Article - Greenbyte

August 31, 2020 — Customer Stories

How CGN Europe Energy breaks down data barriers with manufacturers

CGN Europe Energy has built a 2.4GW EMEA portfolio worth €3bn, including a 75% stake in the 650MW Markbygden 1 project in Sweden. We hear from Jean-Baptiste Breban and Diego Coronado about how they use the deep insights into their turbines to break down data barriers with turbine manufacturers.

Caroline Mizael
Director of Marketing, Greenbyte

When Chinese utilities make moves in Europe, they generally go large. 

The most influential of these so far is CGN Europe Energy, a Chinese enterprise based in Europe, that was founded on 30th June 2014.

CGN Europe Energy’s main business includes the development, investment, construction, operation and maintenance of wind power, solar energy and other renewable energy projects, with assets spread across Belgium, France, Ireland, the Netherlands, Senegal, Sweden and the UK. To date, its total investment in Europe and Africa has exceeded €3bn ($3.3bn), while its total installed capacity now reaches 2.4GW.

The portfolio is made up of onshore wind farms in countries such as France, Sweden and the UK, and includes a 75% stake in the 650MW Markbygden 1 project. This is the first phase of the 4GW Markbygden complex in Sweden, which Bloomberg last month dubbed “the $8bn wind farm the virus couldn’t stop”.

In this article, we’re going to look at how CGN Europe Energy uses the Greenbyte Platform to break down data barriers at its projects. This includes examples of where CGN Europe Energy has used the system to diagnose faults that could otherwise have been costly. This is based on its presentation at the Greenbyte Forum in November 2019.

Exchanging insights

We were joined at the event by Jean-Baptiste Breban, supervision team leader at CGN Europe Energy, and Diego Coronado, mechanical and operation engineer. Breban started by explaining that CGN Europe Energy’s vision is to become one of the “leading renewables providers in Europe”, and that it doesn’t want to be just an investor.

“We want to operate and understand deeply our assets,” he said. The company currently carries out its own blade inspections and substation maintenance, while relying on turbine manufacturers or third party O&M provider to carry out maintenance on these machines. He said this tends to be dictated by contractual restrictions, quick growth management, diversity of technology and expertise.

“If you have a replacement [job that needs doing]… we cannot just say that: ‘You are taking so long, I will do it’,” he said. “we want to be reliable have clear data and analysis to present to have our partner understand that we all have the same goal and complementary competence to join for best wind farm performance.”

This means that CGN Europe Energy uses the Greenbyte system to identify faults and maintenance priorities, and to manage the flow of information between them and manufacturers: “It’s very complicated sometimes to get information from the turbine suppliers in a reasonable time with accurate data,” he said.

There is a particular risk of a data gap when a project operator has to rely on their manufacturer’s technicians to share information about turbines during inspections.

“The technicians are the eyes of the projects and they have all the information. For us, it’s very important to have direct contact with the technicians. We have a control room where we have direct contact, we have them on the phone every day, and we ask them detailed information to get the data and then to perform data analysis.”

Breban said it uses the system to collect data directly from turbines and findings from the manufacturers’ technicians, which CGN Europe Energy’s asset managers can then analyse and use to inform their decisions in daily operational meetings. They can then feed their insights into “strange behaviours” at turbines to the manufacturers’ technicians. 

This helps break down barriers to data exchange that can exist between the parties.

The system automatically creates warnings for anomalies where turbines stop for over 24 hours, all technical curtailments, grid failures, and communications failures. For more on managing communications failures, check out this ebook.

Digging deeper

Diego Coronado, who works on the engineering side at CGN Europe Energy, shared more information about how the Greenbyte Platform fits into CGN’s own engineering capabilities. He said that notifications from the system helped CGN to identify issues with components at high risk of failure and those that need more analysis.

This additional research that CGN can carry out includes laboratory analysis of oil or grease samples, and in-depth data analysis using the Python programming language. This can also provide it with vital insights to share with internal and external technicians.

For example, Coronado said Python was helpful if the company needed to analyse the power curve and whether it could see any fluctuations that may relate to failures. He said this enabled CGN to be more proactive when working with manufacturers – and identified two specific instances where Greenbyte’s analysis has helped.

Case study 1: Main bearing failure

The Greenbyte system had reported an alarm that had been set off because of a high temperature in the main bearing in a turbine at one of its wind farms.

This is not a typical alarm and carries a high risk of failure. Coronado said this meant that CGN could carry out an analysis of the bearing grease, which showed there was a high number of particles in the grease that were caused by wear and tear.

“We could see a lot of wear particles in the samples, so we could see there was a sick bearing, and then we could look at the past at how this turbine was behaving,” he said. CGN also carried out temperature analysis on the main bearing, and used Python to show a correlation between the bearing temperature and the performance of the turbine.

The company was also able to find a similar fault on another turbine at the scheme, where it had not yet received an alert. It then brought in the manufacturer to fix them.

“The main bearing replacement is a huge replacement because you need to remove the rotor,” he said, and added that it also meant the manufacturer had not had to pay out due to lack of availability: “They don’t want to lose money due to downtime.”

Case study 2: Gearbox failure

Coronado said CGN had received an alert that it needed to carry out maintenance on the gearbox in one of its turbines, because there was a high risk of damage.

This time he said the gearbox oil appeared to be in good condition, but the data showed that the number of particles in the oil was rising and a bearing should be replaced.

He said this meant CGN could carry out further analysis on the turbine and was able to avoid a potentially costly gearbox failure: “This damage can increase exponentially if we don’t act,” he said.

Identifying themes

Finally, he explained how CGN had used the data held in the Greenbyte Platform to monitor and classify turbine problems using a system that groups them into different types of problems. 

Coronado said this was important as it helped CGN to see connections between the specific issues that might exist in different turbine types. 

“This is important for us because we carry out reliability analysis, which will allow us to determine the downtime and the failure rate per component,” he said. “Maybe I have frequency converters that are failing and I don’t know why. But if I know which wind farms and which countries under which conditions are failing, maybe I can find a reason why it’s failing and avoid the failures.”

This helps with all assets, but particularly on older wind farms where CGN may need to take decisions on the profitability of short-term repairs versus larger investments in lifetime extension, repowering, or decommissioning. He said this information is even more important for companies with growing portfolios, as CGN has in Europe.

“When you start having a big fleet, like we are having now, these statistics are super-important for us.”

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