How can we report accurate and valuable data?


Data scientists are tired of spending lots of valuable working hours formatting data instead of doing the actual analysis and focusing on the reportable information. Even after the normalization process, it’s very common to find gaps and errors in the data collected. This process not only slows down the work of data scientists, but also affects the quality of decision making by asset managers or owners since KPIs might be based on invalid numbers.

As in many other sectors, in the wind energy business, data analysis is one of the most important parts to take into account when running a fleet of wind turbines. We need to analyze all information available to understand what is happening in our wind farms and if they are performing successfully. This is the only way for asset managers to verify whether they have achieved the desired production and revenue to meet every assets’ financial plan.


Green Eagle Solutions is focused on business orchestration and automated processes for the operations of wind farms and solar power plants. When referring to orchestration, various 3rd party data sources such as assets monitoring platforms, analytics services, spot market prices, weather services etc. are gathered in Green Eagle’s system to autonomously operate accordingly.

We want our clients to maximize their profitability and most of all, boost their workflows’ efficiency; that’s why Green Eagle’s data intelligence applications are published through standard open data protocols. This allows for data to be easily used in any commercial or in-house tool, from the well-known Excel to Power BI, Tableau or any other system.

Data is not only coming from different sources but each one might have a completely different format for real time data, event data, etc. Therefore, the normalization process after the data is collected is extremely important to be able to compare different assets’ performance correctly by making use of organized and manageable information.

The API’s performance itself is another important point. Robustness, reliability and high speed data flow architecture are some of the essential features that a data connection system should have. These characteristics will maximize the efficiency of the analysis processes whenever we make data queries, getting the right data in a few seconds. Moreover, each tool used in Green Eagle’s data flow process has data-saving procedures. By this way, despite any connection loss or system failure, they can automatically reconnect to the data origin to recover data. This grants our technology the essential property of fault tolerance.

Rarely have we had the pleasure of having such a reliable and efficient source of data as Green Eagle Solutions. It’s a very intuitive and fluid API.

Ana Patricia Talayero Navales, Responsible of diagnosis and generation facilities improvement at Circe.



From all data collected, we want to focus on the most important: operational performance and financial KPIs. Energy production, availability, energy losses, wind turbine efficiency or wind and solar resource are additional KPIs calculated by the system to enrich and give meaningful sense to the raw data captured. With this customized information, which shows the exact and valuable data that makes sense to asset managers or owners, they can analyze power plants’ performance and optimize their operational strategies.

As benefit margins become tighter and more competitive within the renewable energy industry, we must ensure we have the right tools and capabilities to carry out exhaustive analysis that allows us to identify improvement opportunities, however little they might be. Nowadays, making sure there is data that can be used in any desired tool, is a must for IPPs and ISPs.

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