cloud computing algorithms can deliver more than just energy savings. With the ability to take in hundreds of data points, a predictive solution has the ability to consider factors like weather forecast, building orientation, positioning of the sun, humidity, air quality and mean radiant temperature to deliver comfort, all the while saving energy. Imagine algorithms that can model the thermal envelope and air quality of your building, before sending out the optimal strategy to achieve the perfect balance.
Any day, a predictive solution can reveal to you more than just your energy usage. Performance evaluation provides insight into equipment performance, which can help predict equipment failures and verify service actions. This drives even further efficiencies and helps to increase your bottom line.
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Predictive maintenance is not a new term in the HVAC industry; it’s been around for decades. According to the U.S. Department of Energy (DOE), past studies on predictive maintenance have shown it can reduce maintenance costs up to 30 percent, eliminate breakdowns 70-75 percent of the time, minimize downtime, and increase production. Moreover, Smart and connected products have improved the effectiveness of predictive maintenance. These devices help building owners and operators by providing meaningful data. Those data can then be leveraged to improve building performance. By using periodic or real-time data from connected systems, facility management teams can be more informed about building operating conditions and allow for more targeted maintenance and repair efforts. Experts feel that predictive analysis will become more advanced as the analytics improve and it will go mainstream. After all, lowering a customer’s cost of owning and operating a building is what predictive analytics guarantees.
(Disclaimer: This is a guest post submitted on Techstory by the mentioned authors.All the contents and images in the article have been provided to Techstory by the authors of the article. Techstory is not responsible or liable for any content in this article.)
Image Credits: magazine.com
About The Author:
Gaurav Burman works with 75F as the VP & Country President, India. He was recently recognized as one of the 50 Most Talented CMOs in India in 2013 & one of the 100 Most Talented CMOs in the World by the US-based CMO Council.
Prior to Marketing, Gaurav spent 20 years of his life in Sales and worked with companies like PCL, IBM, L&T, APC & Schneider Electric. Gaurav has handled diverse portfolios including product management, alliances, channel sales, enterprise sales. He was a part of the Management Team at Schneider Electric, South Asia.