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Using Energy Analytics

Energy Analytics

Using energy analytics for a cost down program starts with monitoring energy usage and demand, but many facility owners do not collect or retain their own energy information. Even a brief historical platform can go a long way towards establishing the essential relationship between the key performance indicators (for example, kWh per unit produced, or cost to store 1000 SKUs for 1 day, etc) that drive energy costs.

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Energy Map

The next step is to track energy costs in real-time, and create what HelioPower calls the "Energy Cube."  The Energy Cube is a three dimensional map of the following information:

  1. Energy and Power by date, time and location
  2. Production or distribution volume by date, time and location
  3. Tariff

However, once the relationships are established, the principal objective is to understand how to analyze this data to reduce energy cost going forward.  That's the focus of HelioPower's predictive energy analytics platform, PredictEnergy™.

Energy analytics management programs are well known; load shifting, load sharing, demand response, renewable energy production, energy efficiency measures and tariff adjustments to name a few.  But understanding how to use the information to determine the best energy program by predicting results to maximize savings is the real challenge.  What energy program strategy provides the best outcome for a facility’s specific demand, usage and circumstances?

What To Work On First?

This is where predictive energy analytics comes in.

There is general agreement that without real-time and historical knowledge of energy usage and demand data, that the options to reduce load and cost are limited.  Analytics provides the understanding of where improvements are needed, the measurement and verification of improvements performed, and optimization of energy programs to solve for best outcome and predict results. HelioPower's energy analytics engine PredictEnergy™ is designed to maximize savings and to optimize energy production and reduction with maximum return.

using energy analytics explanation

Our predictive energy analytics software solution has three phases in deploying successful long term energy cost reduction strategy.  To learn more please download our PredictEnergy™ Implementation Phases from the Download Library.

3 phases of using energy analytics