Energy Management/Energy Efficiency

How AI supports sustainability

  • As digitalization progresses rapidly, Artificial Intelligence (AI) is being applied to various fields.
  • Efforts are being made for sustainability in industrial sites such as plants.
  • AI helps make decisions for energy efficiency and savings through data analysis.
How Artificial Intelligence supports sustainability

Digitalization in the industry has been accelerating ever since the 2021 pandemic made contactless business the new normal.

Businesses have adopted Cloud and AI-driven digital applications to fit their purpose: enable working from home, “remote everything,” and to build smart factories, to name just a few.

Technological disruptions as a way to achieve digital transformation have justified the role of AI than ever before in helping businesses get just enough resources they need and to discern valuable information that really matter to them.

AI should be beneficial rather than simply intelligent. With this principle, AI has been built and deployed in ways that generate valuable data that contributes to improve decision -making, productivity and efficiency for industries.

Businesses were not only hit by supply chain challenges and shortage of workforce competencies, but also found themselves forced to shoulder the responsibility to reduce carbon emissions.

All of these pushed industries to respond by reshaping their business landscapes. They knew that laying the foundation for sustainable business through energy transition with AI as the enabler was the way to address both pandemic-driven challenges as well as to adjust to climate change.

Energy transition can be swift, if coordinated, to achieve net-zero. This transition requires significant investment, but AI can substantially contribute to accelerate reliable and low-cost energy transition by helping us learn and understand the exact usage of energy in every infrastructure so that we can measure and take action accordingly to save energy.

As we become more energy efficient, increasing capacity system-wide becomes unnecessary as well allowing operators to save replacement costs. For the past two years, AI application for energy efficiency has dramatically increased in all industries.

AI has had many different applications in plant operations, but in terms of next generation smart manufacturing, we are moving rapidly towards data-driven software-based automation.

For Schneider Electric, it means delivering innovative software and services, helping clients achieve “remote everything” and adhering by the golden rule of “openness, partnerships and agnostic” to make the integration happen for data-driven software-based automation. Data-driven software-based automation is driving more integration trends.

Energy and automation in the industry are now coming together and no longer operated in silos. Based on the sustainability agenda and the needs to accelerate de-carbonization and increase efficiency now, energy and automation run in a common data environment.

This integration has proven to give direct benefits of up to 20% Capex saving, up to 10% saving in process energy usage, up to 15% reduction in downtime and up to 3% pts improvement in profitability.

Digital twin is integrating the lifecycle to generate valuable insights for integrated asset management. We are increasingly moving towards using a full digital twin approach that follows the same infrastructure, the same operations for the entire lifecycle, unlike in the past when silos in the physical infrastructure, between the phase of design and build, and between the phase of operations and maintenance was prevalent.

Schneider Electric group provides solutions enabled with a full digital twin from the design phase to maintenance for the entire operation cycle with the same digital environment. This provides AI very stable and reliable data sets to process in real-time to efficiently manage the design, build, operation, and maintenance of the physical system.

The need to drive sustainability and efficiency at corporate-level is transforming site-by-site management into integrated company management.

Resources and data that were once managed at individual sites are now integrated and managed at the corporate level at the unified operation center with the goal to save Capex and achieve sustainability in addition to improve efficiency.

The prerequisite to these big integration trends is digitization. Digitization allows companies to integrate their sites and the entire supply chain to gain better visibility and control over performance. I

n an AI-embedded integrated system, system administrators and operators are provided with insights generated from data collected that enables efficient operation, maintenance, and decision-making.

Businesses have had to face a double-whammy of dealing with crisis management and accepting the social responsibility to address exacerbated climate change risks in these unprecedented times.

The pandemic, however, accelerated the application of innovative technologies for energy transition and sustainability. We are already seeing the value of AI in data analytics to achieve energy efficiency.

Digitalization is improving performance efficiency and facilitating energy transition. The opportunity to drive sustainability lies in applying various digital technologies that exist today.

Business continuity and future breakthroughs across industries rely on making the best out of these technologies to address challenges posed today.

Please visit this article(in Korean) if you’d like to obtain more information.

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