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Resource Planning & Revenue Analytics

Resource Planning

Locational Resource Planning

PowerRunner’s micro forecasting and analytics allows system planners to consider the locational effects dynamic loads have on resource planning.

  • Understand the impact of distributed energy resources, demand response programs and changing consumer habits on resource planning

  • Evaluate the impact of load and generation growth and DER penetration on all distribution system assets

  • Dynamically model local resource requirements based upon actual historical and forecasted load, as well as any DER data for each local circuit

Dollar Bills

Rate and Revenue Analytics

Use PowerRunner to support cost of service studies and rate case development.

  • Develop new and innovative rate structures that represent the true cost of service to all customer classes.

  • Model new rate structures with historical and forecasted service point data to:

    • Analyze impact of new rates on each rate class

    • Evaluate cost of service for new rider

    • Appropriately price ancillary services

  • Combine service point  usage data, and billing determinant charges, to develop a line item by line item breakdown of charges for each service point per rate class. ​


Distributed Energy Resource Integration

Our Predictive Analytics solution provides DSOs with load and generation forecast data for every asset on the distribution system to support operational decision support management generation forecasts on every system asset.

  • PowerRunner can help Distribution System Operators physically integrate intermittent assets while maintaining system fidelity.Aggregate asset forecasts by circuit, substation, or other spatial attributes to analyze the impacts of DER assets on other local system assets

  • PowerRunner delivers near-real time net load and generation data for each DER asset.

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Unbilled Energy

PowerRunner can carry out detailed analysis of intra month unbilled revenue reduce to unbilled energy estimation error and revenue restatements.

  • Significantly reduce unbilled energy estimation error and revenue restatements by  dynamically calculating the Unbilled Energy within any given time period.

  • Replace highly manual, tedious and error prone process of reconciling  monthly revenues by using our automated product offering.

  • On demand daily vs. monthly reconciliation of unbilled energy revenue provides greater confidence in revenue projections.

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