SBIR-STTR Award

Many good load-estimation algorithms for the electricity distribution system have arisen from research activities, but they often are difficult for utilities to implement. This project will develop a customizable load estimation system, using OSIsoft's Historian with extensions to the IEEE Power Quality Data Interchange Format (PQDIF) standard, to collect and manage the data. In Phase I, the OSIsoft RtAnalytics package and the MathWorks Matlab product will be used to develop customizable algorithms for load modeling, estimation, and forecasting. The PQDIF will be enhanced to support the data necessary for load modeling. Host utilities and candidate algorithms will be identified for Phase II implementation. The end result will be a load estimation toolbox that is suitable for large-scale applications.

Commercial Applications and Other Benefits as described by the awardee:
Using the load estimation toolbox, researchers from universities or industry should be able to develop new modules as either OSIsoft or MatLab add-ons. Utilities that already use the OSIsoft platform, which amounts to 50-75% of the U.S. market, should find these modules easy to adopt and customize

Effective management of electricity distribution systems requires analysis tools that can estimate the state of the system (the operating condition). Although state estimation algorithms recently have arisen from research activities, they have yet to be adopted in practice. Utilities need an easier way to implement these new algorithms, along with tools that can pull together all the data needed for the analysis. This project will develop a branch-current state estimation algorithm that is suitable for large-scale applications. The algorithm will be deployed on a large-scale data historian software system, which provides access to a large volume of measurements to support state estimation. In Phase I, the framework for deploying advanced state and load estimation algorithms to utilities was specified. A suitable research-grade state estimator was identified, and its interface to the deployment framework was tested. In Phase II, a configurable mapping to measured data will be developed, and then deployed and tested at an electric utility. Applications and Other Benefits as described by the awardee: The algorithm should allow researchers from universities or industry to develop new modules as add-ons to the industry-leading data historian software for electric utilities, enabling better operation of the electric power distribution system. In the future, the same basic framework should support additional data collection from automated meters and power quality monitors, thereby leveraging the use of these measurements.