Technologies Driving Asset Optimization in Renewable Energy
Cutting-edge technologies are revolutionizing the transition to Energy 4.0, as highlighted in our whitepaper, How the Digital Evolution Accelerates the Transition to Energy 4.0. These innovations are playing a pivotal role in optimizing assets and driving transformation within the energy sector. With the growing demand for cleaner and greener power, achieving efficiency and sustainability has never been more crucial. Systems that can respond and act in real time have the potential to make a significant impact in advancing these goals.
For renewable energy systems like wind farms, solar installations and hydrogen production facilities, advanced technologies are transforming operations. Tools like edge computing, digital twins, robotics, machine learning (ML) and artificial intelligence (AI) are driving innovation, enhancing performance, reducing costs and minimizing environmental impact.
Explore with us in this blog how renewable energy asset optimization benefits companies and highlights the cutting-edge technologies that are unlocking the full potential of clean energy systems.
Edge Computing
Edge computing is transforming the way renewable energy assets are managed. By bringing data analysis and processing closer to the source, it allows for data to be processed near its point of collection, at or near the sensor. This technological approach enhances real-time data processing while mitigating communication delays, reduces latency, and enables faster, localized decision-making.
An example is installing edge devices on wind turbines. These can process sensor data such as vibration, temperature or output power in real time, predicting component stress or inefficiencies. For example, Vestas uses Microsoft Azure's high-performance computing and AI to optimize wind energy efficiency. Their edge computing approach includes wake steering, which adjusts turbine rotors to maximize energy capture while minimizing wake effects on downstream turbines.
In solar farms, edge computing enhances monitoring of panel performance, identifying shading, connectivity issues or degradation immediately to minimize energy loss, enabling predictive maintenance and operational efficiency. This approach ensures higher energy production and reduces downtime.
Digital Twin Technology
Digital twin technology is reshaping renewable energy by creating virtual replicas of physical assets, such as wind turbines, solar panels or energy storage systems. These digital counterparts allow operators to simulate conditions, predict maintenance needs and optimize operations before executing changes in the real world. This allows companies, specifically for remote or offshore applications, to plan for scenarios such as maintenance and downtime virtually, resulting in operational savings.
Offshore wind farms use digital twins to simulate adverse weather conditions such as storms, which enables operators to develop risk mitigation strategies and maintenance plans. One real use case is the Hywind Tampen Floating Wind Farm project, developed by Equinor ASA, which uses a predictive digital twin platform to monitor and forecast potential failures in wind turbine components. The platform integrates real-time data and predictive algorithms to enhance maintenance strategies and operational efficiency.
Solar farms also benefit from this technology. For example, SmartHelio uses digital twins for solar power plants that incorporate design, geographical and performance factors to optimize operations. By analyzing real-time and historical data, SmartHelio's digital twins help solar asset managers detect performance deviations, predict maintenance needs and determine optimal times for panel cleaning and adjustments. This approach minimizes operational costs and maximizes uptime.
Digital twins improve decision-making by offering precise insights, enabling energy providers to maintain optimal performance levels. By reducing unnecessary interventions and focusing on targeted actions, these technologies play a vital role in enhancing efficiency and cost-effectiveness in renewable energy projects.
Robotics
Robotics is playing an increasingly vital role in renewable energy asset management, particularly in applications requiring precision and safety in difficult-to-access environments. Autonomous robots and drones simplify inspections, automate repetitive tasks and reduce risks to human operators.
A real use case is Nexamp, which uses drones equipped with thermal imaging to inspect its solar farms, identifying and resolving string faults using aerial infrared inspection technology. This approach allowed them to detect issues like blown fuses and loose strings that were missed by traditional methods. This proactive approach reduces downtime and helps maximize energy production while cutting maintenance costs.
Offshore wind farms also benefit from asset optimization using advanced marine robots. These robots can inspect and maintain underwater components, such as turbine foundations or subsea cables, with unmatched precision. In addition, robots can also remove humans from harm and can get to places that people cannot easily get to, reducing human exposure to high-risk tasks. Beam leverages AI and autonomous robotic systems for offshore wind farm operations, using their AI-powered autonomous underwater vehicle (AUV) system, "Scout," for subsea inspections, helping with maintenance, construction and decommissioning of wind farms. This technology reduces costs and improves efficiency across the lifecycle of offshore wind assets.
While safety improvements are a significant advantage, efficiency gains from frequent, precise inspections are directly tied to optimized asset performance. By increasing inspection regularity without compromising worker safety, these technologies help renewable energy operators maintain peak operational efficiency.
Artificial Intelligence
AI, enabled by ML, is revolutionizing energy systems by enabling predictive insights, automating decision-making and balancing production across diverse operations, from clean energy sources to hybrid systems.
AI enables renewable systems to integrate real-time data seamlessly. For instance, in wind farms, AI-powered algorithms can adjust turbine angles based on weather forecasts to maximize energy generation. Solar farms utilize AI to monitor panel efficiency and alert operators to performance dips, ensuring sustained production.
AI also enhances grid stability by balancing energy supply from renewable sources with storage and demand. Additionally, its predictive capabilities allow operators to schedule maintenance at the optimal time, preventing unplanned downtime.
Recognizing the power of AI to deliver new value, Baker Hughes turned to EPAM to support the development of two digital assistants, one for production engineers and another for field engineers. Both digital assistants were developed using the robust resources of the AWS GenAI toolkit.
Helping humans do what they do better is the foundation for both GenAI collaborations between Baker Hughes and EPAM. These projects successfully demonstrate how to enable GenAI in a large energy company, which means Baker Hughes not only has two new digital assistants to use, but it also has a framework for how to build and execute additional GenAI projects going forward.
Also, technologies like our proprietary AI-enabled platform GRAIN can collect data from different sensors and process the data through edge machine learning and smart predictive analytics. This technology is highly applicable to the energy industry for use cases such as pipeline anomaly detection and automated inspection, drone surveillance of pipeline construction, and full-scale VR for effective off-site training.
Conclusion: Transforming the Energy Landscape
Asset optimization technologies like edge computing, digital twins, robotics, ML and AI are shaping the future of renewable energy. While clean energy systems such as wind, solar and hydrogen lie at the forefront of this transformation, these technologies also support hybrid networks and traditional systems during the transition to a sustainable future.
Energy companies that embrace asset optimization don’t just refine operations, they unlock the pathways to scalable, efficient and sustainable energy ecosystems. From reducing downtime to enabling sustainable practices, these innovations are redefining how energy is produced, stored, and delivered.
As the energy landscape evolves, are you ready to optimize your assets and lead the future of energy?
