Powering the Future: AI & ML Revolutionising the Energy Sector
Artificial Intelligence and Machine Learning are transforming the energy sector by enabling data-driven decision-making. One of the most important innovations in this field is the Virtual Twin experience, which offers a 3D representation of physical energy assets.
May 06, 2025. By News Bureau
With the growing demand in the energy sector, the need for advanced tools to drive operational excellence has also gone up. Artificial Intelligence (AI) and Machine Learning (ML) are transforming the energy sector by enabling data-driven decision-making. One of the most important innovations in this field is the Virtual Twin experience, which offers a 3D representation of physical energy assets. By utilising real-time data, Virtual Twin technology helps organisations optimise operations, reduce waste, and achieve sustainability goals with remarkable precision.
A recent EY report highlights that 66 percent of energy firms are adopting AI, improving efficiency through predictive maintenance and real-time monitoring. AI-driven solutions optimise energy distribution, cut operational costs, and boost renewable integration, ensuring a more reliable, cost-effective, and sustainable power grid.
The Need for Smarter, Sustainable Energy Systems
With an installed power capacity of 442.85 GW as of April 30, 2024, India is the third-largest producer and consumer of electricity worldwide. Growing electrification and increasing per-capita energy consumption are accelerating the need for a smarter power infrastructure. The government has committed to augmenting non-fossil fuel-based electricity generation capacity to over 500 GW by 2031-32, highlighting the nation’s ambitious clean energy transition.
AI-driven optimisation is playing a crucial role in the integration of renewable energy sources. By improving forecasting accuracy by up to 30 percent, AI enables better planning of energy production schedules, reducing overall costs by 15 percent. This contributes to a stable grid, allowing seamless integration of solar and wind energy. Additionally, India’s power sector is expected to attract investment worth INR 17 lakh crore (USD 205.31 billion) over the next 5-7 years, demonstrating the country’s commitment to advancing its energy infrastructure.
Another advantage of AI in the energy industry is cost reduction. AI-powered energy management systems can lower operational expenses for utilities by up to 25 percent. These systems enable smart decision-making, allowing companies to dynamically adjust energy generation and distribution to meet demand while minimising waste and inefficiencies.
The rise in the global energy demand has led to the challenge of balancing supply with sustainability commitments. While industries worldwide are striving toward net-zero emissions, traditional energy infrastructure is struggling to keep pace with this transition. One of the primary challenges is renewable energy integration, as managing intermittent sources like solar and wind within conventional grids requires advanced forecasting and optimisation solutions. Additionally, ensuring grid stability and resilience is crucial in an era of decentralised energy generation, where seamless distribution must be maintained despite fluctuating inputs.
Operational efficiency also remains a key concern, with a need to reduce energy losses, improve asset utilisation, and enhance safety in energy production. To address these challenges, energy leaders must adopt AI and ML-driven innovations that provide real-time insights and predictive capabilities. These technologies empower better decision-making, enabling a more reliable, efficient, and sustainable energy ecosystem.
AI and ML are crucial in optimising energy systems, driving efficiency, and enabling a more sustainable future. One of the prime applications of Virtual Twin is predictive analytics and maintenance, where AI-driven failure prediction models help minimise downtime in critical energy infrastructure through proactive maintenance strategies. In grid optimisation and innovative energy distribution, machine learning-powered dynamic load balancing enhances energy efficiency by analysing real-time consumption patterns and adjusting distribution accordingly.
Renewable energy integration is also benefiting from AI-enhanced forecasting models, which improve the reliability of wind, solar, and hydropower by reducing variability and enhancing grid stability. Additionally, AI-powered smart meters and intelligent automation are transforming energy consumption management, allowing industries and consumers to optimise usage, lower operational costs, and minimise waste. Collectively, these technologies are unlocking new levels of efficiency, ensuring energy resources are utilised optimally while significantly reducing environmental impact.
A New Era for the Energy Sector
Beyond AI and ML, Virtual Twin technology is reimagining how energy assets are managed by creating digital replicas of power plants, grids, and renewable energy systems. This innovation enables energy companies to monitor and optimise operations in real time, providing actionable insights that enhance efficiency and performance. Additionally, AI-powered simulations allow organisations to simulate different energy scenarios, helping decision-makers predict outcomes under various operational conditions and implement the most effective strategies. Virtual Twin technology also plays a crucial role in reducing carbon footprints, particularly in sectors like hydrogen production and nuclear energy, by optimising resource utilisation and minimising emissions. As a result, this technology is driving the energy sector toward a more sustainable, data-driven future.
India’s government is accelerating clean energy adoption with bold initiatives such as increased funding for green hydrogen, solar power, and green-energy corridors. To meet its 500 GW renewable energy target and address coal supply challenges, the Ministry of Power has identified 81 thermal units that will transition from coal to renewable energy by 2026. Additionally, the Cabinet has approved the PM-Surya Ghar: Muft Bijli Yojana aiming to install rooftop solar in one crore households, further demonstrating India’s commitment to clean energy.
Applications of Virtual Twins in the Energy Sector
The impact of Virtual Twin technology is already transforming various energy sectors, driving efficiency, sustainability, and innovation. In sustainable infrastructure development, virtual twins are enhancing the design and performance of next-generation energy projects by reducing construction waste and operational inefficiencies. In the oil and gas industry, AI-driven virtual twins are playing a critical role in predicting risks, improving safety, and optimising efficiency across both upstream and downstream processes.
Similarly, in the hydrogen economy, virtual twin simulations are ensuring the feasibility of hydrogen as a clean energy source by optimising production, storage, and distribution. India’s commitment to advancing energy infrastructure is further reinforced by INR 9.15 lakh crore (USD 109.50 billion) investment plan aimed at strengthening the national power grid and enhancing energy security. This long-term vision aligns with AI- and ML-driven digital transformation, ensuring a more sustainable and efficient energy management system for the future.
A Future Powered by AI, ML & Virtual Twins
The convergence of AI, ML, and Virtual Twin technology is accelerating the transformation of the energy sector. These digital solutions are not only driving efficiency and cost savings but also paving the way for a sustainable, resilient, and decarbonised future.
As the world transitions towards cleaner energy, industry leaders must embrace AI-driven innovations to stay competitive and contribute to global sustainability efforts. The energy revolution is here, and those who leverage digital intelligence will lead the charge toward a smarter, greener future.
- Tanuj Mittal, Sr. Director Sales, Customer Solution Experience, Dassault Systemes India
please contact: contact@energetica-india.net.
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