Ensuring optimum plant performance and quality of assets is perhaps the top priority for solar power plant operators. To this end, it is important to have skilled operations and maintenance (O&M) crews as well as the most advanced equipment, while keeping costs in check. The solar power landscape in India has changed radically over the past five years – project sizes have increased four to five times, the geographical spread has expanded and developers have amassed multi-GW project portfolios. Thus, individual developers now own double-digit projects spread across multiple states and of various types, including rooftop, utility scale and floating solar.
Consequently, traditional O&M models, with a large, dedicated O&M team for each asset, will no longer work and will become too expensive for developers. Moreover, such a model would not be able to meet future O&M demands, as the process of monitoring data gets more complex. Thus, the focus of both asset owners and O&M teams (whether in-house or third-party service providers) is now turning towards incorporating more automation and digitalisation in their O&M practices, using drones, robotics, artificial intelligence (AI)-enabled monitoring and analysis, advanced fault diagnostics techniques and intelligent remote monitoring software. Such O&M tools and services not only help in getting the job done quickly, but also ensure higher quality and greater reliability. Moreover, they can significantly reduce O&M costs owing to lower manpower requirements, even though a small initial capital investment may be required to deploy such advanced tools. Better O&M also leads to more energy generation, improved equipment life and less project downtime. All these ultimately lead to cost benefits for asset owners through increased revenue, operational savings and reduced maintenance costs. There are numerous models that developers can adopt, involving both in-house and third-party contracts or a mix of both, in the evolving solar O&M market.
Power Line takes a look at some of the advanced technologies that are likely to dominate the solar O&M market in the near future…
Drones for inspection
With the increasing size and scale of projects, manual inspection may no longer be possible and is also time-consuming. If manpower were to inspect each piece of equipment spread across hundreds of acres of land, it would take days for fault detection. Thus, the use of drones for inspection activities has emerged as a popular alternative to manual inspection. Drones today can be equipped with thermal cameras to capture infrared signatures and detect defects, dirt and soiling on panels. These defects are geotagged and the data is sent to O&M teams. Drones can provide more granular details than ground crews and can detect malfunctioning modules, specifically hotspots, which reduce electricity generation. They can also point out faulty strings with greater accuracy and reliability.
Robots in module cleaning
One of the most critical but expensive steps in the O&M process is the periodic removal of dust and soiling from solar panels. Traditional methods in India involve manual cleaning, using buckets of water for smaller projects and hosepipes attached to water tankers for bigger projects. These techniques not only entail large manpower requirements, but also huge volumes of water. According to industry estimates, the cost involved in such a process can be 10-35 per cent of the total O&M expense, depending on the cleaning technique employed.
Costs can be reduced with the help of robotic technologies, which limit human involvement as well as water usage in cleaning activities. Many wet cleaning robots have wipers, scrubs, brushes, water and detergent for cleaning solar panels. In regions where water availability is a challenge, dry-cleaning robots, with large microfibre brushes on wheels, can be used, which rotate at high speeds to generate air flow and remove dust from solar panels.
For instance, projects in arid regions such as Rajasthan, where the government does not allow the construction of borewells for pumping water, can rely on such dry robotic cleaning. AI-driven robots are now being used in the module cleaning space. These highly efficient robots can take into account various parameters such as inclination of solar panels, geographic location, wind direction, and speed and dust content to clean panels effectively, without any manual intervention. They can also decide the frequency of cleaning.
Although initial costs might be a challenge for some developers, the overall benefits are worth the investment. Moreover, with increasing uptake, these robotic technologies are likely to become more economically viable in the near future.
Automation and digitalisation
Automation and digitalisation can be effectively put to use in fault detection and rectification. Remote monitoring systems with real-time updates can help in predicting faults, diagnosing their causes and taking corrective action to prevent equipment or project downtime. Renewable energy developers are also focusing on setting up advanced monitoring systems to avoid paying penalties for over- or under-generation, according to their respective scheduling, forecasting and deviation settlement regulations. Thus, advanced asset management software with AI-enabled monitoring platforms is being increasingly used for predictive O&M as it helps developers and O&M service providers analyse data from a number of projects and take corrective action accordingly.
Predictive maintenance technologies have evolved and advanced greatly to ensure higher reliability and efficiency. Cloud-based remote monitoring systems are being developed, which collect data based on specified critical parameters and make them accessible to O&M teams from anywhere in the world via cloud computing. Data loggers transmit this data to cloud-based internet of things (IoT) platforms, which can be accessed in raw form or aggregated forms, or as visual representations, so as to make monitoring of projects and even stand-alone equipment less complicated. For instance, TrackSo, developed by Free Spirits Green Labs, is an IoT-based energy management platform that helps track solar power plant performance and predict failures by providing proactive maintenance of assets.
Digital twin
A technology with immense scope in O&M activities is AI-based digital twins. 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, thus, predict possible faults or breakdowns in a solar power project based on the behaviour of this digital twin in certain simulated conditions. Moreover, through simulation, energy outputs can be enhanced where possible. Thus, a digital twin can be a powerful tool for improving plant performance, reducing breakdown-related expenses and improving revenues.
Role of AI and machine learning
Accurate weather forecasting services are being integrated with monitoring systems to predict energy generation and possible deviations from the expected energy output. In such cases, large real-time weather data sets sourced from satellites, weather stations and other devices are analysed and compared with historical weather data. Further, with the help of AI-enabled analysis of historical, present and future weather data, the impact of weather on solar production can also be determined. Moreover, machine learning is being applied in advanced solar O&M. Equipment is programmed to learn and react to the various operational processes and issues of a solar power plant so that, through self-learning, machines can identify possible faults and diagnose them. At present, efforts are focused on developing advanced self-monitoring and self-operating machines that will, in time, evolve to such an extent that they will be able to address minor O&M issues on their own.
The way forward
During the Covid-19 pandemic, developers faced issues in carrying out proper O&M, since O&M in India is highly dependent on manpower. Regular availability of water for module cleaning also became an issue. In the case of rooftop projects, O&M teams could not get access to project sites. To overcome these issues, most developers have accelerated their transition to some level of automation, and use digitally enabled tools for their daily O&M needs to enable higher efficiencies. Going forward, this trend is likely to continue, corresponding to the increasing size, scale and number of projects owned by each developer.
