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Developing renewable energy asset management software for real-time performance tracking. Shifting from reactive to predictive maintenance for extending the assets’ lifecycle. Creating an adaptable system to accommodate upcoming expansions and innovations.
client
NDA Protected
Germany
45 employees
A growing renewable energy company handling wind turbines and solar farms faced scaling challenges, including performance variability and unplanned downtime. It needed renewable asset management software to optimize output, reduce maintenance costs, and ensure compliance with industry standards.
request background
Reasons to Implement Renewable Energy Asset Management Solutions
The renewable energy sector is growing rapidly, driven by the global shift toward sustainability and decarbonization. However, scaling up renewable assets like wind farms and solar power plants comes with operational complexities that require advanced technological solutions.
Effective asset management is essential for maximizing the performance and longevity of renewable energy infrastructure. Wind turbines and solar farms operate in dynamic environmental conditions, where even minor inefficiencies can compound into significant losses over time.
Without real-time insights and predictive analytics, companies face a range of operational and financial risks. Inefficiencies in energy production directly impact revenue. A single turbine or solar panel operating below capacity can result in significant annual losses.
Also, renewable energy companies must meet strict performance and reporting standards. Failure to comply can lead to penalties, legal issues, or loss of contracts.
To address these needs, the company needed a scalable, AI-powered renewable energy asset management tool. This solution would provide real-time performance tracking, predictive maintenance, and data-driven insights, enabling proactive decision-making and better asset management.
challenge
Challenges that Asset Manager Renewable Energy Can Overcome
The company faced significant challenges in managing its renewable energy assets.
Fluctuating energy output made predicting and optimizing production difficult, leading to missed opportunities in maximizing power generation. Without accurate forecasting, the company struggled to balance supply with demand.
Frequent equipment failures and inefficiencies caused unexpected shutdowns, resulting in energy losses and higher costs. The lack of an automated fault detection system meant that issues often went unnoticed until they led to major disruptions. Emergency repairs became more regular, adding to maintenance expenses and reducing system reliability.
Maintenance was another critical issue. The company relied on a reactive approach, servicing equipment only after failures occurred or following fixed schedules that didn’t account for actual asset conditions. This resulted in increased repair costs and shortened asset lifespan.
Data integration and monitoring complicated further operations. The company collected performance data from many sources, but it was difficult to consolidate and analyze it effectively. Limited visibility slowed decision-making and made identifying patterns or predicting failures difficult.
These challenges highlighted the need for renewable energy asset management software development. Such a system would track performance in real time, predict maintenance needs, and integrate data, helping the company optimize energy production and reduce downtime.
goals
- Minimize performance variability and ensure consistent, reliable energy generation.
- Use predictive maintenance to cut unplanned outages, boost reliability, catch issues early, and reduce costs.
- Centralize data on one platform for faster, smarter decision-making.
- Build a scalable renewable energy asset management platform to support future growth and expansion.
solution
Renewable Asset Management for Real-Time Performance Tracking
Node.js, TypeScript, NestJS, Express.js, PostgreSQL, Redis, RabbitMQ, GraphQL, WebSockets, Docker, Kubernetes, AWS (Lambda, S3, DynamoDB, EC2, RDS), Terraform, Prometheus, Grafana, ELK Stack, React, Next.js, Tailwind CSS
Ongoing- 7 specialists
During the discovery phase, we closely analyzed the client’s infrastructure and challenges to identify the reasons for performance variability and frequent downtime. The goal was to identify pain points and propose a solution that would enhance operational efficiency and sustainability.
Based on this analysis, we designed an AI-powered renewable energy asset management solution customized to the client’s needs and growth goals.
It integrates real-time data from wind turbines and solar panels, offering a comprehensive view of asset performance. With advanced analytics, the system monitors performance and provides predictive maintenance. This ensures early detection of potential problems before they lead to unplanned downtime. As a result, assets remain operational, minimizing energy production losses and reducing repair and maintenance costs.
A key feature of asset management for renewable energy is a centralized dashboard that brings together all the necessary data into a user-friendly interface. It provides real-time performance statistics and allows you to make informed decisions quickly. Data from various sources is seamlessly integrated into the platform, eliminating fragmentation and ensuring information accuracy and timeliness.
Scalability was a key factor during development. The platform was designed to be flexible, ensuring it can accommodate the addition of new renewable energy assets, expansion into new regions, or the adoption of new technologies. Its architecture allows the company to optimize its operations, adapting to changing industry requirements.
As a result, this platform provides the client with a powerful tool to monitor, analyze, and optimize the performance of their renewable energy assets. It also provides proactive management, leading to better operational results, reduced costs, and increased reliability.
- AI-powered asset management software renewable energy, integrating real-time data from wind and solar assets.
- Performance tracking and predictive maintenance through advanced analytics.
- A centralized dashboard for data visualization and decision-making.
- Scalability capabilities to accommodate future growth and new technologies.
outcome
Renewable Energy Asset Management for Predictive Maintenance and Optimized Performance
- 25% reduction in unplanned downtime through predictive maintenance and early issue detection.
- 15% extension in asset lifespan by shifting to proactive, condition-based maintenance.
- 20% increase in energy production through optimized performance and reduced inefficiencies.
client feedback
The team at Acropolium was highly collaborative, attentive to our unique needs, and delivered a solution that met our needs and supported future growth. We couldn’t be more pleased with the results and look forward to continuing our partnership.
