As India’s renewable energy capacity continues to expand every year, the operations and maintenance (O&M) segment has emerged as a critical enabler for ensuring the long-term success of renewable energy assets. With the country’s installed solar capacity reaching 102.56 GW as of March 2025 and wind capacity increasing to 48.58 GW, ensuring efficient asset performance over their lifecycle has become increasingly important.
Needs and requirements
The growing complexity and scale of renewable energy projects demand a robust O&M ecosystem not just for maximising energy output, but also for extending asset lifespan and minimising downtime. Moreover, in a sector where power purchase agreements span decades, O&M plays a crucial role in maintaining assets. Further, for developers and investors, solar plants are long-term infrastructure assets expected to operate efficiently for 25 years or more. Without structured O&M practices, issues such as module degradation, inverter breakdowns and soiling losses can lead to significant generation losses.
In India, scheduled maintenance forms the backbone of solar O&M services. These include activities like physical and visual inspections, verification of key components, cleaning of solar panels and vegetation control. They are crucial due to environmental factors like dust accumulation. When a fault is detected, corrective maintenance is implemented to restore system functionality through remote monitoring systems or on-site inspections.
This can range from minor interventions that do not require part replacements to more complex ones involving software or hardware changes. Thus, corrective maintenance plays a key role in fault diagnosis, temporary fixes and complete repairs. By restoring components post-failure, corrective maintenance acts as a reactive layer of support, ensuring minimal downtime and performance losses.
O&M practices are also evolving towards predictive maintenance, which utilises data-driven insights for anticipating system failures before they occur. By analysing trends and degradation indicators through advanced monitoring tools, operators can forecast issues and intervene early. This proactive approach requires intelligent equipment and performance data from critical PV components.
Extraordinary maintenance is reserved for unforeseen and severe disruptions, such as those caused by natural disasters, theft, or systemic equipment failures. These interventions go beyond routine tasks, often requiring significant effort to restore the plant to its original condition. Extraordinary maintenance may also be triggered by regulatory changes or inherent design flaws that demand retrofits. These situations require swift and expert action to mitigate prolonged downtime and financial losses.
As solar plants age, routine maintenance is no longer enough to ensure optimal performance. This is where revamping and repowering strategies become essential tools. Revamping refers to the replacement of components such as inverters and modules without altering the plant’s capacity. It focuses on modernising outdated parts to restore efficiency and addressing wear and tear without disrupting the plant’s existing grid commitments or permissions. Repowering also involves component replacement but significantly changes the plant’s nominal power output. By installing higher-capacity modules or integrating energy storage systems, repowering not only transforms old infrastructure but also enhances the energy yield of the project.
Strategies for solar plants
Operational costs of PV plants significantly impact the total levelised cost of energy (LCOE) and, consequently, the profitability of a project. Optimising operational quality, reducing maintenance costs and maximising plant performances are key to ensuring project success. This process requires balancing the reduction of interventions and spare part replacements during the lifetime of a project while maintaining optimal plant performance.
O&M practices in the solar sector are rapidly evolving with the adoption of digital technologies and automation. Most utility-scale plants are now equipped with supervisory control and data acquisition (SCADA) systems and internet of things (IoT) sensors for real-time monitoring, enabling quick fault detection and data-driven decision-making. Predictive maintenance using AI and machine learning is gaining traction, particularly for anticipating failures in critical components such as inverters and connectors, thereby reducing unplanned outages.
With water scarcity becoming a growing concern, especially in arid regions like Rajasthan and Gujarat, robotic and waterless cleaning systems are being deployed to maintain panel efficiency while reducing operational costs. According to the Council on Energy, Environment and Water, India uses 7,000–20,000 litres of water to clean per megawatt of solar panels, highlighting the significant environmental impact. However, with the use of automated robotic cleaning, the water dependency can be significantly reduced. In robotic cleaning, robots roll over the solar panels and remove dust, bird droppings and other dirt from the surface to maintain optimal efficiency levels.
Advanced aerial thermography using drones and aircraft-mounted infrared cameras enable faster and more efficient inspection of PV modules, which reduces labour and operational costs. A digital twin is a virtual replica of a solar plant that integrates real-time data from SCADA, drones, sensors and maintenance systems. In India, where large-scale solar deployment is expanding, digital twins can improve decision-making by enabling performance modelling, fault detection and predictive maintenance. Automating data flow from various sources into the twin allows operators to optimise plant performance and reduce downtime.
Solutions for wind power projects
India’s wind energy sector has witnessed significant growth, with an installed wind energy capacity of 48 GW. With the expansion of the sector, the O&M practices have also evolved to ensure the longevity and efficiency of wind power assets.
O&M plays a crucial role in the wind energy industry, directly impacting turbine performance and energy output. Typically, O&M activities for wind power include routine inspections, preventive maintenance and timely repairs. These strategies not only enhance turbine reliability but also reduce the LCOE. Some major factors driving the demand for technological innovations in the sector are ageing wind power components, supply chain constraints and the unavailability of spare parts, which extend the turbine downtime. While some original equipment manufacturers offer full-scope O&M services, independent power producers (IPPs) prefer in-house or hybrid models to control costs and performance.
In India, factors like extreme weather conditions, remote sites and variations in topography shape O&M strategies. Predictive maintenance powered by data analytics and machine learning enables operators to anticipate component failures and schedule proactive interventions. To inspect blades for reparations and avoid risks, operators are increasingly using drone technology and robotics. SCADA platforms are used for remote monitoring systems to gain real-time insights on turbine performance.
Another key trend is the emergence of offshore wind projects in India. Although the Indian wind segment is predominantly onshore, the recent announcement of viability gap funding (VGF) for 4 GW of offshore wind projects in Gujarat and Tamil Nadu is expected to drive a new set of trends. To accelerate offshore wind development, the Ministry of New and Renewable Energy (MNRE) has proposed VGF for the first 4 GW of offshore projects in Gujarat and Tamil Nadu. Offshore wind O&M, in particular, relies heavily on remote monitoring, AI-driven diagnostics and autonomous drones to minimise physical interventions in challenging marine environments. Furthermore, advanced measures for preventing wind turbine failures using equipment information are likely to gain traction.
However, cybersecurity has emerged as a critical concern. In the Indian context, the growing adoption of IoT platforms and digital twins by IPPs highlights the urgent need for robust cybersecurity protocols, encrypted communication and regular audits to safeguard wind assets.
Conclusion
As India expands its solar and wind power base, O&M will be crucial for maintaining optimal asset performance. The sector is moving towards a data-centric, cyber-secure and cost-optimised O&M model. Trends such as predictive maintenance, digital twins, remote monitoring, robotic cleaning and aerial thermography are transforming O&M into a more proactive and data-centric function. These innovations not only help reduce downtime and operational costs but also enhance the overall efficiency and sustainability of renewable energy assets.