From smart cities to stable grids: A data-driven path to ending energy poverty in emerging economies

I did not enter the energy field through the typical route of climate policy debates or abstract modeling. I entered through blackouts. Growing up in Lagos, power outages shaped daily routines in ways that are impossible to ignore. Families kept candles and generators close. Businesses made financial decisions based on diesel prices. Students planned their reading around unpredictable electricity. Energy poverty was not a statistic; it was a constant presence.

Years later, as a PhD student and power & energy researcher at the University of New Orleans (UNO), I am working on a different side of the problem: designing grids that can support renewable energy at scale without sacrificing stability. My research sits at the intersection of smart cities, grid visibility, digital twins, battery systems, microgrids, and stability modeling. These are diverse topics, but they are linked by a single question: How can emerging economies develop clean, reliable grids without repeating the mistakes of older systems?

In our recent publication in IEEE Sensors Reviews, my co-authors and I argued that smart cities are not defined by apps, dashboards, or slogans; they begin with infrastructure that works. True “smartness” in a city is reflected in its power grid: whether it can detect stress early, predict failures, and respond with resilience. This requires a foundation of granular, real-time data from the distribution network, where most instabilities originate.

This is why I view Advanced Metering Infrastructure (AMI) not just as a billing tool, but as a stability instrument. In a study presented at IEEE SoutheastCon 2025, we showed how AMI data, integrated into an IoT platform, can transform weak distribution networks into observable digital systems. The ability to detect voltage drops, phase imbalance, and feeder overload at the household level allows utilities to identify problems with unprecedented accuracy. When this data is combined with predictive analytics, it becomes possible to anticipate failures rather than react to them.

Similarly, my work on digital twins for smart substations helps operators test interventions before they are implemented physically. Instead of discovering a misconfigured setting during a fault event, operators can simulate the system under various conditions. This is especially important as inverter-based generation becomes widespread because traditional protection and stability mechanisms behave differently with renewable systems.

Another dimension of my research concerns energy storage. In our Measurement: Energy publication on next-generation lithium-ion batteries for electric vehicles, we explored how AI-driven optimization can extend battery life and improve performance. These insights also apply to grid-scale storage, which is essential for smoothing variability in renewable-heavy systems. Better battery placement and scheduling can significantly reduce instability in grids with high solar penetration.

In work on flexible and wearable energy storage devices, we examined how energy systems can integrate more seamlessly into daily life. And in earlier work on blockchain-based peer-to-peer energy trading, we explored how communities can share energy efficiently and transparently, particularly in settings where centralized grids are unreliable.

Although these research areas cover different scales from microgrids to substations to national distribution systems, the underlying principle is consistent: energy systems must be designed around people, not the other way around. Africa’s energy future must prioritize resilience, affordability, and adaptability. With the right tools, AMI visibility, digital twins, and AI optimization, emerging economies can leapfrog traditional infrastructure bottlenecks and build grids fit for a renewable-powered century.

My current work at UNO’s Power & Energy Research Laboratory focuses on small-signal stability, transient stability, voltage behavior, and the integration of inverter-based resources. These challenges are increasingly relevant in the United States as data center demand rises, EV adoption accelerates, and extreme weather events intensify.

If there is anything I have learned so far, it is that the energy transition is not a single technology problem but a system design challenge. It requires integrating engineering, policy, behavior, materials science, and human needs into a coherent framework.

I am committed to this work. Every paper I write, every dataset I analyze, and every model I develop is motivated by a clear belief: reliable electricity is the foundation of modern opportunity. Ending energy poverty requires more than generation; it requires systems that are stable, intelligent, and designed for the realities of the communities they serve.

illuminem Voices is a democratic space presenting the thoughts and opinions of leading Sustainability & Energy writers, their opinions do not necessarily represent those of illuminem.

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