Development of an Advanced Smart Grid Data Analytics System for Utilities

The utility client faces difficulties in effectively collecting, storing, and analyzing data from a large-scale smart metering infrastructure. They need to enhance operational transparency, optimize grid management, reduce energy losses, prevent technical failures, and detect illegal energy consumption. Additionally, they seek scalable, flexible solutions to support future expansion goals, such as deploying smart meters to at least 80% of end-users, including around 14 million meters, by 2028.

A large regional utility provider managing extensive electricity distribution infrastructure, seeking to implement smart metering and grid analytics.

• Design and develop an integrated data gathering, storage, processing, and visualization system leveraging cloud technology.
• Enable advanced analytics on massive daily datasets (tens of millions of readings per month) to support operational decision-making.
• Implement real-time monitoring tools, including automated quality indices (e.g., SAIDI & SAIFI) and load modeling for grid planning and optimization.
• Develop machine learning-based modules for detecting illegal energy consumption and balancing energy flows across low- and medium-voltage grids.
• Create an accessible graphical user interface for technical teams to perform complex queries and visualize infrastructure and measurement data geographically and through dashboards.
• Support scalability and cost-effectiveness for planned large-scale deployment and future data growth.

• Integration with smart meters and grid sensors to collect real-time measurement data.
• Data storage infrastructure capable of handling large volumes of high-frequency measurements (e.g., 61.7 million daily readings, 570 GB monthly data).
• Advanced analytics modules including load modeling, reactive energy analysis, and outage index calculations.
• Machine learning algorithms for detecting illegal energy consumption and predicting grid failures.
• Geographical mapping tools for visualizing measurements, theft zones, and infrastructure status.
• Automated calculation of grid quality indexes such as SAIDI & SAIFI.
• Simulation tools for transformer load and simultaneity factor analysis to support grid expansion planning.

• Smart metering infrastructure (AMI) data sources
• Grid sensors and balancing meters data systems
• Existing utility management and operational systems
• Legal and security compliance systems for data integrity and privacy

• System must process and store at least 61.7 million readings daily and 570 GB monthly data, with scalable architecture.
• High system availability and reliability to support 24/7 operations.
• Data security and privacy compliance aligned with industry standards.
• Cost-effective operation of cloud resources, optimized to reduce operational costs over time.
• Fast query response times for complex data analysis and visualization tasks.

The deployment of the advanced data analytics platform is expected to enhance operational transparency, reduce technical failures, and lower energy losses in the distribution network. It will facilitate faster detection of illegal activities, support strategic grid planning, and optimize infrastructure investments. Overall, the system aims to improve energy supply stability, decrease commercial losses, and enable data-driven decision-making, supporting large-scale smart meter deployment initiatives.