By enhancing various industries and transforming the way we live and work, Artificial Intelligence (AI) is set to play a key role in the future of our lives. Through data analysis and predictive monitoring, AI allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. In this article, we take a deep dive into how AI technologies will support a sustainable future for the energy transition into renewable sources.
Key takeaways:
- Artificial Intelligence (AI) analyzes data to optimize energy efficiency, improve energy supply and demand predictions and increase grid flexibility.
- In the transition to renewable energy sources, the analytical and predictive capacities of AI will be crucial to reducing greenhouse gas emissions.
- Three of the most promising ways in which AI will accelerate the energy transition are smart grids, optimized electricity consumption and electric mobility.
Artificial Intelligence (AI) stands as one of the most significant technological advancements of the 21st century, holding the potential to reshape our society at its core. This transformative power comes at a crucial time, considering the alarming rise in global energy-related CO2 emissions, which reached a record high of 36.3 billion tons in 2021, according to the International Energy Agency (IEA).
The urgency to reverse this alarming trend has become paramount. To avert an irreversible climate crisis, we must embark on a journey of decarbonization and transition towards renewable energy sources, necessitating a fundamental shift in our energy production and consumption practices.
Enter AI—a game-changing force that can contribute immensely to this essential energy transition. Research indicates that 93% of the environmental goals (outlined in the United Nations Sustainable Development Goals) can be achieved with the aid of AI-powered solutions. Furthermore, industries have the potential to reduce their Economic Emissions Intensity (EEI) by up to 45% by 2030 through the adoption of AI-enabled use cases, depending on their specific sector.
As we strive towards a carbon-free future, AI emerges as a key enabler that can accelerate the much-needed energy transition.
AI and energy transition: Embracing a data-driven world
Currently, we find ourselves inundated with an overwhelming amount of data that surpasses the capacity for human analysis. The proliferation of the Internet of Things (IoT) further exacerbates this situation, as the International Data Corporation (IDC) predicting a staggering 175 zettabytes of global data by 2025. Attempting to grasp the magnitude of these numbers would seem rather futile – it would take an individual approximately 1.8 billion years to download such data at the present processing speed.
This is precisely where AI technologies come into play. With their ability to rapidly adapt and their diverse range of applications, even marginal gains in efficiency, storage capacity, or flexibility can yield significant savings and CO2 reductions. Leveraging AI models enables more precise forecasts, improved predictions of energy supply and demand, enhanced grid flexibility, as well as optimized maintenance and operation of energy assets.
In alignment with these goals, Enel has recently inaugurated the AI & Robotics Lab in Tel Aviv, Israel. This state-of-the-art facility, the latest addition to our global innovation network, welcomes startups and entrepreneurs to explore AI and robotics solutions in the fields of renewables and power grids. By driving innovations in AI, we can enhance energy efficiency, minimize waste, and foster environmental sustainability.
In conclusion, as we confront the imperative of sustainable energy practices, the integration of AI becomes increasingly vital. Harnessing the power of AI to revolutionize our energy landscape holds the promise of a cleaner and more sustainable future. By embracing this transformative technology, we can drive unparalleled advancements towards achieving our climate goals.
Let’s take a look at three ways AI is helping drive the future of sustainable energy
- Smart grids
Since the inception of electricity grids in 1882, significant progress has been made. The conventional grid, comprising transmission lines, substations, and transformers, has paved the way for a new era known as “smart grids.”
Smart grids are integrated networks that incorporate sensors, data analytics tools, energy storage systems, and energy management platforms, among other technologies. These advanced systems collect data from every device connected to the grid, enabling AI to analyze and optimize energy efficiency for consumers.
The application of AI in energy forecasting plays a crucial role in grid balancing, congestion reduction, and the optimization of renewable energy sources like solar and wind. Real-time monitoring allows companies to predict and curtail energy consumption during peak hours, resulting in cost savings for consumers and a greener planet for all.
Enel, as part of its Net-Zero strategy to eliminate CO2 emissions by 2040, adopts the Grid Futurability® approach. This approach combines robust infrastructure with cutting-edge technological solutions to create resilient, participatory, and sustainable digital electricity grids. By 2024, Enel aims to serve 81 million grid customers, with 63% of them benefiting from digitalization facilitated by Gridspertise’s advanced smart meter technology.
2. Optimized electricity consumption
According to the World Economic Forum, buildings account for 39% of global greenhouse gas emissions, primarily driven by operational energy usage. Hence, organizations addressing energy waste is a crucial step towards achieving a Net-Zero future. AI-powered smart buildings and homes offer solutions to these market inefficiencies.
AI can be employed in residential, commercial, and industrial settings to learn patterns of human behavior and equipment usage, thereby reducing electricity consumption. By analyzing sensor data and utilizing computer vision, AI algorithms can identify occupancy levels and gain insights into a building’s thermal behaviors. Implementing smart solutions in existing buildings could potentially reduce EU energy consumption by 5-6% and decrease CO2 emissions by 5%. Notably, Google’s DeepMind AI achieved a 40% reduction in cooling energy at one of their data centers, contributing to a 15% overall decrease in power usage.
The prevalence of smart devices such as Amazon’s Alexa and Google Nest is growing, with an estimated 478.2 million smart homes worldwide expected by 2025. These Internet of Things (IoT) devices empower consumers to monitor their energy consumption and adjust habits to minimize unnecessary electricity use. Moreover, smart homes facilitate the integration of renewable energy sources by automatically optimizing appliance usage based on factors such as electricity prices and the availability of solar power.
3. Electric mobility
Road transportation emissions constituted 71% of the EU’s total greenhouse gas emissions in 2019. Transitioning to electric mobility (e-Mobility), powered by clean and renewable electricity, is essential to achieve decarbonization goals. Optimistically, however, the electric vehicle market is poised for rapid growth, with projections suggesting electric car sales could reach 31.1 million units by 2030, accounting for 32% of the market share.
AI plays a crucial role in the e-Mobility sector as it offers diverse applications. For instance, Enel collaborated with the Israeli B2B startup Make My Day to develop a smart algorithm that assists electric vehicle drivers in planning routes based on available charging stations. Enel X is also partnering with the global AI software platform Optibus to optimize and manage electric vehicle fleets in public transportation, contributing to the electrification and decarbonization of cities. These AI-driven advancements will propel the e-Mobility sector and accelerate the transition to a more sustainable energy future.
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Source: Openinnovability.enel.com (2023).
