The transformation of electricity grids from centralized, unidirectional models dependent on fossil fuels to decentralized networks powered by renewable energy promises to unlock enormous progress. However, says Bret Simon of Exodigo, coordination between the systems has been difficult. The answer? Artificial intelligence and advanced analytics.
Achieving change in deeply entrenched systems has proven difficult. The interlocking infrastructure that underpins society presents daunting and complex coordination obstacles. These frictions have made the path to decentralized and fully sustainable networks slow and unstable.
I believe we are at an inflection point where artificial intelligence and advanced analytics are perfectly placed to help us navigate.
The decentralized and decarbonized network of the future will rely heavily on increased capacities to unlock its potential efficiently and equitably.
Everything I want to discuss here comes down to one simple and critically urgent goal: ensuring that tomorrow’s energy supplies remain secure, equitable and environmentally sustainable for all communities.
Did you read?
Sensor technology and AI increase transmission capacity by 52%, says Litgrid
Navigating the digital energy era
Pressures on traditional public service infrastructure
The rapid proliferation of distributed energy resources (DERs) (i.e., residential solar, electric vehicles, and battery storage) is driving a dramatic shift from centralized power grids to decentralized, democratic “smart” grids . Artificial intelligence, machine learning and advanced data analytics will play a critical role in helping utilities manage this complex transition while ensuring equitable access.
U.S. renewable energy capacity is expected to double by 2025, and double again by 2030, as adoption of assets such as rooftop solar explodes (Yale Climate Connections). This distributed clean energy boom introduces greater variability and unpredictability into production and use patterns, overwhelming aging utility infrastructure.
Investor-owned utilities in the United States already spend more than $130 billion a year on grid improvements and maintenance, but trillions more will be needed in the coming years just to address the accumulated infrastructure deficits, not to mention facilitating the integration of variable renewable energy sources (IED).
Fundamental changes in consumer behavior are accelerating the transition, putting pressure on traditional customer engagement systems with great diversity in energy consumption patterns.
Tech-savvy energy consumers also expect low rates, reliable service and opportunities to benefit from incentives to sell excess renewable energy back to the grid.
Overcoming these multifaceted pressures requires a coordinated evolution of infrastructure that leverages the interconnectivity of AI and advanced analytics.
The role of AI and multi-sensor technology
Utilities are at the epicenter of this transformation as network operators and electricity providers. They face major challenges in accurate forecasting, infrastructure modernization and balancing the priorities of various stakeholders.
However, an essential element of the infrastructure, the basement grids and ducts, which have immense potential but require high investments, are underutilized despite clear stakeholder preference due to superior resilience and aesthetic benefits.
The opacity of underground infrastructure considerably limits the sustainability of a renewable network. Without precise mapping of buried cables and conduits, adding variable generation from solar and wind risks overloading network visibility.
Advanced, always-on sensor technologies and analytics help power diagnostics on existing underground utilities. Integrating real-time sensor data with AI/ML capabilities enables network simulation, risk detection, and predictive maintenance as waves of distributed resources increase.
Enhanced subsurface mapping provides immense clarity to utilities, helping to optimize investment planning to advance system modeling in the event of a disruption.
A diversity of emerging approaches, from satellite image analysis to drones and even autonomous underground inspections, are making rapid progress tangible. As infrastructure transparency improves, so do the prospects for balanced and sustainable decentralized networks.
Realizing the Smart Grid Vision
“Smart grids” leverage connectivity, automation and intelligence to optimize electricity delivery while enabling wider integration of decentralized renewable energy.
Key capabilities such as advanced customer usage analytics, self-diagnosing and self-healing network architectures, and interconnected microgrids have the potential to fundamentally reshape the service landscape public. But to realize the full benefits of these technologies, infrastructure must keep pace with strategic investments powered by advanced mapping data and grid modeling algorithms.
Sensors and asset analytics can guide targeted network upgrades, while machine learning and artificial intelligence inform load forecasting, outage prediction, and even automated control mechanisms to balance more efficiently real-time supply and demand.
Sustainability for equitable access
In addition to infrastructure demands, equity issues must also be addressed in the context of disrupting traditional public service models that tend to exacerbate existing gaps in reliability, affordability and access for groups disadvantaged.
However, advanced technology also offers the opportunity to ensure inclusiveness and access. Resilient, distributed network architectures help minimize the disproportionate infrastructure threats faced by low-income communities that lack alternatives.
Mapping, modeling and software analysis directly combat excessive energy bills, unlocking efficiency as consumption habits evolve. Access to real-time, integrated data that improves investment planning, customer engagement and regulatory decisions is a powerful equalizer.
The path to follow
A technology that serves all interests; policies that reflect shared priorities; and collaborative roadmaps that promote collective needs.
These technologies and techniques demonstrate the invaluable role of artificial intelligence in upgrading critical infrastructure and building reliable decentralized energy integration as we prepare the grid for the future. As utilities navigate this period of complexity, ethical technology partners are able to drive immense societal impact.
But technology alone cannot drive this transition. Progress relies on the coordination of all stakeholders – all united behind the top priority of safeguarding a resilient, affordable and sustainable energy future.
Utilities must convince reluctant regulators of the critical upgrades needed; policy makers must encourage consumer participation; and technology partners must design solutions that promote equity and accessibility across all socio-economic layers of society.
As consumer habits, business models and climate realities rapidly evolve, it is up to utilities, the pillars of power generation, to ensure our most basic needs remain met. The clean energy transition will never fit neatly into quarterly earnings calls.
Yet forward-thinking utilities that see what’s on the wall will harness technological advances not only to protect the status quo, but also to drive decentralized networks where customer and climate needs seamlessly align.
In this context, artificial intelligence offers much more than just incremental improvements. Mindfully configured, augmenting human capabilities through cutting-edge technology promises to unleash the best in ourselves and the tools we build – a more resilient, equitable and sustainable future for all.
About the Author:
Bret Simon leads U.S. utility and energy partnerships at Exodigo, a non-intrusive, multi-sensor subsurface imaging platform.
Prior to Exodigo, he spent more than 12 years working with electric and gas utility companies, such as Arizona Public Service, Entergy, Duke, PG&E and others.
