Trading New Energy Vectors Toward Net Zero 1
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Creating Accurate Short-Term Energy Generation Forecasting

Enhance forecasting accuracy and grid reliability by integrating real-time data, automation, and advanced analytics into renewable energy generation planning
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Inaccurate and fragmented renewable energy forecasting limits grid stability, reduces operational efficiency, and constrains the ability to optimize market participation in increasingly dynamic energy systems
WHY THIS “CREATING ACCURATE SHORT-TERM ENERGY GENERATION FORECASTING” CHALLENGE?
From fragmented data to reliable, real-time forecasting intelligence

Disparate data sources, limited automation, and inconsistent data quality reduce forecast accuracy and hinder effective nomination, scheduling, and operational decision-making.

Key benefits
Enabling precision and reliability in renewable operations

Accuracy, automation, and scalability

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Improved forecasting accuracy for renewables

Leverage real-time and historical data to enhance prediction precision for wind and solar generation

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Greater grid stability and operational reliability

Support balanced supply-demand management through more reliable forecasts

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Increased efficiency through automation

Reduce manual intervention in nomination and scheduling processes

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Stronger data integrity and standardization

Ensure high-quality, interoperable data aligned with industry standards

How NTT DATA helps

01
Enhancing forecasting platforms with advanced capabilities

Strengthen day-ahead and intraday prediction models through integrated solutions

Deploy advanced analytics and forecasting
02
Integrating real-time and historical data sources

Leverage PI Historian data to provide detailed asset performance insights

Scaling Renewable Energy Pipelines with Data-Driven Site Identification
03
Applying CIM-based data standardization

Enable consistent data exchange and improved interoperability across systems

Trading New Energy
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Implementing automation and anomaly detection

Improve accuracy through continuous validation and performance monitoring

Green Allocation
05
Building scalable, future-ready architectures

Facilitate onboarding of new assets and data sources with minimal complexity

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Substation Electrical
Proven impact
Improving forecast accuracy and grid stability through data-driven, automated renewable energy intelligence
Results that matter
Measurable improvements in accuracy, efficiency, and system reliability:
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Higher accuracy in renewable energy forecasts

Improved data integration and validation enhance prediction precision

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Enhanced grid stability and reliability

Better forecasting supports balanced and efficient energy system operations

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Reduced manual effort in operational processes

Automation streamlines nomination and scheduling activities

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Scalable integration of new assets and data sources

Flexible architecture supports future growth and system expansion

Improve forecasting accuracy and grid performance with advanced data capabilities

Enhance reliability and operational efficiency

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