Inferring power grid transformer to meter association using inconsistent geospatial data

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Having up-to-date and accurate geospatial data of a power utility company is critically important to maintaining the overall health of the power grid. Routine grid maintenance can change the physical topology of the grid; however, the subsequent update to the geospatial information systems may be forgotten or entered incorrectly by personnel. Some meters may have inaccurate or outdated transformer connectivity information (i.e., data identifying what transformer is directly upstream of a meter). Other meters may have an incorrect phase association. Without accurate data, Awesense is unable to provide important reports about energy balancing, theft analysis, load balancing, and transformer health information. The proposed research project brings together researchers from SFU and Awesense with the goal of developing computational methods to optimally find the inaccurate geospatial data in a utility's power grid information system by developing algorithms that quantify the confidence of meter connectivity and/or association information data. Outcomes from this project will be used to enhance Awesense's existing software services platform by adding new feature offerings.