As India’s wind energy capacity is expanding every year, the operations and maintenance (O&M) segment emerges as an important enabler in ensuring long-term success for wind assets. With the country’s installed wind capacity reaching 48.58 GW as of March 2025 and continuing to increase, ensuring that these assets perform efficiently over their entire life cycle has become very important. For instance, taking a conservative estimate from the Global Wind Energy Council’s India Wind Energy Market Outlook 2023-27 report, “From Local Wind Power to Global Export Hub”, India is expected to add 17.4 GW of onshore wind capacity over the next five years. This would take India’s total onshore wind installations to 59.3 GW by the end of 2027.
Additionally, the growing complexity and scale of wind energy projects demand a robust O&M ecosystem not only for maximising energy output, but also for extending the asset lifespan and minimising downtime. Moreover, in a sector where power purchase agreements extend to a long time period, O&M plays a crucial role in maintaining assets. Without structured O&M practices, issues such as turbine component wear and tear, gearbox failures, blade erosion and sensor malfunctions can lead to significant downtime and energy generation losses.
Evolution of wind O&M
Over the years, wind energy O&M practices have transitioned from reactive fault correction to more predictive and condition-based approaches. This shift has been driven by the need to minimise unplanned downtime and improve asset longevity. Traditionally, O&M involved scheduled inspections and post-failure repairs. In general, some fault correction cases may involve remote fault diagnostics via supervisory control and data acquisition systems or on-site troubleshooting by maintenance teams. Reactive-based fault corrections can range from software resets and sensor recalibrations to more extensive repairs such as replacing damaged components or addressing structural issues.
Beyond this, O&M practices have been witnessing an evolutionary shift 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.
As Bajrang Ahirwar, Head – Asset Management, Fortum India said, in the “AI in Renewables” conference organised by Renewable Watch, “Traditionally, maintenance was largely preventive, which was inefficient and costly. Then came the shift to predictive maintenance, where we only work on systems that actually require manual intervention. Now, we are moving to prescriptive maintenance where we do only what is absolutely necessary to achieve cost-effective O&M.” The move towards preventive and prescriptive maintenance is also bringing in a greater use of artificial intelligence (AI) in daily O&M operations, in a bid to predict wind speeds and weather changes.
O&M teams now also work on what is called “extraordinary maintenance”, which 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. Although rare, these situations require swift and expert action to mitigate prolonged downtime and financial losses.
Challenges
Wind O&M activities include routine inspections, preventive maintenance and timely repairs requiring skilled labour force. A key challenge for wind independent power producers (IPPs) and third-party O&M players is to hire such skilled labour force and then retain them as attrition rates are quite high. Such challenges impact service quality and also contribute to increasing costs.
Another key challenge is the change in climatic conditions. For instance, as pointed by Consolidated Energy Consultants Limited, a wind energy consultancy based in Bhopal, wind speeds have declined when analysed in 2003 and 2023 due to temperature increases. This results in a higher probability of incurring higher operational costs due to breakdowns. Energy generation can potentially be impacted by a factor of three times when wind speeds change – going down from 6m per second to 3m per second. Against this backdrop, the wind energy O&M segment is witnessing a growing emphasis on technological innovations.
Technological trends and the way forward
With technological innovations, there is a possibility of declining long-term operational expenses. For instance, the introduction of direct drive technology helps in cutting down maintenance needs in a big way. This happens by reducing reliance on gearboxes, which are often the first to break down. Another smart innovation is the tension control measurement for turbine bolts. It is able to tackle a weak spot as 90 per cent of turbine failures happen because bolts are not properly tensioned. Furthermore, advanced measures to prevent wind turbine failures using the equipment information are likely to gather pace. Meanwhile, cybersecurity has emerged as a critical concern due to potential targets for cyber threats. In the Indian context, the growing adoption of IoT platforms and digital twins by IPPs also highlights the urgent need for robust cybersecurity protocols, encrypted communication and regular audits to safeguard wind assets.
The integration of AI is redefining traditional O&M approaches in India’s wind sector to make predictive maintenance possible. This approach not only cuts down on-site visits and labour needs but also allows for remote troubleshooting, thereby enhancing efficiency and reducing costs.
A key development in the future will be the advent of offshore wind projects in India. Although the wind sector in the country is onshore-dominated, with the recent announcement of viability gap funding of 4 GW offshore wind projects in Gujarat and Tamil Nadu, this segment is expected to take off. With the uptake of offshore wind projects, specific O&M techniques for the segment will be needed, particularly with a greater focus on remote monitoring, AI-driven diagnostics and autonomous drones to minimise physical interventions in challenging marine environments. This will aid in grid management and optimises energy generation from wind farms.
However, the increasing reliance on AI-machine learning (ML) platforms also brings its own set of challenges. A key concern is the difficulty to understand how these platforms are developing their algorithms internally. Moreover, most AI-ML tools are fundamentally based on regression analysis of historical data, which may not fully account for unforeseen future scenarios.
Net, net, as India expands its wind power base, O&M will be the foundation for sustained asset performance. In a bid to meeting renewable purchase obligations, it is fair to expect that wind capacities will grow further, thereby increasing the market size for wind O&M. Going forward, the sector should gradually move towards a data-centric, cyber-secure and cost-optimised O&M model. Building a robust and future-ready O&M ecosystem will call for greater support for digital innovation, local capability development and open data initiatives. Encouraging collaboration between IPPs, internet service providers, original equipment manufacturers and technology providers and setting a framework of standards for predictive analytics and cybersecurity will be crucial to ensuring that India’s wind energy assets remain reliable and globally competitive in the years to come.
By Mohammed Ali Siddiqi
