Blog

September 12, 2022
AI, Data Science and Machine Learning

How Artificial Intelligence Is Transforming The Future Of Renewable Energy

As the world’s power demand continues to soar, the energy sector is staring at a unique challenge. In addition to meeting increasing global demand, it must achieve the milestones that’ll help us achieve a future of net-zero emission. According to November 2021 data, 193 countries of the United Nations Framework Convention on Climate Change (UNFCCC) are parties to the Paris Agreement.

Renewable energy is the only sustainable solution to meet our energy demands while reducing emissions. However, there are multifold challenges in adopting it, which brings us to the topic of this post. Artificial Intelligence has the potential to address some of the key renewable energy challenges to pave the way for an emission-neutral future. AI based prediction models, such as IBM’s program for the US Department of Energy’s SunShot Initiative, is a self-learning model that improves its accuracy with time, as it has access to larger datasets.

Generation forecasting

Sun, wind, and water are the three major renewable energy sources to transition away from fossil fuels. These are available abundantly and relatively simple to harness. However, there is an element of unpredictability associated with each of them. These are dependent on weather, which is beyond our control. Adopting Artificial Intelligence in energy management can help read historical data and current weather parameters to forecast future generation. During high availability periods, operators can supply the entire customer base through renewables. When there is insufficient availability to meet expected demand, they can shift a part of the load to fossil based generation to maintain steady supply.

Demand forecasting

Power distribution companies use historical demand trends to predict expected demand. Despite being helpful, this model is prone to errors because it does not take current data (weather, satellite imagery, wind speed, solar intensity, sensors, etc.) into account. Given the unpredictability of weather, sunlight availability, and wind speed, it is crucial to blend past data with present parameters before predicting expected demand. AI can process large amounts of complex data and develop more accurate algorithms to forecast accurate demand trends for the next few hours.

Grid management

Power grids are the backbone of the energy infrastructure. Artificial Intelligence algorithms can leverage large datasets to learn about the load patterns and ensure optimal utilization. Grids can adapt themselves to generation and load demand forecasts to provide enhanced reliability while keeping the costs low. As governments incentivize solar adoption for domestic and commercial consumers, grids are becoming bi-directional. AI can enable different components of the power system to talk to each other and prevent congestion.

Infrastructure maintenance

Power grids are a complex mesh of electrical components and malfunctioning is only a matter of time. Sudden breakdowns are time-consuming and the resulting disruption causes loss to the economy. AI enabled systems can provide real-time data on the overall health of the network and predict which portions of the grid are most likely to trip. Operators can use this data to carry out preventive maintenance during times of low demand. Customers can be alerted in advance to ensure there is minimal disruption.

Automation driven operational excellence

Accurate demand forecast, flexible power generation, efficient power transmission through a healthy grid, and distribution are some of the key moving parts of a power system. It is a complex network that requires fast and accurate decision-making. Modern computers are better than humans at ingesting large quantities of data and making rule-based decisions. The self-learning capabilities of Artificial Intelligence make computers far more efficient than operators when it comes to monitoring grid health and maintaining a reliable power infrastructure. A power grid performing at its efficient best is a win-win situation for all stakeholders.

Integrating Artificial Intelligence into the renewable energy sector has the potential to solve a multitude of existing problems plaguing the industry. However, it is easier said than done. You need a trusted partner to ensure a successful transition.

AI Superior’s Artificial Intelligence consulting services offer tailored solutions to assess your needs and formulate a suitable change management strategy. We understand that each problem is unique and the complexity of the renewable energy sector demands customized AI solutions. Whether you are yet to get started on your digital journey or are midway through it, we can help you take the next step towards operational excellence. For companies getting started on the digitalization path, we offer customized data strategy to collect and organize your data to have it stored securely, cleaned up and analysis-ready. We then help you optimize existing processes by using the data you already had but didn’t know how to use effectively. Finally, we take you through the digital maturity journey where AI, advanced neural networks, and simulation techniques will be implemented to drive profits.

Contact us for more information

Having Any Query?

Recent

How Artificial Intelligence Is Transforming The Future Of Renewable Energy

AI, Data Science and Machine Learning

The Transformative Potential of AI in Logistics

AI, Data Science and Machine Learning
Group 66