The transition to renewable energy sources has gained momentum in recent years as the world grapples with the growing threat of climate change and the need to reduce greenhouse gas emissions. Renewable power plants, including solar, wind, hydro and geothermal facilities, play a pivotal role in achieving sustainability goals. To maximise the efficiency, reliability and cost-effectiveness of these power plants, digitalisation has become an essential component.
Power Line takes a look at the challenges, requirements and technologies associated with the digitalisation of renewable power plants.
Need for digital power plants
Renewable power plants are affected by varying environmental conditions, such as changes in wind speeds, sunlight and temperature. Digitalisation enables real-time monitoring and control, allowing operators to optimise energy production and minimise downtime. By collecting and analysing data, operators can anticipate issues and take preventive measures to ensure continuous operation. As the share of renewable energy in the grid increases, integrating these intermittent sources becomes more challenging. Digitalisation provides tools to manage the variability of renewable energy sources, helping to balance supply and demand. Additionally, digital solutions can be used to control and optimise energy storage systems, increasing grid stability.
Unplanned downtime is a significant cost factor for renewable power plants. Digitalisation enables predictive maintenance by monitoring equipment condition and performance. This proactive approach reduces repair costs and extends the lifespan of assets, increasing the overall return on investment. The wealth of data generated by digitalisation tools empowers operators to make informed decisions. From resource allocation to performance optimisation, data analytics are instrumental in streamlining operations and improving efficiency.
Digitalisation begins with the deployment of sensors throughout the power plant. Sensors can monitor various parameters such as temperature, wind speed, solar irradiance and equipment health. These sensors should be capable of real-time data transmission and must be rugged enough to withstand harsh environmental conditions. A reliable communications infrastructure is essential for transmitting data from sensors to control centres. This often involves a combination of wired and wireless technologies, including fibre optics, satellite communication and cellular networks. Redundancy and cybersecurity measures are crucial to maintaining data integrity and system security. Power plants generate vast amounts of data, which must be collected, stored and analysed. Effective data management systems are required to process and interpret this data, providing actionable insights. Machine learning (ML) and artificial intelligence (AI) technologies play a pivotal role in predictive analytics. Automation systems are necessary for remotely monitoring and controlling power plant operations. These systems must be highly reliable and capable of handling various functions, such as adjusting equipment settings, optimising energy output and managing energy storage systems. Additionally, cybersecurity is a critical requirement, as the digitalisation of power plants introduces vulnerabilities. Therefore, robust security measures are essential to protect the infrastructure and data from cyberthreats.
Technology options
Digitalisation is not a new concept for the renewable power sector, which has moved from computer-based systems, databases and communication networks and servers to the internet of things (IoT), cloud-based platforms, advanced analytics, predictive data analytics, smart sensors and intelligent forecasting solutions. The digitalisation of renewable power plants is a critical step in harnessing the full potential of clean energy sources while ensuring their reliability and efficiency. Digitalisation is essential for enhanced energy production, grid integration, predictive maintenance and data-driven decision-making. Meeting these requirements demands sensor technology, communications infrastructure, data management, automation systems and robust cybersecurity measures. To fulfil these needs, a wide range of technologies are being employed, including IoT, supervisory control and data acquisition (SCADA), cloud computing, big data analytics, blockchain, AI, ML, digital twin and drones and robots.
IoT involves the integration of sensors and devices into a network, allowing real-time data collection and communication. IoT technology facilitates remote monitoring and control, predictive maintenance and data analytics. SCADA systems enable centralised control and monitoring of power plant operations. They collect real-time data from sensors and equipment, enabling operators to make informed decisions and control various aspects of the plant remotely. Cloud computing offers scalable storage and processing capabilities for the vast amounts of data generated by digitalised power plants. Cloud-based solutions provide flexibility and cost savings, allowing operators to access data and applications remotely.
In addition, big data analytics technologies enable operators to extract valuable insights from the massive data sets generated by renewable power plants. ML and AI algorithms can detect patterns, predict failures and optimise operations, ultimately improving efficiency and performance. Further, blockchain technology is emerging as a means to enhance trust and transparency in renewable energy transactions. It can be used to securely record and verify data related to energy production, consumption and trading, making it an important tool for grid integration and energy sharing. AI plays a critical role in digitalisation, particularly in predictive maintenance and performance optimisation. Meanwhile, ML algorithms can analyse historical and real-time data to identify anomalies and predict equipment failures, allowing for timely maintenance and reducing downtime.
Popular solutions for renewable power plants
AI-based digital twin is a technology with immense scope in operations and maintenance (O&M) activities. This involves the creation of a replica of an actual physical asset, to be used as a benchmark for identifying faults through data anomalies. O&M teams can, therefore, predict potential faults or breakdowns in a solar power project based on the digital twin’s behaviour in certain simulated conditions. Moreover, through simulation, energy outputs can be enhanced wherever possible. Thus, a digital twin can be a powerful tool for improving plant performance, reducing breakdown-related expenses and improving revenues.
With the increasing size and scale of renewable energy projects, the use of drones for inspection activities has emerged as a popular alternative to manual inspection. Drones can be equipped with thermal cameras to capture infrared signatures and detect defects, dirt and soiling. Drones can provide more granular details than ground crews and can detect malfunctioning modules, specifically hotspots, which reduce electricity generation. They can also identify faulty strings with greater accuracy and reliability. In addition, developers are adopting robotic technologies for cleaning activities and sensors to identify the optimal angle for maximum yield.
Furthermore, the constant monitoring of wind turbines and associated equipment to measure the current, voltage, power and energy generation is essential for ensuring that the plant’s performance meets the required standards. Automatic monitoring systems not only monitor the plant yield but also assist in timely diagnosis and rectification of faults, so as to prevent plant downtime. Additionally, the analysis of data sets provides forecasts for energy generation. Since the number and scale of wind assets have increased for each developer, the need for integrated asset portfolio management has risen. This requires greater connectivity and much higher levels of automatic monitoring.
Conclusion
The automation of O&M processes through technologies such as predictive maintenance, big data analytics, digital twins, drones and robotics has become essential, especially for developers and operators with multiple assets. The capital cost of digitalising O&M activities may seem high, but the long-term gains in generation, reduced downtime and increased revenues compensate for the costs. Meanwhile, several O&M platforms exist and continue to evolve with AI, ML and other advanced technologies to save O&M costs. With rapid technological advancements, the cost of ownership is likely to reduce. As a result, more developers and operators will adopt digitalised and automated O&M processes.
The integration of digital technologies is driving the transformation of renewable power plants into smart, interconnected and efficient systems that will play a key role in the transition to sustainable energy sources. With continued innovation and investment in digitalisation, renewable power plants will be better equipped to meet the country’s growing demand for clean and reliable energy.
Akanksha Chandrakar
