Smart electricity for urban India 

Incorporating smart grids facilitates the seamless integration of renewable energy sources into the power distribution network.

In the vibrant landscape of India’s urban upliftment, the integration of smart electricity systems stands as a beacon of progress within the framework of smart cities. As metropolitan areas evolve into hubs of innovation and efficiency, deploying intelligent and adaptive electricity infrastructure becomes paramount.

Smart electricity in Indian smart cities involves implementing cutting-edge technologies to enhance energy management, reduce wastage, and promote sustainability. Advanced metering systems enable real-time energy consumption monitoring, allowing residents and businesses to make informed decisions about their usage patterns. This leads to cost savings and contributes to a greener, more eco-friendly urban environment.

Moreover, combining smart grids facilitates the seamless integration of renewable energy sources into the power distribution network. Solar and wind energy and other sustainable options play a pivotal role in meeting the rising energy demands of burgeoning urban populations. This transition to cleaner energy aligns with India’s commitment to environmental stewardship and addresses the challenges of conventional energy sources.

The advent of smart electricity in smart cities signifies a transformative step towards a more intelligent, efficient, and sustainable future. By embracing innovative technologies and prioritising environmentally conscious practices, these cities are not only meeting the present energy needs. Still, they are also laying the foundation for a resilient and progressive nation.

AI and machine learning in power systems

AI and machine learning find significant applications in predictive maintenance, particularly substation maintenance. With vast data streams from SCADA and BMS systems and real-time camera feeds, these technologies enable the creation of virtual maintenance environments.

Anil Yadav from EY says, “AI and machine learning (AIML) find significant applications in industrial settings, particularly in maintenance. For instance, in substation maintenance within the transmission sector, the integration of AI and ML is pivotal. The influx of vast data from SCADA and BMS systems, coupled with real-time feed from cameras, allows virtual environments to mimic maintenance processes. This enables training maintenance crews by providing a lifelike simulation of tasks and scenarios.”

“Predictive maintenance is another compelling use case where AIML analyse asset data, such as that from transformers, to anticipate and prevent machinery failures. These applications are currently in the POC stage, demonstrating the potential for transformative impacts in enhancing operational efficiency and minimising risks in industrial contexts,” Anil adds.

Akilur Rahman from Hitachi Energy says, “At Hitachi Energy, Anil Yadav highlighted the use of AIML for predictive maintenance in energy infrastructure. Sensors in transformers and substations generate data, enabling AIML models to predict failures. This augments predefined algorithms in asset performance management.”

“Another crucial application is energy forecasting, particularly for renewables like solar and wind. Given their intermittent nature, AIML factors in variables such as panel condition, inverters, converters, and environmental factors for accurate predictions. While plans involve integrating AI/ML into protection and control systems, the current focus is on a learning phase to develop algorithms. Real-time requirements in protection and control demand 100% accuracy, a threshold AI/ML aims to achieve through continuous learning,” he adds.

Murali Shankar from FluentGrid adds that one crucial application of AI in the energy industry is demand prediction for efficient power trading. AML techniques aid in forecasting power consumption patterns and facilitating grid management. An ongoing project involves predicting power grid anomalies by analysing consumption patterns, followed by continuous model refinement through feedback from field visits. He says, “This iterative process enhances anomaly detection accuracy, optimising identifying potential issues like pull fridge incidents. Analysing signal strength patterns aids in predicting optimal times for meter pulls, ensuring adherence to SLAs in our DSL scheme. This dual focus on anomaly detection and signal strength optimisation enhances overall operational efficiency.”

Smart city development and power infrastructure

India is actively pursuing smart city development, integrating advanced technologies for efficient urban management. The focus extends to upgrading power infrastructure, implementing smart grids, and deploying renewable energy solutions to enhance sustainability and meet the growing energy demands of its rapidly urbanising population.

Aniruddha Shahahpure from CyanConnode says, “In 2016, India embarked on a challenging mission to establish 100 smart cities, a complex endeavour for a developing nation. The goal was to enhance urban living, tailoring solutions to each city’s unique needs rather than replicating global models. A network of 100 labs was set up, experimenting with approaches to create citizen-centric, livable environments. Differentiated by geography and demographics, these labs identified what worked best for each location. Among the crucial components were 100 command control centres, including one in Pune, where the speaker served as a session director during the COVID-19 pandemic.”

“These centres played a pivotal role in data analysis, utilising artificial intelligence and machine learning to model the spread of the virus and manage containment zones effectively. The success of these initiatives signals a need for widespread implementation and continuous improvement in cities nationwide,” Shahapure adds.

Commenting on the smart city development, Anil Yadav from EY says, “In the realm of smart cities and their reliance on technology, a robust smart electricity infrastructure forms the foundation for various technological advancements. Implementing a city-wide Distribution Management System (DMS) is pivotal for enhancing power reliability and minimising outages. Automation systems within the city should efficiently detect and rectify faults, enabling swift responses and performance improvements.”

“Technologies like Distributed Energy Resource Management (DRM) systems play a crucial role in managing diverse energy resources, including battery storage, electric vehicles, and solar installations. Furthermore, deploying smart meters is integral to the overall smart city strategy. This holistic approach, encompassing DMS, VPPs, DRM systems, and smart meters, ensures a resilient and technologically advanced framework for smart cities to thrive,” he adds.

Challenges and Opportunities

The future of smart electricity relies on the transformative impact of connected devices on the electricity grid. Emphasis should be placed on leveraging data from smart meters, substation monitoring, and renewables for grid automation, with insights on opportunities and challenges in India’s renewable energy landscape.

Murali Shankar from Fluentgrid says, “The industry grapples with the challenge of harnessing data from connected devices in the electricity grid. While the focus is on smart metering for data collection, the crucial question is what more can be done with this data. Integration of substation monitoring, solar panel, and EV charging station data into a comprehensive data warehouse is key. The convergence of these datasets can provide insights for ensuring stable, high-quality power for consumers.”

“Initiatives to integrate SCADA systems with AMI systems are underway, forming the backbone of efficient transmission and distribution management. Exploring technologies like blockchain and smart contracts may automate scheduling, minimising deviation settlement. The widespread implementation of such solutions will drive automation and efficiency in the electricity grid,” Murali Shankar adds.

Akilur Rahman opines that India possesses significant potential for renewable energy, offering opportunities to establish large utility-scale systems in diverse locations like the Himalayas, deserts, and offshore wind sites. While setting up renewable plants is relatively quick and cost-effective, the challenge lies in efficiently transferring the generated power to load centres. Evacuating power requires addressing technical, financial, and time-related obstacles, particularly in planning transmission systems. High Voltage Direct Current (HVDC) technology proves beneficial by minimising footprint and infrastructure costs, aiding in quicker implementation.

He says, “Challenges also encompass securing right-of-way for transmission systems. Embracing technologies like HVDC, VSC, flexible AC transmission, and distributed energy resource management presents avenues for overcoming obstacles and optimising renewable energy integration. Balancing these challenges and opportunities is crucial for advancing India’s renewable energy landscape.” 

Shahapure says, “I emphasise the immense opportunities and risks of future technologies, particularly quantum computers. It is crucial to thoroughly assess existing systems, identify vulnerabilities, and establish task forces to address these challenges. The potential for development, employment, and innovative products is vast, evident in renewable projects enhancing IoT security.”

“Despite challenges, opportunities abound, paving the way for a secure and prosperous future. University students are already exploring such systems, showcasing the substantial potential in this rapidly evolving landscape,” Shahapure added.

“The industry grapples with the challenge of harnessing data from connected devices in the electricity grid. While the focus is on smart metering for data collection, the crucial question is what more can be done with this data.” – Murali Shankar Gopalakrishnan, Senior VP, Solutions and Product Engineering- Fluentgrid Limited.

“AI and machine learning (AIML) find significant applications in industrial settings, particularly in maintenance. For instance, in substation maintenance within the transmission sector, the integration of AI and ML is pivotal.” – Anil Yadav, AVP – Technology consulting- EY 

“I emphasise the immense opportunities and risks of future technologies, particularly quantum computers. It is crucial to thoroughly assess existing systems, identify vulnerabilities, and establish task forces to address these challenges.” – Aniruddha Shahapure, Chief Operating Officer- CyanConnode India

“Embracing technologies like HVDC, VSC, flexible AC transmission, and distributed energy resource management presents avenues for overcoming obstacles and optimising renewable energy integration.” – Akilur Rahman, Chief Technology Officer (CTO), Hitachi Energy India