Energy Analytics Explained: What is PredictEnergy™?

Energy Analytics Explained

Most people think that energy information, such as your current power draw or how much energy you use, is all there is to energy analytics. Not quite...
 
Useful energy analytics combine energy data with non-energy context information  (such as costs, production metrics, tariff, date and time, weather, etc) to provide you with actionable intelligence.

Ultimately, energy analytics are intended to guide you to take action to reduce your cost of energy and improve your efficiency and profitability.

energy analytics explained talks about PredictEnergyThe common approach to energy cost reduction focuses on basic energy efficiency, basically, to use less energy. This can be a good place to start. However, complex energy environments, constrained by complicated tariff rate structures require a more sophisticated and analytical approach.

Many energy cost reduction efforts fail because they neglect to take into account 2 crucial factors:

  • Energy use and generation must support the business and scale as business conditions change; and,
  • Energy cost reduction is not necessarily directly related to energy usage reduction.

Depending upon the tariff, reducing load may not save money, and simply shifting load to the wrong time can be expensive. Although business operating conditions may not offer a lot of flexibility, real energy analytics can help chart a path to success.

Energy Analytics Approach

Most people think that energy information, such as your current power draw or how much energy you use, is analytics. Not quite...

True energy analytics combines specific energy data with non-energy information, like costs, production and time, then performs calculations to put the results in context and provide the user with knowledge.

Ultimately, Analytics are intended to guide the user to take action; Action which can reduce their cost of energy and improve efficiency and profitability.

The common approach to energy cost reduction focuses on basic energy efficiency, basically, use less energy. This can be a good place to start, however, complex energy environments, constrained by complicated tariff rate structures require a more sophisticated and analytical approach.

Many energy cost reduction efforts fail because they neglect to take into account 2 crucial factors:

  • Energy use and generation must support the business and scale as business conditions change; and,
  • Energy cost reduction is not necessarily directly related to energy usage reduction.

Depending upon the tariff, reducing load may not save money, and simply shifting load to the wrong time can be expensive. Although business operating conditions may not offer a lot of flexibility, real energy analytics can help chart a path to success.

If reducing energy costs are a priority for your enterprise, PredictEnergy™ Analytics can help you determine what to do next. Checkout the full webpage to learn more.