Artificial Intelligence (AI) and the Energy Sector Revolution

Artificial Intelligence (AI) and the Energy Sector Revolution

While artificial intelligence is about to make a huge difference in our lives, work and play, few people understand what the technology can do beyond Amazon's Alexa or Apple's Siri. These are virtual assistants, or 'weak AI' technologies, and are among the most common examples of artificial intelligence applications. In the energy sector, however, sophisticated machine learning driven by data is paving the way for 'strong AI' to improve energy efficiency, prediction, electricity trading, and user accessibility.

Artificial intelligence: electricity trading

Electricity is a commodity that can be bought, sold and traded on the open market. In order for the market to operate efficiently, electricity sellers, buyers, and brokers must continuously analyze vast amounts of data, from forecasting weather to balancing supply and demand on the grid. Those who understand the data best have a competitive advantage in the marketplace. In '18, IBM's Deep Mind started applying machine learning algorithms to Google's wind farm with a capacity of 700 GW (enough to power a medium-sized city) located in the Midwest. Using a neural network fed with weather forecasts and historical wind turbine data, we were able to predict wind power 36 hours in advance. In less than a year, Deep Mind's machine learning algorithms improved the value of wind energy by about 20%.

Artificial intelligence: intelligent power consumption

About half of U.S. electricity consumers use electric smart meters. Smart meters enable consumers to manage their own energy use by providing data about an individual's energy consumption. Although new AI-powered smart meters and smart home solutions are not yet widespread, they have the potential to improve the efficiency of final energy consumption. These energy monitoring devices are linked with other home appliances to help consumers save money on energy by reducing energy wastage. Control air conditioning use, charge electric vehicles during times when electricity prices are low, control lighting and manage appliances.

With the ability to adapt and respond to energy usage patterns and electricity prices, these devices can deliver huge energy savings as the number of users increases. The widespread use of intelligent power-consuming devices can contribute to creating a green and reliable power grid for all.

Artificial intelligence: intelligent energy storage

Artificial intelligence can enhance existing energy storage technologies by making it easier to integrate discrete technologies such as renewable power microgrids, utility-scale battery storage, and pumped-water power generation. The role of energy storage in modern power grids is growing rapidly as intermittent power sources (wind, solar, etc.) proliferate. As technology advances and costs reduce, intelligent energy storage will play a greater role in the ancillary services of the grid, helping grid operators balance supply and demand and supporting transmission from power plants to consumers.

When there is a gap between supply and demand, artificial intelligence can help distribute power more efficiently. This saves power that could have been wasted so that it can be used when needed later. Integrating multiple individual energy storage systems not only maximizes cost savings, but also enhances safety and security by improving frequency and voltage control by intermittent power generation. Younicos, an energy storage system company located in Berlin, Germany, has been a global market leader in the development and distribution of these integrated systems since 2005.

Artificial intelligence: robot

One notable application of AI technology in the power sector is creating autonomous robots that will replace humans in hazardous situations. These autonomous, unmanned machines can patrol high-voltage power lines on land or search for valuable resources on the seabed. This machine allows recording and reporting of future energy extraction locations without risk of personal injury.

ExxonMobil's two-way collaboration with MIT through the MIT Energy Initiative is one project to develop autonomous robots that can independently perform these complex tasks. MIT Professor Brian Williams and his team are developing a self-learning robot that mimics NASA's Mars rover, Curiosity, to explore and utilize the seabed. Earth scientist Lori Summa, a former consultant for ExxonMobil's MIT Underwater Robot Project, said innovations "going beyond conventional energy research to solve the challenges of the future" are essential.

Artificial intelligence: the future of energy

As we face the unprecedented COVID-19 pandemic, the economic improvement of the global energy system is being emphasized once again. To this end, market participants are leveraging machine learning to improve forecasting, increase transparency in electricity transactions, integrate renewable energy sources, manage smart grids and energy storage, and bring unmanned drones to life.

The convergence of strong AI and the energy sector will have a dramatic and far-reaching impact on energy consumers worldwide. This reminds me of Bill Gates' graduation speech in '17.

“If I was a graduate again today and was looking for an opportunity to make a big difference in the world, I would consider these fields. First, artificial intelligence (AI). We are just beginning to harness the potential of artificial intelligence to make human life more productive and creative. Second, energy. Because creating clean, affordable and reliable energy is essential to combat poverty and climate change. ”