Harnessing Automation for a Cleaner Energy Landscape

Amidst the pursuit of a greener tomorrow, the seamless integration of automation into clean energy production emerges as a pivotal catalyst, showcasing its transformative potential in paving the way towards a more sustainable energy landscape.

December 21, 2023. By News Bureau

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Greenhouse gas emissions

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In the quest for a sustainable future, the world is increasingly turning to clean energy sources to combat climate change and reduce environmental impact. This paradigm shift towards renewables is facilitated by technological advancements and innovative solutions. Amidst the pursuit of a greener tomorrow, the seamless integration of automation into clean energy production emerges as a pivotal catalyst, showcasing its transformative potential in paving the way towards a more sustainable energy landscape.

The urgency of transitioning to clean energy cannot be overstated. Rapid industrialisation and urbanisation have led to significant greenhouse gas emissions, driving global warming and its catastrophic consequences. According to the International Energy Agency (IEA), as of 2020, the energy sector accounted for approximately 42 percent of global CO₂ emissions, with electricity and heat production being the largest contributors. Renewable energy sources, such as solar, wind, hydro, and geothermal power, offer a glimmer of hope for a cleaner and more sustainable future. With favourable government policies and growing public awareness, the clean energy sector is witnessing a remarkable surge in demand.

Harnessing Automation for a Greener Tomorrow

In the pursuit of a cleaner energy landscape, automation plays a pivotal role. Automation technologies, including robotics, artificial intelligence, and machine learning, are revolutionising clean energy production processes. By optimising efficiency, increasing productivity, and reducing operational costs, automation is redefining the potential of renewable energy sources. The global energy storage market is projected to grow at a CAGR of over 20 percent between 2021 and 2026, driven by advancements in automation and energy management.

The integration of automation in wind energy is a prime example of this transformative power. Wind turbines, a cornerstone of renewable energy, benefit immensely from robotic machining systems. These systems perform multiple operations with precision, ensuring proper blade fastening, reduced cycle time, and elimination of rework According to the IEA, increasing automation in wind energy can improve turbine efficiency by up to 20 percent, resulting in higher energy output and reduced emissions. Projects across offshore and onshore wind farms, remote wind parks, hybrid wind power stations, grid-connected wind plants, and near-shore wind farms are now leveraging such advanced automation solutions to enhance reliability and efficiency.

A project which aims at addressing the challenges faced by wind energy companies that utilise non-robotic systems for drilling holes in windmill blades can be taken as an example. These blades, with large diameters of up to 3 meters, require accurate hole placement for better fastening with the hub or rotor. The existing system exhibits limited accuracy, resulting in significant rework and a lengthy cycle time of 14-15 hours. To tackle this, a robotic solution focusing on the accurate drilling of holes in two orientations after sawing and milling the circular blade surface can be effective. This innovative approach would be able to slash the cycle time to 8-9 hours, marking a remarkable reduction of 35-45 percent. Furthermore, the implementation of this robotic solution would be able to virtually eliminate rework, streamlining the production process and enhancing the efficiency of wind energy systems.

Advancements in Clean Energy Technologies

Alongside wind energy, other clean energy sectors are witnessing remarkable advancements driven by automation technologies. The transportation sector accounts for about 14 percent of global greenhouse gas emissions, as reported by the United Nations Environment Programme. Catalytic converters, pivotal in reducing pollution from automobile exhaust, are now benefiting from sophisticated substrate coating solutions. These converters play a crucial role in decreasing pollution by converting carbon monoxide (CO) to carbon dioxide (CO2), oxidising hydrocarbons (HCs), and reducing nitrogen oxides (NOx). Given that transportation is a primary source of urban air pollution and a significant contributor to global environmental challenges, optimising catalytic converter efficiency is of paramount importance.

One of the critical factors affecting the efficacy of catalytic converters is substrate coating. Automation takes centre stage in this context. Consider a scenario where a substrate coating system, a synergy of multiple automation systems, revolutionises substrate coating processes. This solution encompasses data traceability, high productivity, customised designs, and safety measures for heavy-duty trucks, passenger cars, and motorcycles. Such advancements are not only vital for minimising environmental impact but also for improving the overall efficiency of transportation systems. To cite an example of this, we can take the case of a collaboration where the challenge of properly coating metallic or ceramic substrates for catalytic converters needs to be addressed with the goal being to ensure proper coating and incorporate check stations to verify coating accuracy. This can be dealt with through the development of a sophisticated two-station solution which involves the use of vacuum for washcoat coating, with air stripping to remove excess coating and ensure precise weight control. This system not only guarantees the adequacy of the coating process but would also provide an impressive output rate. This exemplifies the fusion of automation and substrate coating to achieve heightened efficiency, reduced emissions, and an overall cleaner transportation sector.

Artificial intelligence, machine learning, and predictive analytics are making inroads in clean energy technologies. These technologies optimise energy production and consumption, enabling better grid management and storage. Predictive analytics offer insights into energy demand patterns, aiding efficient energy distribution and utilisation. The World Economic Forum estimates that by 2040, AI-powered demand response systems could save up to 10 percent of global electricity consumption. These advancements are transforming the clean energy landscape, paving the way for a more reliable, efficient, and sustainable energy grid.

The Path Forward: Collaboration and Innovation

While discussing the above, it is important to remember that the journey to a sustainable energy landscape requires concerted efforts from multiple stakeholders. Governments, industry leaders, research institutions, and communities must collaborate to drive innovation and promote clean energy adoption. Wind energy automation solutions and substrate coating projects serve as just a glimpse of the transformative potential of automation in this sector.

As automation technologies evolve, there is a pressing need for investment in research and development to unlock new frontiers of clean energy solutions. Innovations in material sciences, battery technologies, and smart grid systems will be instrumental in realizing the full potential of clean energy sources.

Serving as the key to unlocking the potential of clean energy and realizing a sustainable future, automation stands as a beacon of hope. From harnessing wind power with robotic precision to optimising catalytic converters for cleaner transportation, automation is ushering in a new era of efficiency, reliability, and sustainability in the clean energy sector. Moving forward, it is essential to embrace collaboration and innovation to build a world powered by clean energy, where automation is the catalyst for a brighter and greener tomorrow.

- Mahesh Wagle, Co-Founder and CEO, Cybernetik