Temperatures are soaring across the globe. This summer, dangerous heat waves hit parts of the U.S. and the U.K., and the trend is only expected to worsen as climate change takes its toll. In turn, the power grid is facing heightened demand with air conditioners and fans cranked to the max as temperatures tick up.
The overloading of the grid is particularly harmful in places that have never seen such high temperatures, like London, where temperatures reached an unprecedented 104.5 °F in July.
Aging electricity grids, which were not designed to handle the energy demands of extreme heat, can fail, leading to blackouts and leaving entire cities without power. To compound this issue, power is typically only generated in certain parts of a region, so when every home, business, and factory needs air conditioning, transmission lines are stretched to their capacity as they attempt to bring electricity to different areas.
Although there’s no simple solution to the repercussions that unpredictable weather has on the grid, artificial intelligence (AI) can play a key role in preventing power outages and sustaining a more resilient grid. Solutions such as microgrids and battery storage units can work to “transfer” available energy to satisfy demands that exceed available supply, sometimes in isolated areas, but they use massive amounts of computing power to function properly and are not a permanent solution.
By helping providers forecast energy demand and supply, AI technology can become a critical element of power operations and ensure that adequate supply is available at the right location on the grid at the right time.
The Power of Prediction
Preparation is key to success in any field but makes all the difference in the energy industry. To avoid grid failures, power plant managers can take advantage of AI platforms with the capability to predict energy demand levels days in advance. In practice, AI technology has the ability to process massive quantities of data from utilities to generate accurate assessments of when energy supply is typically higher or lower.
Hybrid AI - which combines traditional, data-driven analysis with encoded human knowledge - is particularly useful in cases where historical data may be lacking in quantity or quality. While numeric AI is considered to be a “blackbox” where decisions may not be easily explained, hybrid AI provides an audit trail of its reasoning for every decision.
It not only provides information that is key to decision-making, but offers it in a manner that allows human operators to trust what the AI tells them.
Forecasting operations over a time horizon is an essential element of power plant operations, so enhanced visibility into future energy production needs can simplify important decisions such as when to perform maintenance, enact upgrades, schedule human operators, and charge or drain batteries. This type of decision-making is based on a variety of factors, including cost, reserves, redundancy, and availability. AI-generated intelligent time horizon analyses give facility managers the necessary tools to make confident decisions in their planning
Apart from predictions around energy supply, AI can also analyze data to accurately predict energy consumption levels. By forecasting when power will be available and consumed, operators have a 360-degree view of what will be required of the grid at some time horizon. They can plan operations for the forecasted demand and produce the exact amount of energy needed, which prevents stress and helps the grid run as smoothly as possible. Operators can also prepare for shortfalls in production and have reserve power on hand in case of emergency. In doing so, facility managers can help the grid maintain resiliency and prevent future power outages.
AI: A Solution for Climate Change?
AI is undoubtedly useful to the smooth operation of the energy sector, but it can also facilitate the integration of renewable energy into the current system. In fact, by using historical data to predict weather conditions and future patterns, AI can provide insight into the availability of renewable energy sources like solar and wind.
Renewable energy sources, like solar and wind, have zero fuel cost but provide intermittent supply. In addition, there is often insufficient renewable power generation to satisfy the demand. Consequently, it is necessary to have a blend of renewables and conventional power generation to satisfy the demand over a normal 24-hour day. AI can be used to predict renewable generation throughout a typical day and formulate a plan for the optimal blend of renewables and conventional power generation.
For example, a power plant in Arizona can use AI to comb through data points on wind patterns in the state over the past few decades and condense the information into actionable insights for plant managers. Knowing there will likely be more wind in July and August gives managers the ability to wean the grid off traditional power sources leading up to those months and employ more energy from wind turbines. With an increase in information on when renewable energy will be available, the energy industry can come to rely on solar and wind power unlike ever before.
Reducing dependency on fossil fuels and other power sources that drive significant carbon emissions can impact the future of climate change, helping to curb the development of extreme weather patterns that might damage the grid and leave thousands without power. As the industry adopts AI solutions for these purposes, AI will soon learn the complexity of entire power systems and gain additional capabilities. AI solutions that take operational constraints into consideration, as well as predicted supply and demand, will soon be available as the industry transforms and improves grid reliability while taking full advantage of renewable power.
Stepping into the Future
Data analysis is where AI shines — having a platform sort through millions of data points transforms the way organizations interact with the data they collect. Artificial intelligence is unearthing the inherent value of data in the energy sector by examining figures on the state of the power network, potential load demands, past weather conditions, and likely fault points.
Although the future of climate change may appear bleak, AI platforms can revolutionize grid management with intelligent time horizon analyses and accurate energy consumption predictions, which will play crucial roles in increasing grid resiliency as scorching temperatures become more frequent. While AI can improve the resiliency of the grid by improving the planning and scheduling of the energy flow and stave off the effects of climate change, it can also change the face of the energy industry by helping power plants successfully maximize the amount of solar and wind power into their operations. Technology has the power to change the planet for the better and solve some of the world’s most pressing issues, and AI will play a critical part in this transformation.