
๐๐ป๐ต๐ฎ๐ป๐ฐ๐ถ๐ป๐ด ๐๐ ๐ฆ ๐ฃ๐ฒ๐ฟ๐ณ๐ผ๐ฟ๐บ๐ฎ๐ป๐ฐ๐ฒ ๐ง๐ต๐ฟ๐ผ๐๐ด๐ต ๐๐
๐๐ฒ๐ฟ๐ป๐ฎ๐น ๐ก๐ฒ๐๐๐ผ๐ฟ๐ธ ๐ ๐ผ๐ฑ๐ฒ๐น ๐ฅ๐ฒ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป ๐๐ป๐๐ฝ๐ถ๐ฟ๐ฒ๐ฑ ๐ฏ๐ ๐๐ต๐ฒ ๐๐๐ฐ๐ฐ๐ฒ๐๐๐ณ๐๐น ๐ถ๐บ๐ฝ๐น๐ฒ๐บ๐ฒ๐ป๐๐ฎ๐๐ถ๐ผ๐ป ๐ฎ๐ Duquesne Light Company (DLC) The Opportunity: Simplifying Network Models to Improve Real-Time Reliability Electric utilities rely on Energy Management Systems (EMS) to provide accurate, real-time insights into the condition of the power grid. A core component of this is the State Estimator (SE), which calculates system status using real-time data and a detailed network model. However, many utilities over-model external systemsโthose parts of the grid outside their ownershipโwhich leads to: โข Slower EMS performance โข Unnecessary maintenance complexity โข Increased data dependency on external entities โข Reduced system observability and responsiveness This presents an opportunity to streamline EMS performance by reducing the complexity of external network modeling, without sacrificing accuracy. Our Approach: Targeted Model Reduction Based on Operational Impact. Utilicast leverages a proven, practical approach inspired by DLC, which achieved a 53% reduction in modeled external elements and dramatically improved EMS performance. Key Steps in the Approach: 1. Boundary Identification – We define โcore,โ โnear-neighbor,โ and โexternalโ zones based on regulatory guidance (e.g., NERC TOP-001). 2. Impact Assessment Using Line Outage Distribution Factors (LODFs) – We simulate line outages to identify external components that meaningfully affect the internal system. Only significant components are retained. 3. Model Reduction & Equivalencing – External components with low impact are replaced by simplified equivalents, using real telemetry where applicable. 4. Validation & Monitoring – Automated validation and custom dashboards track estimation quality, model health, and convergence performance across the network. ๐ง๐ต๐ฒ ๐ฉ๐ฎ๐น๐๐ฒ: ๐ฃ๐ฒ๐ฟ๐ณ๐ผ๐ฟ๐บ๐ฎ๐ป๐ฐ๐ฒ, ๐๐ณ๐ณ๐ถ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐, ๐ฎ๐ป๐ฑ ๐๐ผ๐บ๐ฝ๐น๐ถ๐ฎ๐ป๐ฐ๐ฒ By simplifying external network models, utilities realize: โข Improved State Estimation Accuracy (6% increase in SE quality at DLC) โข Faster System Response (11% fewer iterations required) โข Reduced Operational Complexity โข Easier Model Maintenance โข Alignment with NERC Standards โข Enhanced Situational Awareness through targeted dashboards Duquesne Light Companyโs experience demonstrated that a streamlined model leads to a more reliable and resilient grid, with fewer errors, less volatility, and greater operational confidence. Utilicaster, Kiamran Radjabli, and Chad Hirsh from DLC, co-wrote and presented a paper at EEEIC (European chapter of IEEE) in early July detailing all this. |