Improved Asset Utilization & System Design

Utilities today perform detailed studies to determine the expansion needs of their distribution grids to accommodate load growth. These studies are based upon current system load levels and forecasted load growth across the distribution system. While the system load levels are well understood (typically readings taken from SCADA data collected), the actual customer loads assumed in these studies is based upon calculated levels from TLM (transformer load management) systems that take kWh loadings on customer meters and determine an assumed peak load level. Unfortunately, TLM systems do not calculate the coincidence of peaks or the transformer loading level at the time of a system peak condition which is the most critical condition for planners to evaluate. Planners today are typically forced into making assumptions concerning loads at system peak load conditions that creates error in the methodology which typically translates into creating margin for error. A major enhancement to this current process is the utilization of customer load data now made available through installed AMI systems to take actual customer demand loads at specific peak load times to create circuit load models for use in these studies for system expansion. This more accurate representation of the utility grid will take some of the uncertainty out of the current analysis allowing the utility to plan to a tighter margin than previously. This will result in better utilization of the current asset base and a reduction in capital spending levels until the additional capacity resulting from the improved accuracy of the load model is consumed.

As the utilities today perform the studies to determine expansion requirements, they base their recommendations on the analysis of a few (several) options considered to satisfy the conditions being forecasted. A least cost economic selection of options is typically performed to generate a capital portfolio of work. A prioritization tool may be used to help a utility today rank their needs for capital spending. A major enhancement to this process is the use GRIDmaster to determine stress points on the system and then, using unique algorithms, determine the most cost effective solution to relieve stress conditions. An overall prioritized list of work required on the system is then generated where a utility can then match their available spending level with the project work identified.