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January 2025
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Big-data analytics on State Grid SG186 and SG-ERP estates for resource analysis and decisions.
Dynamic monitoring of the full business process and efficient cross-discipline collaboration
Intelligent mining and analysis of data value; timely response to frequent business-application changes
Intelligent grid load forecasting to optimize grid resource dispatch
Use AI to improve grid resource allocation; analyze regional new-energy impact and weigh economic benefits for decisions
Standardized control of the full data process
Intelligent grid load forecasting to optimize grid resource dispatch
As demand for mining grid data value deepens, data-application methods continue to change, gradually shifting from traditional data applications that are single-discipline, single-data, simple processing, and mainly after-the-fact offline analysis toward cross-discipline, multi-data-type, algorithm-model applications with fast online response and real-time processing and more predictive complex data applications; data applications show multi-source, heterogeneous, fast agile processing and intelligent early-warning characteristics.
Based on big data, IoT, and deep-learning technologies, oriented to grid-resource forecast and warning and decision support; in large-scale new-energy integration, intelligent transmission and transformation, intelligent dispatch, intelligent distribution, intelligent consumption and interaction, and more, realize grid-resource dispatch optimization and disaster-defense emergency response, and optimize grid resource-allocation decision capability.
The platform integrates full-volume grid resource data, integrating wind resources, meteorology, precipitation, grid load, grid operating status, grid-related equipment, and more, forecasting power-energy distribution, disaster impact, and generation capability, and optimizing grid topology.
Integrate business, production, and equipment data across smart-grid generation, transmission, substation, distribution, consumption, dispatch, and enterprise operations.
Based on the big data platform, use deep-learning algorithms to forecast grid load in the next 24 hours, shorten the forecast cycle, and raise grid resource-dispatch efficiency.
Perform full-business multidimensional visual analytics on meteorology, wildfire, icing, load, grid topology, solar, PV, charging piles, new energy, and more to support grid energy allocation and dispatch.
Identify key factors affecting grid load and support decision-making for disaster response and dispatch.
Present provincial-grid core network equipment at 500 kV and above in 3D visualization, showing and analyzing overall grid-topology operation in real time.
Centralize on a unified platform, with full-freedom exploratory analysis, power-equipment (source–grid–load) facility information, grid operating status, power-market information, grid-related roads and streets, meteorology, and other natural-environment information.
+86 400-810-0466
international@sugon.com
津公网安备 12011602000521号
+86 400-810-0466
international@sugon.com
津公网安备 12011602000521号
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