Some time ago, I wrote a blog about how sustainability and digitization go hand-in-hand. I mentioned the power of Artificial Intelligence (AI) to help us make smarter decisions that rely on hard facts and enormous amounts of data – providing companies operational benefits and supporting us on our path to sustainability.
But there’s a catch: To be future-ready, companies must start combining AI, human skills, and trusted partnerships NOW. After all, climate change is happening NOW. Rising sea levels, and intensifying wildfires, storms, droughts and floods hammer home that message every day. The damage is undeniable, and the clock is ticking.
Human and artificial, the energy challenge requires intelligence
Let’s be clear: clean energy and efficient energy management are key to attacking the climate crisis. And the true value of Artificial Intelligence in energy management springs to life when technology meets human expertise. When you equip energy market experts with data-based insights and digital technologies, you get better-informed corporate strategies, quicker decision making, and greater operational efficiency.
AI is still a relatively new kid on the block – and many people may still have the impression that it’s a theoretical discipline that’s not yet able to deliver practical solutions.
The reality, however, is that we already apply AI to analyze, simulate, test, use logic, learn, predict, and adjust over time. And those capabilities can help companies and societies advance toward greater energy efficiency and decarbonization.
Three ways AI can shape energy management
More efficient use of energy
Companies collect large amounts of data that they can use to maximize efficiency. Turning that data into insights can be a challenge – but one that AI can help with.
AI can accurately track and anticipate consumption trends, notice where changes need to be made, and automatically fine-tune systems to ensure optimum efficiency. And it can help companies react instantly to demand response opportunities and to the increasingly frequent disruptions caused by extreme weather.
Diversification of energy sources
AI can support companies in introducing renewable energy sources and controlling their carbon footprint – giving clean energy a better chance in the market.
Companies producing their own renewable energy can apply AI and predictive analytics to weather data to help determine peak times for generation and optimize the use of distributed-energy storage systems or batteries.
Smarter energy buying
AI can examine complex market trends and dissect data to devise plans to better manage energy spend and reduce risk in a volatile market.
This technology can also observe how and when companies consume energy and support their trading decisions. For example, companies who both consume and produce energy – known as prosumers – can receive guidance to make optimal decisions on when to sell excess energy from their renewable sources.
Here’s how AI is already helping
At Schneider Electric, we’ve focused on sustainability and digital innovation for many years – and earlier this year, the media and research company Corporate Knights named us the world’s most sustainable corporation.
Our solutions already use AI to optimize operations, helping our customers to achieve energy transparency and to consume less energy.
What does this look like in practice? Take the distribution center of the retailer Lidl in Finland. Here, EcoStruxure Building Operation software “teaches” the building management system to predict and optimize energy use. The system works in tandem with EcoStruxure Microgrid Advisor so that energy is produced, consumed or stored exactly where it needs to be, saving 70% in energy costs. During certain times of year, it can even go beyond net-zero by distributing excess energy to 500 homes nearby.
Optimizing energy costs
Another example: The South Australian Produce Market struggled with volatile tariff rates along with negative pricing on certain days. EcoStruxure Microgrid Advisor helps manage that volatility to optimize operations based on the price signals.
In Schneider Electric Exchange, our open ecosystem for IoT energy management and automation solutions, efficiency-focused analytics and software are becoming a key area of partnerships. Companies like Predictive Layer are a great example of this approach. This Swiss company offers its AI Forecasting platform and publishes its own external data sets on Exchange, helping eliminate the uncertainty of energy demand forecasting and create savings of up to 25% on energy bills.
Our last best chance to tackle climate change
AI is not a “silver-bullet” that can single-handedly green a business overnight. But it’s already opening up far-reaching possibilities for companies. When implemented in tandem with – and in support of – a company’s overall sustainability goals, it can help accelerate the journey to a more climate-friendly future. And that means it can help address the greatest challenge facing humanity today.
Read this free white paper to discover how to improve energy efficiency and lower carbon footprint with digital solutions and collaboration.