Conserving Energy Use in Schools: Why Machine Learning and Predictive Analytics Will Decrease School Energy Budgets

By Jack Bullock  
Chief Engineer, PE, CEM, BESA

School districts need to cut energy use to enable reinvestment in education and meet the expectations of the public, as well as changing regulations. Although decreasing the school energy budget might seem like the easiest option, simply doing that is another ball-game. Conserving energy use in schools means encouraging students to make energy-smart decisions, take advantage of natural resources and much more. At the same time, schools may consider energy-efficiency improvements or the installation of automated systems, including motion-sensors, to prevent unnecessary energy use. Ultimately, the burden of deciding what actions to take could lead to decisions that adversely affect energy costs, but machine learning and predictive analytics can help.

Challenges in Conserving Energy Use in Schools

Education Facility Managers face multiple obstacles to conserving energy use in schools, including:

  • An average school age of 40 results in buildings with aging systems that are not energy-efficient.

  • Students and faculty may be resistant to changes necessary to conserve energy.

  • Manual system management makes energy conservation difficult at best.

  • Resistance from the school board due to misconceptions and myths about energy-efficiency improvements.

However, it is possible to overcome these challenges through the application of data and new technologies, including machine learning and predictive analytics.

Machine Learning and Predictive Analytics Highlight the Best Ways to Save

Machine learning and predictive analytics give school district officials and facilities management staff an extra layer of information to use in making decisions to conserve energy, explains Fiona Burlig of the Energy Policy Institute at the University of Chicago, via ForbesMachine learning and predictive analytics provide a data-based map for ways to get more value from upgrades to school assets and changes in energy use behaviors that will have the most significant impact on such savings.

In addition, the application of predictive analytics enable the automation of system controls, including the HVAC system, lighting and more, explains Dian Schaffhauser of Campus Technology. Automated systems effectively reduce the stress associated with energy management, resulting in better conservation of energy. Using machined learning and predictive analytics to conserve energy use lets education Facilities Managers focus their time and resources on encouraging energy use behavioral changes to further drive savings.

Benefits of Conserving Energy Use in Schools

Conserving energy use utilizing machine learning and predictive analytics in school district energy management offers additional benefits for the district, its faculty, and students, including:

  • More funds for use in other areas of the budget.

  • Encourages social skills by giving students a comfortable place to interact without higher costs.

  • Extension of school asset longevity, eliminating the uncertainty over when assets may malfunction and require replacement.

  • Compliance with government regulations, which are subject to change following any legislative cycle.

  • Improved building integrity, as well as enhanced safety of students and staff from improvements to air quality and preventing the growth and spread of potential pathogens.

  • Socially-responsible behaviors attract new students to the district, further strengthening the value of energy use behavioral change.

  • Low upfront investment costs make using machine learning and predictive analytics more affordable than ever for schools, especially those that have struggled to reduce energy costs and engage students.

Leverage the Right Technologies to Conserve Energy in Your District

The best practices for conserving energy use in schools may not necessarily fall into a one-size-fits-all mold. This is why it is essential to consider the unique characteristics and factors affecting your district. For example, Cenergistic's On-Site Energy Specialist takes on this role in ensuring maximum energy savings and conservation. Learn more about what your district can do to succeed in conserving energy by visiting Cenergistic online today.


Jack Bullock

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