The PowerRunner Energy Platform is a self-service data platform that allows business users to analyze and predict disparate scalar and time-series data sets, create data views unique to each business unit, feed defined data sets to other IT systems and operational technologies and create operational and executive dashboards that display relevant and actionable information. As the cornerstone to the PowerRunner business solutions PREP empowers business users with an intuitive solution to harnessing big data.


The PREP is a contextual business user layer that rolls-up operational sensor data along with data from other internal and external sources to present relevant and actionable information to business users in near-real time. The intuitive drag and drop navigation allows users to analyze and predict big data sets in support their unique operational requirements.

Business users can create standard analysis reports viewable by other team members, ad hoc reports for personal use and configure operational or executive dashboards from the drag and drop navigational functionality.

PREP Business

System Loss Analysis

The PREP provides system planners with granular locational and temporal load and generation data to support dynamic System Loss Analysis. By comparing the load and generation at each asset for each voltage class to the system load, the system applies loss algorithms that calculate the locational losses for every hour of operation.

Customer Segmentation

The hierarchical data architecture of the PREP provides business users with the ability to easily aggregate and segment asset load and generation, revenue and cost data to create unique customer segmentations by any defined physical or commercial attribute.

Coincident Peak Analysis

Granular load and generation data is evaluated for individual assets or an aggregate asset point and compared to corresponding system load data to analyze end use coincident and non-coincident peaks

Load Factor Analysis

The PREP dynamically calculates the load and generation factor of every asset or aggregate asset point on the distribution system to understand system diversity and locational loading trending analysis.

Power Factor Analysis

Reactive power measurements in the PREP calculate the power factor for each asset. Power factor variances outside of tolerances can be flagged and compared to substation SCADA data to determine the localized effects on the system.

Diversion Detection

When SCADA data is integrated in the PREP, users can analyze bottom-up vs. top-down load and generation measures to identifying anomalies in performance. Flagged assets with erratic usage will be alerted for further investigation.