What Are Energy Analytics?

Energy companies, commercial properties, and even residences need a way to measure how much energy they’re using and what it’s being used for. Oil and gas companies need information about energy use to ensure safety and peak efficiency. Commercial buildings and homes also need energy information to operate efficiently and save costs. This is done through a process called energy analysis.

What are energy analytics, exactly? They are any method of determining how energy is used in an operational capacity in physical or chemical material processing or via energy conversion. In simpler terms, energy Analytics collects data about energy use and uses it to produce insights into consumption and time of use. These days, energy analysis can be performed with software solutions and computer algorithms to produce accurate data. Here are just a few ways energy analytics can be deployed and its benefits.



Energy analysis helps energy companies focus on specific regions for future developments based on multiple forms of data received. These days, planning is often about finding more ways to deliver clean energy and delivering it in the areas where it can make the most impact. This typically means deploying in large metropolitan areas, and energy companies work with cities to set goals for climate change adaptation, determine how to enact energy strategies, create ways for everyone involved to collect accurate data, and determine what other cities can achieve new energy plan.

Of course, energy analysis also helps industries and large organizations adopt clean energy and reduce their carbon footprints. Some major tech companies have become carbon neutral since 2007, and many more are making significant efforts to eliminate their footprints in the next ten years. Companies can achieve this by matching all electricity use with renewable energy, and some are looking to go a step further by only using renewable energy shortly. Since large cities produce the vast majority of carbon emissions, enterprise organizations and cities must effectively combat climate change.



Energy analytics is critical for companies to predict future energy needs, methods of production, and scenarios that may affect them. Such situations could include financial hardships, a more rapid push for renewable energy, or anything else that could interrupt normal processes.

Machine learning has been great for energy forecasting since complex computer algorithms are excellent at ingesting big data and producing consistently accurate insights. Machine learning programs can also predict the weather, sometimes weeks in advance, which can easily affect energy production. For example, if massive storms come over solar power grids, machine learning can predict how much power such grids will have available so that companies can adapt by preparing to rely on other sources.



Every company wants to operate at optimum efficiency, which is even more important for energy companies since so many others rely on them. Machine learning helps predict future costs and ways to cut them, improve manufacturing systems, and detect problems before they happen while also formulating ways to address them.

Energy analytics also help energy companies determine better power distribution methods so that more can be done for less. This also helps improve the usage time for assets, which is essential in a world that relies more and more on electricity, where the financial costs and other consequences of power outages can be dire.

Ultimately, energy analytics is a great way for power companies and those who rely on them to collect and analyze all relevant data in one place. This is similar to the software integrations happening as part of the digital transformations of companies worldwide. Data is one of the most valuable resources in existence these days, and proper analytics systems are the way to monetize it.