| summary | Line Dashboards and AggregationData in Heimdall Cloud is presented based on an asset model of a power line, which consists of spans, phases, and measurement points. Data from the various measurements and models are aggregated to best represent the state of the line or span.This section provides a brief introduction to how data is aggregated and used in order to provide insight into the condition of the line. As an example the measured conductor temperature of a power line can vary widely across different spans. Heimdall's asset model for power lines makes it easy to aggregate this information so that only the most relevant information is provided through the dashboards or integrated into operational systems like SCADA, DMS, and EMS. With a fully instrumented line, operators are immediately notified of dangerous situations, eliminating guesswork. Operational decisions can be tested and verified through observation and lines are utilized to their full capacity. Why good aggregation is importantPower lines differ from other power system assets in their great extent and exposure to environmental conditions. A single power line can pass through valleys and mountains, across roads and rivers, yet, in many ways, it still needs to be operated and analysed as a single component.All lines will contain a few spans that are dimensioning for the whole due to their low ground clearance or exposure to environmental conditions. By instrumenting these spans, and observing the aggregated data produced from them, TSOs and DSOs can have full control over their power lines. How it WorksNeuron data is sent to our cloud-hosted solution where it is associated with a specific phase, span, and power line, along with contextual data on the operational limits of the power line, line properties, and weather data from the area. These are used as input to run models for SagClearanceDynamic Line RatingLine events Ice detectionVibrationsLine ForecastingObservational data are aggregated across multiple spans and in time. For the selected time interval, the system will by default present the max observed wire temperature and the average observed load. Aggregation of Dynamic Line Rating valuesHeimdall Power's DLR models are based on the CIGRE and IEEE standards, and enhanced with the addition of live data from the power line. By leveraging the theoretical strengths of the standards with observations from the grid, we have designed a proven DLR model with extremely high accuracy.To ensure accurate and statistically valid DLR values and forecasts for monitored linesDLR is calculated individually for each monitored span. The span with the lowest rating (critical span) defines the DLR for the line. DLR values presented in Heimdall Cloud are always aggregated by minimum, with a temporal resolution of 1 hour. This ensures that the weakest span is always accounted for while ensuring safe and consistent results for benchmarking and rating line performance and utilization. |
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Data from the various measurements and models are aggregated to best represent the state of the line or span.","fontFamily":"Open Sans, sans-serif"}]},{"type":"paragraph","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":""}]},{"type":"paragraph","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":"This section provides a brief introduction to how data is aggregated and used in order to provide insight into the condition of the line. 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Heimdall's asset model for power lines makes it easy to aggregate this information so that only the most relevant information is provided through the dashboards or integrated into operational systems like SCADA, DMS, and EMS. "}]},{"type":"paragraph","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":""}]},{"type":"paragraph","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":"With a fully instrumented line, operators are immediately notified of dangerous situations, eliminating guesswork. Operational decisions can be tested and verified through observation and lines are utilized to their full capacity. 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"}]},{"type":"paragraph","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":""}]},{"type":"paragraph","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":"A single power line can pass through valleys and mountains, across roads and rivers, yet, in many ways, it still needs to be operated and analysed as a single component."}]},{"type":"paragraph","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":""}]},{"type":"paragraph","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":"All lines will contain a few spans that are dimensioning for the whole due to their low ground clearance or exposure to environmental conditions. 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","fontSize":16}]},{"type":"paragraph","children":[{"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","fontSize":16,"text":"These are used as input to run models for "}]},{"type":"paragraph","children":[{"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serifThese are used as input to run models for ","fontSize":16,"text":""}]},{"type":"bulleted-list","children":[{"type":"list-item","children":[{"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","fontSize":16,"text":"Sag","lineHeight":"34px"}]},{"type":"list-item","children":[{"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","fontSize":16,"text":"Clearance","lineHeight":"34px"}]},{"type":"list-item","children":[{"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","fontSize":16,"text":"Dynamic Line Rating","lineHeight":"34px"}]},{"type":"list-item","children":[{"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","fontSize":16,"text":"Line events ","lineHeight":"34px"}]},{"type":"list-item","children":[{"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","fontSize":16,"text":"Ice detection","lineHeight":"34px"}]},{"type":"list-item","children":[{"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","fontSize":16,"text":"Vibrations","lineHeight":"34px"}]},{"type":"list-item","children":[{"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","fontSize":16,"text":"Line Forecasting","lineHeight":"34px"}]}]},{"type":"paragraph","children":[{"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","fontSize":16,"text":"Observational data are "},{"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","fontSize":16,"text":"aggregated across multiple spans and in time","fontWeight":700},{"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","fontSize":16,"text":". 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By leveraging the theoretical strengths of the standards with observations from the grid, we have designed a proven DLR model with extremely high accuracy."}]},{"type":"paragraph","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":""}]},{"type":"paragraph","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":"To ensure accurate and statistically valid DLR values and forecasts for monitored lines"}]},{"type":"bulleted-list","children":[{"type":"list-item","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":"DLR is calculated individually for each monitored span. "}]}]},{"type":"bulleted-list","children":[{"type":"list-item","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":"The span with the lowest rating (critical span) defines the DLR for the line. "}]}]},{"type":"bulleted-list","children":[{"type":"list-item","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":"DLR values presented in Heimdall Cloud are always aggregated by minimum, with a temporal resolution of 1 hour. "}]}]},{"type":"paragraph","children":[{"fontSize":16,"lineHeight":"24px","color":"#555","letterSpacing":0,"fontFamily":"Open Sans, sans-serif","text":"This ensures that the weakest span is always accounted for while ensuring safe and consistent results for benchmarking and rating line performance and utilization. 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