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Developing advanced renewable energy asset management software for comprehensive solar monitoring and wind monitoring operations. Our expertise includes SCADA integration, predictive maintenance algorithms, KPI dashboards, real-time alerts, IoT sensors deployment, asset performance management, anomaly detection systems, condition-based maintenance, OPC UA / Modbus protocols, and digital twin technology.
client
NDA Protected
Germany
45 employees
A fast-growing renewable energy company operates wind and solar farms and is challenged by scale to manage performers such as expensive idle time. They needed renewable energy asset management software to optimize output and reduce maintenance costs. Requirements included solar tracking capabilities, wind tracking systems, SCADA integration, predictive maintenance tools, KPI dashboards, real-time alerts, IoT sensors connectivity, and comprehensive asset performance management solutions.
request background
Reasons to Implement Renewable Energy Asset Management Solutions
The world of renewables is maturing at pace, thanks to the increasing momentum of efforts to embrace global sustainability and decarbonization. To scale renewable assets such as wind farms and sun gardens, operational complications arise, needing cutting-edge technological solutions. Efficient management of renewable energy optimizes the performance and service life of infrastructure.
And wind turbines and solar farms are both in competitive, dynamic environments where small levels of inefficiency add up to big losses. Real-time alerts and predicting maintenance are must-haves for companies to manage both operational and financial risk. Solar monitoring and wind tracking systems become essential for tracking performance variations.
Inefficiencies directly impact revenue; single turbines or panels operating below capacity cause annual losses. Companies must meet strict standards requiring KPI dashboards and reporting. Non-compliance leads to penalties or contract losses.
The company was searching for scalable AI-driven asset performance management solutions, seamlessly integrated with SCADA. Such a solution would include anomaly detection, condition-based maintenance intelligence and digital twin functionalities that support informed decisions with an optimal management of renewable energy.
challenge
Challenges that Asset Manager Renewable Energy Can Overcome
The company encountered substantial difficulties in efficiently controlling the assets of renewable sources. Production prediction and optimization were challenging due to fluctuating energy deliverability, which resulted in the loss of many production opportunities. When there was no solar tracking and wind monitoring forecasting, so could not control supply with demand.
Equipment was breaking down constantly, causing sudden power outages that led to energy waste and extra expenses. A lack of automated anomaly detection led to problems not being detected until they became large disruptions. Routine became emergency repairs, which brought costs and less reliability. There was no such thing as a predictive maintenance system.
Maintenance relied on reactive approaches, servicing equipment only after failures or following fixed schedules, ignoring actual asset conditions. This increased repair costs and shortened lifespan. Proper condition-based maintenance with IoT sensors could prevent these issues through continuous monitoring.
Data integration complicated operations further. Performance data came from multiple sources, but consolidating it effectively proved difficult. Limited SCADA integration slowed decision-making. Without unified KPI dashboards, identifying patterns or predicting failures remained challenging. Missing real-time alerts delayed critical interventions.
The company did not have digital twin capabilities to model scenarios and optimize operations. OPC UA/Modbus protocols were not followed, which would have allowed systems to talk to each other. Asset Performance: Management was fragmented without centralized control.
These difficulties pointed out the immediate demand for the development of integrated renewable energy management software. It would also monitor machine performance in real time, allow for predictive maintenance and work with a wide range of available data sources to give actionable intelligence.
Success meant bringing solar monitoring and wind tracking together with the power of advanced analytics to form unified platforms that provide visibility and control, enabling proactive management practices that eliminate redundancy across all renewable assets.
goals
- Reduce performance variability for predictable and reliable energy production with end-to-end renewable energy asset management, while integrated solar tracking and wind tracking give real-time visibility.
- Adopted predictive maintenance, such as minimizing unplanned outages, increasing reliability, early detection of problems, and cost savings with IoT sensors, anomaly detection and condition-based maintenance practices.
- Collect information on a single platform with SCADA integration, KPI dashboards and real-time notifications, allowing quicker, more informed decision making through full mechanical performance visibility.
- Build scalable renewable energy management platforms supporting future growth, incorporating digital twin technology, OPC UA / Modbus protocols, and flexible architectures accommodating new renewable technologies and expanding operations.
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 analyzed client infrastructure, identifying performance variability causes and downtime reasons. We designed AI-powered renewable energy management solutions customized for growth goals.
It combines different data sources by linking to wind turbine and solar inverter real-time files and SCADA, providing asset performance views across all assets. Sophisticated solar monitoring and wind analysis that follows each individual asset 24/7. Leveraging advanced analytics, the Solution predicts maintenance needs before unscheduled downtime becomes an issue.
Granular operational data of installations is gathered using IoT sensors. Any abnormal patterns are detected in the act by anomaly detection algorithms. CBMS optimises maintenance intervals as a function of the current state of equipment and not one that adheres to scheduling based on the calendar. Operators are instantly alerted via real-time alerts for critical conditions.
A centralized dashboard consolidates KPI dashboards into user-friendly interfaces, providing performance statistics. OPC UA / Modbus protocols ensure seamless communication between diverse equipment types. Digital twin technology enables scenario simulation and optimization testing without affecting live operations.
- AI renewable energy asset management software consolidating real time data from wind and solar assets, featuring full SCADA integration frameworks.
- For our systems, this means advanced solar tracking and wind monitoring, along with predictive maintenance enabled by machine learning analytics. We are going to identify the issue before it becomes a problem.
- Centralized KPI Dashboards to visualize and assist decision making by integrating data with real time alerts for key parameters.
- The Asset Management Platform is an end-to-end IoT sensor network for continuous data gathering, processing and monitoring for asset performance management.
- Advanced anomaly detection algorithms enable condition-based maintenance approaches – minimising costly service visit.
- Digital twin applications for scenario modelling with the help of OPC UA / Modbus protocols, based on compatibility.
- Modular construction that allows for the future extension and integration of new technology of renewable energy management
outcome
Renewable Energy Asset Management for Predictive Maintenance and Optimized Performance
- 25% Reduced Unplanned Downtime via predictive maintenance and early issue identification, leveraging advanced anomaly detection baked into renewable energy asset management systems.
- 15% Asset Lifespan Extension by transitioning towards proactive condition-based maintenance under IoT sensors and digital-twin simulation.
- 20% More Energy Generation with optimised solar tracking and wind tracking. It is time to eliminate inefficiencies across all sites.
- Enhanced Operational Productivity through SCADA integration, KPI dashboards, and real time alerts for quicker response times.
- Improved Decision-Making with full asset performance management and OPC UA / Modbus data integration.
client feedback
Acropolium was highly collaborative, attentive to our unique needs, and delivered renewable energy management solutions supporting future growth. The solar tracking and wind monitoring for predictive maintenance are a bonus. We are looking forward to further cooperation with you.
