Q&A with Schneider Electric’s Gary Lawrence

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Gary Lawrence, Power & Grid Segment President at Schneider Electric
Gary Lawrence, Power & Grid Segment President at Schneider Electric, details AI’s potential in the energy transition and energy efficiency

AI is everywhere and is undoubtedly having a transformative impact, whether increasing data centre demand or optimising supply chains.

AI is overhauling the energy landscape, too. The intelligence offers smarter, more efficient ways to manage power systems, reduce carbon footprints and optimise energy use.

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From smart grids to AI-powered home and building energy management, these technologies are driving the shift towards greener, more sustainable energy solutions. 

AI is also helping industries meet decarbonisation goals through predictive insights and real-time data analytics. 

However, the integration of AI into the energy sector presents challenges, including the need for grid upgrades and the high energy consumption of the AI systems themselves.

Gary Lawrence is Power & Grid Segment President at Schneider Electric. With more than 20 years of experience in electro-intensive industries, Gary has been at the forefront of developments and transformations industry-wide. 

Since joining Schneider Electric a decade ago, Gary has led teams focused on electrification, digitalisation and sustainability. 

Now overseeing strategic direction for utilities, he plays a crucial role in shaping the company’s contributions to the energy transition. 

In this Q&A, Gary shares insights on how AI and other technologies are transforming the future of energy management.

Q. In your own words, how does Schneider Electric and your work at the company positively contribute to the energy space? 

Schneider Electric is a leader in electrification and digitalisation, pioneering Electricity 4.0 and integrating digital solutions into energy infrastructure. 

We facilitate the efficient integration of renewable energy sources, crucial for decarbonisation goals as the planet exceeds global warming of 1.5C above pre-industrial levels.   

As traditional grids struggle to accommodate the increasing demand from renewable sources and electrification trends like electric vehicles, our smart grid technologies play a pivotal role by enhancing grid resilience and flexibility.

We also collaborate with organisations across the globe to implement carbon reduction plans and support for renewable energy adoption.

At Schneider Electric, we equip grid operators and large energy users with the hardware and software and expertise needed to make energy transition possible. By offering these solutions  that bridge the gap between digital and electric technologies, we’re leading the global transition towards a more sustainable, low-carbon economy for all.

Q. What do you see as the main challenges and opportunities in integrating AI-powered home and building energy management systems with the broader energy grid? 

It is our view that artificial intelligence (AI) might be the next big step to make energy management systems and grids smarter and more effective. 

The new energy landscape is growing in demand and complexity and we must manage our power systems to meet demand while wrestling with scarce capacity. 

The all-electric, all-digital home and building can both produce and consume energy. Smart digital management solutions add resilience to operations, optimises costs throughout the home and building lifecycle and helps reduce the overall CO₂ footprint.

To be more effective and more efficient, AI-infused smart buildings, homes and grids need perfect orchestration. Existing grid infrastructure needs significant upgrades to be able to handle  and facilitate AI technologies effectively.

In addition, investments in digitalisation, the deployment of smart grid advanced solutions and regulatory frameworks also need to be changed to support new AI innovations while ensuring data security for grid users.

Q. How do you envision AI technologies evolving to further support the decarbonisation of energy-intensive industries and what role will solutions play in this transition? 

AI can offer real-time data analytics, predictive insights and automated control mechanisms. For instance, forecasting energy demand and supply, optimising storage usage and facilitating smart grid applications.

This helps industries to reduce their carbon footprint and comply with stringent environmental regulations.

AI-powered tools can also identify inefficiencies in energy usage, which can reduce waste and costs associated with energy-intensive processes. Actionable insights enable these technologies to support the transition towards cleaner energy sources while ensuring grid reliability and resilience.

But AI infrastructure is not electrically frugal. Major AI vendor shipments in 2023 estimated to consume as much as 14TWh, equivalent to the annual power of more than 1.3 million US households. 

As such, AI should not be the end-all solution to the energy transition and should be supported by other available technologies like process electrification, green hydrogen and energy management systems to boost energy efficiency in the long run.


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