LoadSEER

Integrated Spatial Load Forecasting for T&D Planning

What is LoadSEER

LoadSEER is a dynamic blueprint of the future of your electric distribution system.  The LoadSEER distribution, corporate planning and DER integration application is built on the most granular, frequently updated distribution load database and provides the user a multitude of efficient, automated circuit planning scenario capabilities, load shape forecasts and delivers accurate and valued insights for the continuous commissioning of the “grid edge”.  It’s not a sterile simulation engine or a study; it’s a data management platform that harnesses disparate, granular data sets to produce confident planning decisions about the distribution system.  The difference?  The user is the driver.  Your rules are LoadSEER’s rules.

LoadSEER is provisioned as a cloud-based Enterprise Service Bus, integrating geospatial, SCADA historian, AMI, customer billing, historical and forecast weather and the utility’s powerflow application to produce an econometric load and grid reliability blueprint that serve as the core forecasting and planning product for a utility.

LoadSEER Case Studies

Why Use LoadSEER

Why LoadSEER ?

The economic recession has made it tougher to forecast circuit and bank peak loads, and with the advance of micro grids, solar, DG, EV, and the smart grid push, the job of distribution planners is becoming increasingly complex. What happens when the economy returns?  Which economic drivers are the key ones for each of my circuits?   LoadSEER automatically models geographic and economic drivers, along with weather, to provide engineers with the most representative circuit by circuit forecast models.  In some cases, one circuit might respond to Retail Sales, while another might be sensitive to Employment, Personal Income, Housing Starts, or various combinations. 

We are finding that economic risk is now a larger threat than weather to circuit planning in many regions. And simplistic regression forecasts on temperature alone are inadequate, as the economic downturn has lowered loads more than weather variability.” -Tom Osterhus, CEO, Integral Analytics

Improve short-term accuracy and planning.

  • Normalize data for weather and economy (economic factors can be more influential than weather on some circuits and banks)  Improve handling of manual adjustments by engineers because EV, Solar, DG, micro grids are forcing more local complexity (mini IRPs)
  • Create Centralized Load Forecasting Repository
  • Automatic feed of forecasting results into the planning tool (DSMore, CYME, PowerWorld)
  • Archival of historical results/output supported with appropriate documentation
  • Integrate forecasting process across the corporate, transmission and distribution levels.
  • Improve the management, the consistency, and the use of input data.
  • Introduce enhanced review and approval process supported by appropriate documentation to support regulatory assessment. (e.g., more solar, DSM targeting)
  • Provide a transparent approach with detailed understanding of load growth and improve credibility with internal management.