By Aditya Singh Poonia
As Artificial Intelligence (AI) advances, its transformative impact on the renewable energy (RE) sector has become increasingly apparent. AI’s ability to analyse patterns and leverage vast knowledge has set the stage for improvements in energy production, conversion, and delivery.
Currently, India ranks 4th globally for total renewable power capacity additions (source https://www.investindia.gov.in/sector/renewable-energy#:~:text=India saw the highest year, by around 128% since 2014. )
However, the sector faces challenges due to unpredictable weather, impacting energy production. While efficient technologies exist for weather prediction, sudden climate changes can disrupt the energy flow, highlighting vulnerabilities in the renewable energy supply chain. Additionally, emerging energy storage technologies are in a nascent stage and need thorough testing. These challenges emphasise the importance of investing in emerging technologies like AI, ML, and IoT to enhance productivity and address shortcomings in the renewable energy sector.
Here’s how AI can help the solar sector –
1. Scaling and Savings: The construction costs of solar energy systems in India have long posed a barrier to widespread adoption, with each project facing unique challenges and escalating expenses. Artificial Intelligence (AI) steps in as a transformative force, offering efficient solutions to streamline construction complexities and minimise costs. From AI-driven solar site selection and pre-construction planning to overcoming delays and optimising system performance, this technology can reshape India’s solar landscape. With a 30% reduction in construction costs and the ability to forecast demand and enhance efficiency, AI emerges as a crucial catalyst in making solar power more accessible, cost-effective, and integral to India’s sustainable energy future.
2. Automated monitoring and maintenance – AI-driven systems enable automated monitoring of customer usage patterns, pinpointing areas in need of maintenance or repair within solar energy systems. This information empowers companies to automate maintenance schedules, optimising customer systems without dispatching technicians or incurring repair expenses. Embracing AI enhances solar panel installation companies’ capabilities, offering insights and analytics that elevate customer experience, cut costs, enhance efficiency, and propel the evolution of renewable energy sources.
3. Solar Variability Across Regions: Asia Pacific region is predicted to lead the global artificial intelligence (AI) in renewable energy market in the next ten years with India contributing heavily to the same.
India’s expansive landscape encompasses diverse climatic conditions, leading to fluctuating solar potential across regions. In the sun-drenched plains of Rajasthan and the undulating terrains of the North East, AI algorithms must be finely tuned to adapt to this variability. Achieving optimal energy production necessitates a nuanced understanding of the distinct solar characteristics prevalent in different parts of the country. AI’s role in this context involves a sophisticated optimisation process that considers the intricacies of each region’s solar dynamics.
4. Micro-grid Integration for Diverse Energy Landscapes: India’s energy ecosystem has both centralised and decentralised systems. This necessitates a pivotal role for AI in optimising micro-grid operations. This is particularly crucial in rural areas, where standalone solar systems and mini-grids are pivotal for electrification. In addition to this, a substantial population grapples with unreliable electricity access in rural areas. This challenge can be easily addressed by AI-powered off-grid solar solutions. By tailoring technologies to suit the distinctive needs of rural areas, AI can play a transformative role in fostering widespread electrification.
5. Monsoon Challenges on Solar Operations: India’s monsoon seasons pose a unique challenge to solar operations, with reduced sunlight impacting panel efficiency. AI’s predictive capabilities come to the forefront in mitigating these challenges by forecasting and managing energy production during periods of inclement weather. This proactive approach ensures a consistent and reliable power supply throughout the year, even in the face of weather-related disruptions.
6. E-Waste Management in Solar Technologies: With the escalating adoption of solar technologies, the management of electronic waste emerges as a critical concern. AI interventions can contribute significantly to the development of efficient e-waste management systems. These systems align with India’s commitment to sustainable practices, providing a technologically advanced solution to the challenges associated with the increasing prevalence of electronic waste in the solar energy sector.
The global artificial intelligence in renewable energy market size was valued at USD 10 billion in 2022. It is expected to surpass around USD 114.87 billion by 2032 with a noteworthy CAGR of 27.70% from 2023 to 2032.
Over the next decade, automation driven by AI can significantly elevate the efficiency of solar and wind energy. By providing accurate forecasting of weather and loads, AI mitigates risks, such as electrical surges, and enhances the productivity of renewable systems. The synergy of AI and machine learning in the RE industry addresses challenges, analyses data for future predictions, and contributes to the evolution of cleaner and more efficient energy solutions.
The author is founder, Etrica Power
