Panama Minimizes Imbalance Penalties with Power Forecasting
_30.jpg "GE Digital (GE) (General Electric) Logo")
Company Size
1,000+
Region
- Asia
Country
- India
Product
- GE’s Operations Optimization
Tech Stack
- Cloud hybrid architecture
Implementation Scale
- Pilot projects
Impact Metrics
- Cost Savings
- Productivity Improvements
Technology Category
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Renewable Energy
Applicable Functions
- Discrete Manufacturing
Use Cases
- Predictive Maintenance
Services
- Cloud Planning, Design & Implementation Services
About The Customer
The customer in this case study is Panama Group, a power generation company based in India. The company operates in the renewable energy sector, specifically in wind power generation. They were faced with the challenge of meeting regulatory requirements set by India's Renewable Regulatory Fund (RRF). These requirements necessitated accurate weather data forecasting, which was a challenge due to unreliable site connectivity. The company needed a solution that could manage turbine data availability and provide closed-loop control.
The Challenge
Panama Group, a power generation company based in India, was faced with the challenge of meeting India's Renewable Regulatory Fund (RRF) regulatory requirements. The company needed to determine the quality and resolution of weather data for forecast accuracy. However, they were dealing with unreliable site connectivity, which made it difficult to manage turbine data availability and gain closed-loop control. The challenge was to find a solution that could address these issues and help the company meet its regulatory requirements.
The Solution
To address the challenges faced by Panama Group, an initial pilot of GE’s Operations Optimization solution was implemented on one of their wind farms. This wind farm consisted of 44 Wind Turbine Generators (WTGs) and had a capacity of 70 MW. The solution involved the development of a new wind power forecast algorithm that was capable of predicting outcomes 1–4 hours in advance. To address the issue of network connectivity, a hybrid architecture was used that combined on-premises and cloud technologies. This solution was designed to meet the company's specific needs and help them achieve their goals.
Operational Impact
Quantitative Benefit
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