Towards a digital energy future

The scale of ongoing innovations in the distribution network, including city-level advancements under the Revamped Distribution Sector Scheme (RDSS), showcases the nation’s commitment to integrating advanced technologies like Gas-insulated Substations (GIS) and Battery Energy Storage Systems (BESS).

India is on the path of rapid urbanisation, and this urbanisation is pushing for the modernisation of its power infrastructure. Initiatives like smart cities are emerging as catalysts, bridging economic growth and technological advancement. However, the progress remains uneven, with utilities operating at varying technological and governance maturity levels. While some leverage advanced tools to optimise performance, others struggle with basic implementation due to inadequate resources and expertise. Country’s complex power grid presents unique challenges and opportunities. The scale of ongoing innovations in the distribution network, including city-level advancements under the Revamped Distribution Sector Scheme (RDSS), showcases the nation’s commitment to integrating advanced technologies like gas-insulated substations (GIS) and battery energy storage systems (BESS). These innovations are critical for addressing space constraints in urban areas, ensuring reliable power availability, and enabling rapid deployment to meet growing energy demands.

Despite these advancements, challenges persist. A significant barrier is the lack of a skilled workforce capable of effectively utilising modern tools and processes. Additionally, discrepancies in data metrics and asset management inefficiencies underscore the need for improved governance, standardisation, and workforce training. Looking ahead, Artificial Intelligence (AI) and Generative AI (Gen AI) promise to revolutionise operational technologies (OT), from predictive maintenance and workforce optimisation to advanced alarm systems. However, regulatory inertia and the need for robust infrastructure and reliable data systems hinder the adoption of these technologies. With a focus on addressing these challenges through innovation, governance reforms, and responsible AI practices, India’s energy sector is poised to unlock its full potential, driving sustainable growth and meeting the evolving demands of its diverse energy ecosystem.

In an interaction with EPR, industry experts weigh in on optimal resource utilisation, asset upgrade, and the implementation of appropriate regulations to advance smart energy solutions.

Upgrading key components

The energy sector in India is witnessing a significant shift, particularly in utilities and smart energy solutions. Smart cities, backed by robust economic justifications, are set to become catalysts in this transformative journey.

However, Vikram Gandotra, President (Elect) IEEMA, points out that the progress is uneven. “We must understand that all utilities are not at the same technology maturity level or governance level,” he emphasises. While some utilities are equipped with world-class tools, others struggle with basic implementation. The spectrum of performance ranges from utilities that extract exceptional value from their investments to those that cannot fully leverage available technologies. “There is a lot of work to be done for utilities that lack the tools or the expertise to maximise their potential,” he adds.

The complexity of the Indian grid poses unique challenges and opportunities. Anil Yadav, Management Consulting Principal from Accenture Strategy and Consulting, highlights the scale and ongoing innovations in the distribution network, stating, “Our grid is more complex than in other parts of the world, with huge networks and a lot of investments underway.” He mentions city-level initiatives, such as smart city implementations under programmes like RDSS, which are already making strides in integrating advanced technologies. “These innovations will continue to propel India forward,” Anil Yadav notes optimistically.

Addressing these challenges requires adopting cutting-edge technologies tailored to the urban landscape and operational needs. Akilur Rahman, CTO of Hitachi Energy India Ltd, elaborates on solutions such as gas-insulated substations (GIS), modular and prefabricated substations, and mobile substations. “These technologies are essential for urban areas where space is a constraint and load growth demands rapid deployment,” he explains. Akilur Rahman cites the example of Mumbai, where High Voltage Direct Current (HVDC) technology has enabled efficient power distribution without disrupting land use or requiring extensive rights-of-way.

The need for reliable power availability also underscores the importance of asset performance management. Akilur Rahman emphasises, “How can we increase the life of assets and ensure 24×7 power availability? Interruptions lead to power losses and affect productivity and convenience.” Advanced technologies like GIS digital substations, modular prefabricated substations, and battery energy storage systems (BESS) are poised to address these challenges.

The interplay of innovation, investment, and governance will determine how swiftly India can bridge the gaps in its energy ecosystem.

Workforce training, asset management, and data reliability challenges

Despite significant advancements in the Indian power sector through initiatives like Saubhagya (Pradhan Mantri Sahaj Bijli Har Ghar Yojana) and RDSS (Revamped Distribution Sector Scheme), the reliability of power flow remains a pressing concern. Ankit Saboo, Executive Director of Electrolytes, aptly states the current situation: “I can get you the best car in the world, but if you don’t know how to drive it, you can’t really take out everything from it.” This sentiment underscores a significant issue: the lack of a trained workforce in the power distribution sector. While advanced technologies and infrastructure have been introduced, their effectiveness is undermined by the absence of adequately skilled personnel. Ankit Saboo observes that while some utilities perform exceptionally well, the majority face a shortfall in workforce training and capacity building. This gap is particularly evident when effectively utilising modern tools and processes. Without addressing this, the potential of initiatives such as AI, predictive analytics, and IoT for grid management remains untapped. To bridge this gap, a concerted effort is needed to enhance workforce skills through dedicated training programmes, certification courses, and on-ground practice.

Another challenge lies in asset management, as Ankit Saboo argues for the privatisation of assets currently held by the government. He opined, “The sooner it is privatised, the better it might be,” drawing from his experience comparing private companies’ efficiency in managing assets to government utilities. Private players, driven by performance metrics and customer satisfaction, often bring innovation and cost efficiency to asset management, areas where government entities sometimes fall short. This step, however, requires careful policy planning to ensure public interest and affordability.

Vikram Gandotra highlights another foundational challenge: the reliability of data metrics like SAIFI (System Average Interruption Frequency Index) and SAIDI (System Average Interruption Duration Index). He pointed out discrepancies in the methodologies adopted by Discoms for calculating these indices, stating, “The data of SAIFI, which is available in the public domain, is not reliable because they use different methods of calculating.”

It becomes difficult to benchmark performance or demonstrate improvement without a standardised approach to measuring and reporting these indices. Vikram Gandotra stresses the importance of acknowledging this problem collectively, remarking, “Unless we all agree that there is a problem and work on solving it, whatever technology we use… will not be of use.” A unified data collection and analysis framework is essential to create a transparent and reliable foundation for addressing these challenges.

Transforming operational technology amidst challenges and opportunities

The integration of Artificial Intelligence (AI) and Generative AI (Gen AI) into Operational Technology (OT) holds immense promise. Still, it requires strategic evolution and alignment with regulatory frameworks, infrastructure, and data reliability. Operational Technology (OT) has continuously evolved alongside Information Technology (IT) advancements. Starting from basic analog systems probably in the 1960s to IoT-enabled solutions today, the trajectory has consistently aimed at improving efficiency and decision-making capabilities. As Vikram Gandotra aptly notes, “The next big leap lies in leveraging AI tools to analyse the vast amounts of data captured through IoT systems and using it for informed decision-making.”

AI and Gen AI are particularly impactful in asset performance management and workforce optimisation, where millisecond-level reliability isn’t a constraint. For instance, monitoring transformer health using sensors can predict failures weeks in advance, enabling proactive maintenance. Akilur Rehman highlights, “While real-time systems demand 100 percent reliability, AI is indispensable in applications like predictive maintenance and workforce performance management, where immediate responses are not critical.”

Control room operations, often inundated with hundreds of simultaneous alarms, stand to benefit from AI-powered advanced alarm management systems. As Anil Yadav suggests, AI can swiftly correlate patterns and perform root cause analyses, enhancing operator efficiency. Vikram Gandotra says, “An intelligent alarm processing module can focus operator attention on the most critical issues, minimising risks and ensuring stability.”

Despite its potential, regulatory inertia and market readiness hinder AI adoption in OT. Prashant Sinha, COO of Infra Business from Sterlite Power, says, “As long as electricity remains a political tool and regulations do not evolve, the pace of AI implementation will remain slow.” He drew parallels with the software market of the 1990s, suggesting the need for foundational changes to unlock AI’s true potential, particularly in demand-side and generation-side management.

AI’s effectiveness hinges on the accuracy and comprehensiveness of input data. Vikarm Gandotra states, “Any AI tool is only as intelligent as the data it processes. Weak data foundations lead to flawed outputs.” This underscores the need for robust data collection systems to ensure meaningful insights.

Looking forward, the focus must shift to responsible AI, ensuring ethical deployment, transparency, and accountability. Anil Yadav observes, “Responsible AI is essential for sustainable integration; it’s not a plug-and-play solution but a system that requires careful design and execution.” AI and Gen AI hold transformative potential for OT, from asset health monitoring and predictive maintenance to workforce management and advanced alarm systems. However, realising this potential demands regulatory reform, robust infrastructure, and a commitment to responsible AI practices. Prashant Sinha opines, “The market is huge, but without the right regulations and market dynamics, the pace of adoption will be slow.” By addressing these challenges, the OT sector can fully harness the power of AI to meet the demands of an evolving energy ecosystem.

India has immense potential to transform cities into smart, sustainable hubs. However, challenges such as a lack of skilled manpower, asset management inefficiencies, and data metrics inconsistencies must be addressed. Enhanced governance, standardisation, and workforce training are critical to overcoming these barriers. India can harness its strengths to build smarter, more resilient urban ecosystems by fostering innovation, investing in education, and promoting efficient resource management. With a focused approach, the country is well-positioned to lead the global transition towards smart and sustainable energy solutions.