How AI and advanced analytics will be key for the grid of tomorrow

The transformation of electricity grids from centralised, unidirectional fossil fuel-dependent models to decentralised networks powered by renewables promises to unlock tremendous advancements. However, explains Bret Simon of Exodigo, coordinating this across systems has been difficult. The answer? Artificial intelligence and advanced analytics.

Enacting change across deeply entrenched systems has proven difficult. The interwoven infrastructure that underpins society introduces daunting and complex coordination hurdles. This friction has made the path toward fully sustainable, decentralised grids slow and choppy.

I believe we are at an inflection point where artificial intelligence and advanced analytics are perfectly poised to help us navigate.

The decentralised, decarbonised grid of the future will rely heavily on augmented capabilities to unlock its potential, efficiently and equitably.

Everything I want to discuss here comes back to a simple, critically urgent focus – making sure tomorrow’s energy supplies remain secure, equitable and environmentally sustainable for all communities.

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Pressures overwhelming traditional utility 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 electricity grids to decentralised, democratic “smart” grids. Artificial intelligence, machine learning and advanced data analytics will play a critical role in assisting utilities in managing this complex transition while ensuring equitable access.

US renewable energy capacity is projected to double by 2025, and double again by 2030 as the adoption of assets like rooftop solar explodes (Yale Climate Connections). This distributed clean energy boom introduces greater variability and unpredictability in generation and usage patterns, overwhelming aged utility infrastructure.

Investor-owned utilities in the US already spend over $130 billion annually on grid upgrades and maintenance, but trillions more are required in coming years just to address accumulating infrastructure deficits, let alone facilitate the integration of variable renewable energy sources (EEI).

Fundamental shifts in consumer behaviour are accelerating the transition, putting pressure on traditional systems of customer engagement with a wide variance in energy consumption patterns.

Tech-savvy energy consumers also expect low rates, service reliability, and opportunities to earn incentives for selling excess renewable power back to the grid. 

Overcoming these multifaceted pressures requires a coordinated evolution of infrastructure that harnesses the interconnectivity of AI and advanced analytics.

The role of AI and multi-sensing technology

Utilities sit at the epicentre of this transformation as grid operators and electricity providers. They face acute challenges in accurate forecasting, infrastructure upgrades, and balancing the priorities of diverse stakeholders.

However, a core infrastructure element, underground grids and conduits, present immense potential yet require high investment, and so, are underutilized despite clear stakeholder preference given superior resilience and aesthetic benefits.

The opacity of underground infrastructure severely constrains future-proofing a renewable grid. Without accurate mapping of buried cables and conduits, adding variable generation from solar and wind, risks overloading grid visibility.

Always-on, advanced sensor technologies and analytics help power diagnostics on existing underground networks. Integrating real-time sensor data with AI/ML capabilities empowers grid simulation, risk detection and predictive maintenance as the waves of distributed resources swell.

Enhanced underground mapping unlocks immense clarity for utilities – helping to optimize capital planning to advance system modelling amid disruption.

A diversity of emerging approaches, from satellite imagery analysis to drones and even autonomous underground inspections, make surging progress tangible. As infrastructure transparency improves, so do the prospects for balanced, sustainable decentralized grids.

Realising the smart grid vision

“Smart grids” leverage connectivity, automation and intelligence to optimize power delivery while enabling broader decentralised renewable energy integration.

Key features like advanced customer usage analytics, self-diagnosing and self-healing network architectures, and interconnected microgrids have the potential to profoundly reshape the utility landscape. But to fully reap the benefits of these technologies, infrastructure must keep pace through strategic investments powered by advanced mapping data and grid modelling algorithms.

Sensors and asset analytics can guide targeted grid upgrades while machine learning and artificial intelligence inform load forecasting, outage prediction and even automated control mechanisms to balance real-time supply and demand more efficiently.

Future-proofing for equitable access

In addition to infrastructure demands, equity issues must also be addressed within the disruption to traditional utility models that tend to exacerbate existing gaps across reliability, affordability, and access for disadvantaged groups.

However, advanced technology also provides the ability to safeguard inclusivity and access. Resilient, distributed grid architectures help minimise disproportionate infrastructure threats facing lower-income communities lacking alternatives.

Mapping, modelling and software analytics directly combat bloated energy bills, unlocking efficiencies as consumption habits evolve. Access to real-time integrated data, improving decisions across capital planning, customer engagement and regulation, serves as a powerful equaliser.

The way forward

Technology that serves all interests; policies that reflect shared priorities; and collaborative roadmaps that value collective needs.

These technologies and techniques demonstrate the invaluable role of artificial intelligence in upgrading critical infrastructure and building reliable decentralised energy integration as we future-proof the grid. As utilities navigate this period of complexity, ethical technology partners are positioned to drive immense societal impact.

But technology alone cannot drive this transition. Progress relies on coordination across the entire symphony of stakeholders – all united behind the acute priority of safeguarding resilient, affordable and sustainable energy futures.

Utilities must convince reluctant regulators of critical upgrades needed; policymakers must incentivise consumer participation; and technology partners must design solutions that drive equitability and accessibility across the entire socio-economic strata of society. 

With consumer habits, business models and climate realities all evolving swiftly, the onus rises on utilities as the linchpins of power generation to ensure our most fundamental needs remain met.  The clean energy transition will never fit neatly into quarterly earnings calls.

Yet visionary utilities who see the writing on the wall will harness technology advancement not just to protect the status quo, but to drive decentralised grids where customer and climate needs seamlessly align.

In this frame, artificial intelligence offers more than just incremental improvements. Configured conscientiously, augmenting human capability through leading technology promises to unlock the very best within ourselves and the tools we build – a more resilient, equitable and sustainable future for all.

About the author:

Bret Simon leads US utility and energy partnerships at Exodigo, a non-intrusive, multi-sensing subsurface imaging platform.

Before Exodigo, he spent 12+ years working with electric and gas utilities companies, such as Arizona Public Service, Entergy, Duke, PG&E, and others.