The power distribution segment in India is undergoing significant transformation, driven by advancements in technology and constant search for efficient and sustainable energy management solutions. Several new and emerging technologies are being adopted to improve the distribution infrastructure, enhance grid reliability, enable renewable energy integration and empower consumers with smart solutions. These include advanced metering infrastructure (AMI), distribution automation solutions, internet of things (IoT), analytics and artificial intelligence (AI). These solutions aid in boosting the efficiency and productivity of the power sector in a big way. Earlier, the majority of operations and distribution processes in the power sector were manual, which led to poor control, lack of transparency and unreliable information, resulting in enormous power loss.
New IT and OT solutions
cSmart grids: Smart grid technology that integrates advanced communication, control and monitoring systems into the traditional power grid infrastructure is increasingly being adopted by utilities. It leverages information technology (IT) and real-time data analysis to optimise generation, distribution and consumption of electricity. One of the key components of a smart grid is AMI, which involves the installation of smart meters that provide real-time energy consumption data to both consumers and utilities. These meters enable remote monitoring, accurate billing and improved load management. By offering consumers detailed insights into their energy usage patterns, AMI promotes energy conservation and facilitates demand response programmes. Various other technologies such as supervisory control and data acquisition, remote terminal units and distribution management systems are being deployed to automate distribution networks. Notably, the government’s Revamped Distribution Sector Scheme (RDSS) aims to install a total of 250 million smart meters by 2025-26.
- ADMS: Distribution utilities are increasingly adopting advanced distribution management systems (ADMS) as a prominent technology. ADMS plays a crucial role in automating outage restoration and enhancing the performance of distribution grids. It provides comprehensive support for the entire distribution chain, encompassing management and optimisation functions. ADMS encompasses various features including fault identification, isolation and restoration capabilities. It also facilitates peak demand management, voltage optimisation, volt ampere reactive levels and voltage reduction for conservation purposes, as well as offers support for microgrids and electric vehicles. ADMS is becoming a vital tool in improving the efficiency and reliability of distribution utilities.
- IoT and sensors: IoT and sensor technologies are being used to collect real-time data on various parameters such as voltage, current, power quality and temperature. These sensors provide valuable insights into the condition of the distribution infrastructure/assets and enable predictive maintenance. IoT-based applications also enable remote monitoring and control of devices, improving operational efficiency and reducing manual interventions.
- Blockchain technology: Blockchain has the potential to revolutionise the power distribution sector by providing secure, transparent and decentralised platforms for energy transactions and peer-to-peer energy trading. Blockchain-based solutions can enable efficient billing and settlements, facilitate renewable energy certificate trading and create virtual power plants. Several pilot projects are exploring the use of blockchain in India’s energy sector. For instance, Tata Power Delhi Distribution Limited and Power Ledger, in association with the India Smart Grid Forum, rolled out the first peer-to-peer solar energy trading pilot project in Delhi.
- AR/VR: Augmented reality (AR) and virtual reality (VR) technologies are finding applications in various industries including power distribution. These technologies offer new ways to visualise, simulate and interact with the distribution infrastructure, improving operational efficiency, and training and maintenance activities. The technology provides immersive training environments for power distribution personnel and enables hands-on learning, enhances situational awareness and helps trainees develop necessary skills to handle different scenarios and emergency situations.
- AI/ML: AI and machine learning (ML) technologies have the potential to revolutionise power distribution utilities by enhancing their operations and performance. By harnessing AI and ML, utilities can gain valuable insights that enable them to predict network failures, schedule timely interventions and prevent disruptions. Moreover, these technologies are instrumental in demand forecasting and conducting time-of-day predictive analysis. To address the high volume of consumer queries and interactions, many distribution companies are now utilising mobile applications and website chatbots.
Asset management strategies focus primarily on condition assessment, refurbishment, replacement of assets, maintenance management and the adoption of technologies for extending asset life. Distribution companies today are evolving their asset maintenance approach and adopting new asset management strategies. Asset performance management is one of the most prevalent use cases of IoT. IoT enables condition-based maintenance, predictive maintenance and risk-based maintenance. A transition from reactive maintenance to IoT-enabled proactive maintenance can improve the reliability and availability of assets; reduce maintenance cost; minimise or eliminate unplanned downtime, thereby lowering productivity loss and the need to keep an inventory of spare parts for emergency repairs; as well as improve the productivity and safety of repair crews.
Advanced analytics, coupled with AI techniques, are being employed to analyse large volumes of data generated by power distribution systems. These technologies help in identifying patterns, predicting equipment failures, optimising maintenance schedules and improving the overall system performance. AI-based algorithms also enable intelligent demand-side management, load forecasting and load balancing, leading to more efficient energy utilisation.
Moreover, geographic information system (GIS)-based mapping of power distribution assets involves the use of spatial data and technology to create accurate and comprehensive maps of the distribution infrastructure. It allows utilities to visualise, analyse and manage their power distribution assets in a geospatial context, providing valuable insights for planning, operations and maintenance activities. By overlaying network components on the map, utilities can identify areas of high load, voltage drop, or congestion. This information aids in planning system upgrades, optimising load balancing and determining the most suitable locations for new infrastructure.
Network strengthening solutions
With regard to cables and conductors, cross-linked polyethylene (XLPE) cables, underground cabling and aerial bunched cables (ABCs) are increasingly being adopted to enhance the reliability, efficiency and safety of power distribution systems. These solutions address various challenges associated with traditional overhead lines, improving performance and reducing the risk of outages. XLPE cables and underground cabling exhibit lower losses compared to traditional cables, resulting in improved energy efficiency and reduced operational costs. The use of ABCs is widely gaining traction for overhead power distribution networks since they provide benefits such as low power loss, negligible current leakage, protection against power theft, low maintenance requirement, lower fault rate and resilience against environmental factors (wind and falling trees).
With regard to tower designs, utilities are increasingly adopting monopoles and multicircuit transmission towers that have lesser right-of-way requirement, as against the conventional lattice towers. There have been advancements in tower foundation designs, survey techniques and installation methods to ensure speedy execution and sturdy infrastructure. Besides, utilities are adopting model-based software products to increase productivity and ensure accuracy during the construction layout process. Meanwhile, on the transformer and substation front, distribution utilities are increasingly opting for dry-type transformers and K-Class (ester) fluid-filled transformers, gas-insulated switchgear, hybrid switchgear and intelligent switchgear.
Challenges and the way forward
While the adoption of new and emerging technologies in the Indian power distribution segment holds immense potential, it also poses several challenges. One of the key issues is financial constraints as limited financial resources and difficulties in securing financing impede the widespread deployment of these technologies. Second, retrofitting and integrating new technologies with legacy systems can present compatibility and interoperability challenges. Third, there is a shortage of technical expertise in the sector. Successful implementation of new technologies requires a skilled workforce proficient in areas such as advanced metering, automation, data analytics and renewable energy integration. Further, the absence of uniform standards and protocols can create compatibility issues and hinder the adoption of new technologies. Moreover, data management and privacy are critical challenges in the era of advanced technologies as the implementation of these technologies generates a vast amount of data from various sources.
To conclude, the the adoption of advanced technologies is driven by the country’s increasing energy demand, need for grid modernisation and focus on renewable energy integration. These technologies are helping utilities and consumers optimise their energy usage, reduce costs and contribute to the overall decarbonisation goals of the country. Strong policy support, capacity building initiatives and financial incentives can help overcome various challenges and accelerate the adoption of new and emerging technologies in the power distribution sector.