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GE Digital (GE) (General Electric) > 实例探究 > Panama Minimizes Imbalance Penalties with Power Forecasting
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Panama Minimizes Imbalance Penalties with Power Forecasting

技术
  • 平台即服务 (PaaS) - 数据管理平台
适用行业
  • 可再生能源
适用功能
  • 离散制造
用例
  • 预测性维护
服务
  • 云规划/设计/实施服务
挑战
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.
关于客户
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.
解决方案
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.
运营影响
  • The implementation of GE’s Operations Optimization solution resulted in a successful outcome for Panama Group. The solution was provided as a service, aligning the interests of both the customer and GE. The new wind power forecast algorithm was able to achieve a forecast accuracy of 94%, which was 6% better than industry “best” benchmarks.
  • The hybrid architecture addressed the network connectivity challenges, ensuring reliable management of turbine data availability and providing closed-loop control.
  • The solution helped Panama Group meet the regulatory requirements set by India's Renewable Regulatory Fund (RRF), ensuring compliance and minimizing potential penalties.
数量效益
  • 94% forecast accuracy achieved
  • 6% better than industry “best” benchmarks
  • Lower imbalance penalties of $126K per farm realized annually

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