Software AG > Case Studies > Enerjisa Üretim: Enhancing Clean Energy Efficiency with TrendMiner

Enerjisa Üretim: Enhancing Clean Energy Efficiency with TrendMiner

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Technology Category
  • Analytics & Modeling - Machine Learning
  • Analytics & Modeling - Predictive Analytics
Applicable Industries
  • Electrical Grids
  • Renewable Energy
Applicable Functions
  • Maintenance
Use Cases
  • Asset Health Management (AHM)
  • Predictive Maintenance
Services
  • Data Science Services
About The Customer
Enerjisa Üretim is a market leader in Turkey's private sector electricity generation, established in 1996 in Istanbul. The company is committed to maintaining a sustainable balance in power generation and has a diversified and efficient portfolio. With 850 employees, Enerjisa Üretim operates 21 power plants and has an installed capacity of 3.607MW. The company generates 56% of its power from renewable energy sources. Enerjisa Üretim's portfolio includes three wind power plants, twelve hydroelectric power plants, two solar power plants, three natural gas power plants, and one lignite power plant.
The Challenge
Enerjisa Üretim, a leading private sector electricity generation company in Turkey, faced several challenges in its operations. The company was struggling with data silos that hindered operational insights, leading to a lack of operational efficiency. The static diagnostics they had in place were insufficient for understanding the root causes of issues. With increasing pressure to meet sustainability goals, Enerjisa Üretim needed an affordable solution that would empower its operators to improve efficiency and performance. The company's diverse portfolio of power plants, including wind, hydroelectric, solar, natural gas, and lignite, added to the complexity of the challenge. The ongoing devaluation of the lira also made it crucial for the company to provide affordable clean energy, making better asset management a key factor for operational efficiency and cost savings.
The Solution
Enerjisa Üretim turned to TrendMiner's self-service data analytics to address its challenges. The company used this solution to analyze combined data sources from remote monitoring, internal systems, and time-series data from the past three years. Within a week, Enerjisa operators were able to establish four groundbreaking use cases for optimizing operations. These included correlation analysis of cooler and steam turbine performance, optimization of pump operations, and analysis of axial shaft position for predictive maintenance. The company also plans to use TrendMiner's Notebooks functionality, which uses machine learning to analyze complex operational data and create smarter dashboards for operators to interact with. This solution not only helped Enerjisa Üretim achieve operational efficiency but also empowered its operators to become data geniuses.
Operational Impact
  • The implementation of TrendMiner's self-service data analytics has brought significant operational benefits to Enerjisa Üretim. The solution has enabled the company to eliminate data silos, leading to improved operational insights and efficiency. The company was able to quickly establish use cases for optimizing operations, leading to more effective asset management and cost savings. The solution also empowered operators to interact with data and dashboards, enhancing their ability to understand and respond to operational issues. Furthermore, the use of machine learning for data analysis is expected to provide even more sophisticated insights, paving the way for smarter operations and tying into the company's sustainability strategy and ESG compliance.
Quantitative Benefit
  • Eliminated data silos within the company
  • Established four compelling use cases in under a week
  • Discovered a negative correlation (-80%) between the temperature and power output

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