Zielo Green

Energy Performance Indicators (EnPIs) are Key Performance Indicators (KPIs) that focus on energy use to help you measure, track, and improve how well you use energy. They show how energy use is related to one or more factors that affect it, like production output, hours of operation, or the weather. You can set EnPIs for one asset, one process, or the whole site.

In the past, EnPIs were calculated using static, single-factor correlations that linked one energy value to one variable that had an effect on it. This method is still common, but it is no longer recommended by current standards. Energy auditors are increasingly looking for more robust, data-driven methods.

Our statistical regression analysis is used to figure out modern EnPIs. This analysis can be multi-factorial and either linear or polynomial. This method takes into account several factors at once, which greatly improves the accuracy of the Energy Baseline (EnB).

Regression-based EnPIs also enable:

• More reliable energy performance tracking
• Accurate forecasting and scenario analysis
• Automatic replacement of missing meter data
• Faster detection and correction of energy non-conformities

This gives energy managers a better understanding of performance trends while still keeping an eye on compliance and energy efficiency.

With Zielo, it’s easy to look at energy data and keep track of performance according to ISO 50001. Load profile and peak analysis quickly show when demand goes up, when base loads are high, and when operations are not running as smoothly as they could be.

ISO 50001-compliant EnPIs also make sure that energy use is compared to production, operating hours, and/or weather. This means that improvements show real gains in efficiency, not just changes in activity.

By combining load profiles and EnPIs in one place, our platform gives you clear, useful information, helps you keep getting better, and makes reports that are ready for an audit in just a few clicks.

As required by ISO 50001, organisations must keep records to show that they found and fixed any gaps in their energy data without any unnecessary delays. There must be clear and reasonable explanations for any missing or incorrect energy data, and the method used to estimate data during the affected period must be clear and reasonable.

With our EnPI module, energy managers can automatically handle data gaps that happen when meters fail or measurements are interrupted. We use an ISO 50001-compliant regression analysis method to fill in missing values. This keeps Energy Performance Indicators and Energy Baselines consistent while also keeping audit traceability and data integrity.

ISO 50001 does not specify the types or brands of energy counters you need. Instead, it says that energy measurements must be accurate, reliable, and enough to support your Energy Management System (EnMS) and show that energy performance has improved.

Energy counters should be able to:

• Measure Significant Energy Uses (SEUs)
• Provide reliable data for EnPIs and Energy Baselines (EnBs)
• Support ongoing monitoring and analysis

This could include, depending on how you run your business:

• Main meters for electricity, gas, steam, or fuels
• Sub-meters for equipment, production lines, or processes
• Manual readings or virtual meters where appropriate
• Additional measurements for influencing variables such as production volume, operating hours, or weather

ISO 50001 also says that measurement tools must be calibrated, kept up to date, and documented, and that there must be a clear way to deal with any missing data. Our Counter Management and EnPI modules make it easy to handle this by supporting compliant documentation and data handling with smart data replacement.

ISO 50001 calls these metrics “Energy Performance Indicators” (EnPIs). EnPIs are usually based on data about how much energy is used, like electricity (kWh) or natural gas (m³), and they are adjusted for any factors that might affect them. Some common variables are hours of operation, output of production, or quantity of materials.

The EnMS standard allows and encourages the use of other relevant variables, like Heating Degree Days (HDD), Cooling Degree Days (CDD), or material moisture content, for more complicated energy uses. This makes sure that energy performance is measured under the same operating conditions.

An Energy Baseline (EnB) must be set up to measure and show progress in energy performance. The EnB gives us a number to use to compare changes in energy performance. The chosen baseline period must accurately reflect current operations and be underpinned by a statistically robust model, typically evidenced by a high coefficient of determination (R²), as mandated by ISO 50001 for dependable energy performance assessment.