5 Reasons Why Machine Learning + Big Data = Smart Energy Management
Machine learning and big data form the ingredients for smart energy management systems. However, these technologies, although extraordinary, will always rely on input and information from people. The way in which information is contributed reveals the unique relationship between the intuitive, self-learning technologies and school facility management; someone will be necessary to generate the data, even if it means turning the heating on when it is usually the most inefficient use of resources. If that sounds confusing, you are on the cusp of understanding machine learning and its role in smart energy management. It’s an exceedingly complex topic, but its potential must not be ignored, especially considering the key reasons it’s the best possibility for smart energy management.
Technology Continues to Evolve and Increase in Capabilities, Creating More Data
As noted by Energati.com, the average internet-enabled device has a lifespan of four to five years. As consumers move toward newer, smarter devices, the opportunity to collect more data increases. Users are also heavily involved in controlling their environments. In schools, the use of machine learning and big data can help school systems predict energy demand, adjust system settings to maximize comfort and save money through energy-efficient processes.
Aging Infrastructure Demands Smart Energy Management to Maximize Use-Efficiency
The aging infrastructure of America plagues all aspects of life. Pipes are worn and brittle. Electrical lines lose conductivity. Buildings are crumbling, quite literally in some cases, and the average of a school building is 40-years-old! It's a significant problem and a harbinger of energy waste.
Big data and machine learning will team up to tackle this problem. According to Smart Grid, the U.S. electricity grid will warrant $2 trillion in upgrades by 2030, so since funds to repair the grid are out of the question, at least temporarily, school Facility Managers must start thinking about how they can apply technology to ensure schools remain open and use energy efficiently.
Until full upgrades to the infrastructure are made, the best facility management programs will be forced to “make do.” Fortunately, knowing the right ways to update facilities and maximize use of resources, including energy, lies in the application of smart energy management.
Big Data and Machine Learning Enable Scalable Energy Management
As noted by Power Engineering International, change in energy demand and management will be exponential over the next eight years. The amount of change and the value created is set to bring decarbonization to the corners of the globe. Power producers and distributors are focusing on how to squeeze more use from every kilowatt hour. Governments of all sizes and geographic differences move to embrace energy conservation efforts. Economic growth will also affect the growth of smart energy management and demand for more efficiency and productivity. It boils down to the need to enable scalability, and to reap such rewards, big data and machine learning will allow the introduction of new technologies and algorithms to keep up with advancement. For Facility Managers that are still not convinced, consider the five ways machine learning and big data can enhance energy management:
More facilities’ energy data can be analyzed without detracting from responsibilities of management team members and used to define issues and possible solutions.
Machine learning allows for the continuous refinement of algorithms to determine best-case results, as well as determine the best course of action to achieve such results, reports Adam C. Uzialko of Business News Daily.
Big data is growing in scope, and handling it with machine learning will find correlations and patterns that are infinitesimal.
Insights gleaned from big data and machine learning is used by automated technology, including robotics and artificial intelligence, to adjust system settings for improved energy efficiency.
Smart energy management will grow smarter, providing insights that were never conceptualized or imagined, and humans will see it all happen behind the scenes, viewing metrics and KPIs to gain a quick, 360-degree view of operational efficiency.
Forecasting Is Essential to Storage, Distribution, and Use of Renewable Energy Resources
The value of smart energy management is found in taking advantage of available energy resources and using them with reason. Some forms of energy require storage before use, such as storing energy generated from solar power for use during night hours. Unlike non-renewable energy resources, renewable energy sources cannot simply be turned on or off; they depend on the environment at any given time. Therefore, forecasting of energy demand is crucial to ensuring the proper storage, distribution, and use of renewable energy resources. If enough energy is not stored correctly, organizations and schools that need to tap into it cannot unless they know how much should be stored in the first place.