Unlocking Insights: Transparent Energy Production and Losses Analysis
About the project
We are experts in providing innovative software solutions that empower businesses to optimize their operations and drive growth. Our expertise lies in mastering the power of cutting-edge technologies such as Python, Azure Stack, Big Data, and more to deliver tailored solutions that meet our client's needs. In this case study, we tell the success story of how we helped our client to provide transparent insights into energy production and losses, revolutionizing their approach to energy management.
Location
Nordics
Team Size
4
Industry
Green Tech, Renewable Energy
The Challenge
How can we understand what are root causes and drivers in energy production?
Our client, a leading energy provider, faced the challenge of inefficient energy production and significant losses across their operations. Lacking a comprehensive understanding of their energy usage and distribution, they struggled to identify the root causes of these inefficiencies, leading to increased costs and decreased profitability.
This is what we did
The tech we used or pills: Front end, Back end, Analytics, Product Design
Harnessing the capabilities of Python, Azure Stack, and other advanced technologies, we developed a custom solution to address our client's challenges. Leveraging Azure Data Factory and Azure Data Lake, we collected and processed vast amounts of data from various sources, including sensors, meters, and production units.
Using Databricks and Elastic Search, we performed advanced analytics to uncover patterns and anomalies in energy production and consumption. Our analytics dashboard provided real-time insights into energy usage, enabling our client to identify inefficiencies and areas for improvement promptly.
We are processing more than 6 years of energy production data, combining it with weather and geographical data and using calculation model which generates 10 minutes records where we have deep dive analysis of energy production.
The data is later aggregated daily and imported into Elasticsearch database which we use for searching and filtering the data.
Our frontend application is also a part of one large eco system of micro-fronted applications widely used inside the company.
Backend API is running in Kubernetes (k8s), it is written in latest C# a .NET Core framework and implemented CQRS and Mediator Design Pattern.
Business Results that we achieved
Through our collaboration, our client achieved significant improvements in energy efficiency and cost savings.
We enabled users to filter and view segment data, stored in cloud, and to attribute individual “root cause” and its effect to energy production. Whether it’s blades friction, ice, impact of side winds, etc. Our customer is now able to visualize, conduct analysis and implement remedy actions.
We helped our client to process very large amount of data, and to use it in everyday work.
By implementing our solution, they were able to process:
Process the last 7 years of data, from 6 regions, 67 counties, 2950 sites and over 47000 turbines. 111 different turbine models are covered.
The total data size was over 1 billion records of daily aggregated data. More than 500GB of data processed.
By implementing our solution, our client achieved
Togetherness in pursuit of excellence.
Our transparent approach to energy production and losses analysis empowered our client to make informed decisions, optimize their operations, and drive sustainable growth.
At Codetiq, we are committed to delivering transformative solutions that drive measurable results for our clients. Our success in providing transparent insights into energy production and losses is a testament to our expertise in software development and our dedication to client success.
Contact us today to learn how we can help your business reach excellence through innovative technology solutions. What can we help you with?
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