As solar power scales rapidly across India’s arid, high-irradiation regions, robotic module-cleaning solutions are gaining traction in large-scale solar projects to mitigate soiling losses and optimize operations and maintenance costs.

In an exclusive interview with Mercom India, Yogesh Kudale, Co-founder and CEO of TAYPRO, a module-cleaning solutions provider, discussed the cost savings from deploying robots to clean modules, their adoption by the commercial and industrial (C&I) and utility-scale segments, and the key challenges hindering their large-scale use.

Please provide an overview of TAYPRO’s journey so far and the scale of deployment of your module cleaning solutions in India and international solar markets.

TAYPRO’s journey has focused on solving one of the most underestimated challenges in the solar ecosystem: soiling losses and inefficient O&M. It began with the development of fully autonomous, waterless robotic systems specifically for Indian conditions, including dusty environments, terrain variability, and water scarcity.

We have established a strong presence in Rajasthan, Gujarat, and Karnataka, with our robotic cleaning solutions deployed on solar plants totaling over 5 GW of installed capacity across utility-scale and commercial and industrial (C&I) segments.

The manufacturing and technology stack can support the production of over 500 robots per month, enabling rapid deployment across large solar parks.

India is the primary market of focus, but we are actively expanding into international markets, including the Middle East and Southeast Asia. These regions face similar high-dust and water-stressed conditions, which make our solutions highly compatible.

What are the most compelling advantages of robotic cleaning over traditional methods, particularly in terms of cost, performance, and sustainability?

Robotic cleaning systems help transform solar O&M from a manual, resource-intensive process into a more efficient, data-driven model. From a cost perspective, they eliminate recurring expenses such as labor, water procurement, and tanker logistics, which can account for up to 40% of total O&M costs in high-soiling environments. This ultimately converts irregular, resource-dependent spending into a predictable and optimized cost structure.

In addition, consistent, uniform cleaning significantly reduces soiling losses and can increase energy generation by 6–15%, or more in high-dust regions. As a result, most projects integrating robotic module cleaning solutions achieve a return on investment within 12–18 months, making robotic cleaning a financially viable and performance-driven O&M strategy.

Water scarcity is a growing concern. How significant is the reduction in water usage with robotic cleaning, and how is this influencing adoption decisions?

TAYPRO’s systems are completely waterless, eliminating the need for millions of liters of water annually at a single large-scale solar plant. Our portfolio reflects annual savings of over 770 million liters of water.

High water savings have become one of the most critical reasons for regions like Rajasthan and Gujarat to adopt waterless cleaning, especially when solar irradiation is consistently high, but water availability is constrained.  Developers are increasingly factoring water risk into project viability and ESG commitments.

Waterless robotic cleaning systems are increasingly becoming a strategic requirement rather than a functional upgrade. It is influencing both regulatory alignment and long-term sustainability positioning.

From a developer’s perspective, how does robotic cleaning impact the overall O&M costs and project returns over the lifecycle of a solar project? Are there any key challenges specific to India?

When it comes to India, the challenges are largely environmental and infrastructural. High dust loads, unpredictable terrain, and limited connectivity in remote solar parks complicate the deployment, monitoring, and large-scale optimization of cleaning systems.

This drives the need for robust, intelligent systems that can operate reliably with minimal human intervention while adapting to diverse site conditions. We address these challenges through advanced engineering and communication architecture, enabling seamless automation and large-scale adoption.

There are often concerns around module wear and tear. How do you ensure that robotic cleaning systems maintain module integrity over time?

Module safety is a core design priority at TAYPRO. The robots are designed to be gentle and to maintain uniform contact with the panel surface using engineered microfiber and controlled-pressure systems. This also prevents stress on the glass and protects the anti-reflective coating.

Extensive testing across multiple deployments ensures the cleaning process remains non-abrasive even over long operational cycles, which is the approach we follow. Independent testing and approvals from Tier-1 module manufacturers further reinforce this.

Performance data indicates only ~0.34% Pmax deviation over a 25-year lifecycle, confirming that our systems maintain module integrity while delivering effective cleaning at scale.

How are AI, data analytics, and weather sensing being integrated into your solutions to optimize cleaning cycles and improve efficiency?

TAYPRO integrates AI and data analytics into its solutions to enhance operations with an intelligent, demand-based approach in addition to specific cleaning schedules. The systems consistently monitor metrics such as dust accumulation, generation trends, humidity, wind patterns, and weather forecasts.

The automated systems can process data in real time, helping determine the optimal cleaning window. Cleaning is triggered only when performance begins to decline, rather than on a preset schedule. Systems can identify cleaning requirements through predictive analysis of parameters such as motor behavior, battery health, operational anomalies, and more. This reduces downtime and ensures high-fleet availability.

This advanced system enables efficient cleaning and resource optimization while maximizing energy output through data-driven decision-making.

What kind of auxiliary power requirements do these systems have, and how do you ensure they remain energy-efficient?

The robotic systems are designed to operate with minimal to near-zero auxiliary power requirements at the plant level. They do not depend on external grid supply, as they are equipped with dedicated solar panels integrated into their docking stations, enabling fully self-sustaining battery charging and operation.

This makes the system inherently energy-independent and particularly suited for large-scale solar projects, where auxiliary power optimization is critical. Intelligent power management further enhances efficiency by optimizing motor use, cleaning operations, and travel paths to minimize energy consumption per cycle.

Additionally, AI-based battery management ensures optimal charge and discharge cycles based on terrain, workload, and operating conditions. As a result, the energy consumed by the robots is significantly lower than the incremental energy gained from improved panel efficiency, resulting in a net-positive energy outcome.

How do you see the adoption of robotic cleaning evolving in India, especially across utility- scale, C&I, and rooftop segments?

The adoption of robotic cleaning is shifting from early-stage experimentation to mainstream integration, especially for utility-scale projects where scale and soiling losses justify automation. Recent years have seen an increase in the integration of robotic cleaning systems at the project design stage, rather than adding them later.

The C&I sector is also seeing a rise in this adoption as businesses focus on maximizing returns while meeting sustainability targets. The flexibility of operational expenditure models further lowers entry barriers.

Advancements in compact robotic systems are also addressing gaps in rooftop adoption, such as structural and space constraints; however, the space is still evolving. Overall, as water scarcity, labor challenges, and performance expectations intensify, robotic cleaning is becoming a standard element of solar O&M across broader segments.