How AI Can Help Cut Energy Costs While Meeting Ambitious ESG Goals

Rising and volatile energy prices, fueled in part by geopolitical conflicts, are putting business leaders under urgent pressure to cut costs. Energy is eating up an increasing share of corporate budgets, leaving less funding for innovation and growth.

At the same time, consumers, investors, and regulators increasingly expect companies to embrace environmental, social, and governance (ESG) principles and speed up with factual decarbonization. In most industries, thriving in the long term requires urgent progress on ESG. Many enterprises have set ambitious goals for reducing their carbon footprints but are struggling to achieve them.

Artificial intelligence (AI) is changing that today, helping companies optimize energy consumption, deploy renewable energy sources, and manage infrastructure for EVs. With the proper AI technology and energy expertise, any organization with sufficient digitization experience and infrastructure can tap the potential of AI to reduce operating costs while moving the needle on sustainability.

“If we want to ‘decarbonate’ the planet, we need industries to electrify much more, to be more efficient, to use less energy, and to create less waste,” says Philippe Rambach, SVP and Chief Artificial Intelligence Officer of Schneider Electric. “That requires a combination of digitization and AI to optimize our processes.”

The Power of AI

Addressing the twin challenges of energy and sustainability can be challenging: companies need to integrate renewable energy efficiently while ensuring reliable power, but renewable energy sources produce an inconsistent supply that changes with shifting environmental conditions. Such measures as introducing a fleet of EVs requires businesses to manage demand, expand grid capacity, and install charging infrastructure while accounting for energy costs and grid stability.

AI is critical for addressing these obstacles at scale, drawing on massive volumes of data—more than humans could reasonably process—to reveal patterns of energy use and areas of inefficiency. Using AI can help companies incorporate renewable power sources, manage better decisions about EV charging infrastructure, and reach their sustainability objectives, all while cutting energy costs.

As more companies become “prosumers”—both consuming and producing energy—the combination of Big Data and AI can help them use energy efficiently and pivot in real time.

AI and the Future of Energy Management

Despite the best intentions, 85% of AI projects are projected to fail. Successful AI implementation requires organizations to use custom-made solutions that integrate seamlessly into existing operations and processes. And beyond technology, these organizations also need external domain expertise on AI, energy management, and industrial automation from a partner with extensive experience.

Innovations in three cases illustrate the potential of AI to help organizations curb energy use and promote sustainability.

1. A Carbon-Neutral Distribution Center

The 40-year-old supermarket chain Lidl operates approximately 12,000 grocery stores and more than 200 distribution centers in 31 countries.

The company opened a distribution center with Finland’s largest industrial microgrid, hosting 1,600 solar panels and a battery storage system that lightens the load on the national power grid. Its advanced heating and cooling system stores excess heat to reuse in cold weather and provides hot water to around 500 households.

Using AI-enabled forecasts and optimization, the center operates on 100% renewable energy and has reduced its energy costs by 70%.

2. Energy Management for a Fleet of EVs

Schneider Electric manages a large fleet of electric vehicles (EVs) at its headquarters outside Paris. The sheer scale of this fleet could disrupt the smooth operation of the building if all the EVs were charged at the same time.

To address this issue, the company uses an energy-management solution that monitors such critical factors as power availability, weather conditions, and energy sources to prevent power surges during charging peaks and to generate, distribute, and manage power from multiple sources.

At the heart of this approach is the Edge Control component, which optimizes the distribution of power to EVs in real time and maintains a balance between charging needs and available power, using cloud-based AI-driven analytics.

By accounting for such variables as power demand and weather conditions, the analytics ensures optimal power distribution to the building from various energy sources in a microgrid. The result is significant building power efficiency and a marked reduction in carbon footprint.

3. Transforming a Factory in Northern France

Renault Group, the French car manufacturer, set the ambitious goal of achieving a negative carbon balance at its plant in Flins, France, by 2030. To do so, the automaker installed environmentally friendly switchgear and smart sensors that enabled forecasting and remote monitoring of equipment and outages. As a result, the factory has reduced costs and made advances on its sustainability objectives.

Enabling Sustainability and Innovation

The transition to renewable energy cannot happen without AI. But every organization has its own needs and objectives, and implementing the latest off-the-shelf AI technology may not be enough to achieve them.

Schneider Electric’s Rambach says, “Small additional investments in AI solutions in energy optimization and industrial automation can unlock the value of the large investments companies have already made in the cloud and in data gathering.”

Implementing AI can help companies slash energy spending and operate sustainably. Tackling these complex challenges by combining AI with human expertise can have an impact far beyond the organizations leading these efforts.

Discover AI solutions with Schneider Electric.

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