The energy industry is one of the most powerful and cost-efficient industries worldwide. The modern economy heavily relies on energy to run the everyday life of an individual. The energy industry requires modernization as the world massively depends on it and it is critical for every country’s economy.
Most energy companies do not realize the potential of energy production, neither do they incorporate modern technology to optimize its operations. If the industry avails of AI, the global demands for cheap, clean, and reliable energy could be met. For a start, let us see how the energy industry would be benefited from implementing AI as a vital part of it.
Digitization of data
The energy sector still heavily relies on manual labor. By implementing AI, the collection, storage, and management of data could be digitized. The energy sector does collect a vast amount of data secured from operations. These operations include asset performance data, advanced metering data, customer data, geographic information, etc. Hence, one can see that data collection is not new to the energy sector and it has a lot of data to manage.
Artificial intelligence helps to store, process, and manage data in a more cost-efficient and less time-consuming way. It implements changes in processing speed, storage costs, and analysis techniques. AI-powered data management can also help the industry develop better operational methods than the ones that are currently in use. It can be used to discover new insights that can entirely transform the way the industry works.
Artificial Intelligence has the ability to make decisions based on information and carry out actions to achieve its goals. This includes collecting said information and reacting flexibly to changes in the environment. With the help of machine learning and deep learning, AI can provide predictions on demand, system overload, and possible failures. The cost of error in the energy industry is very high and AI can be used to overrule it. AI has the potential to predict and prevent disasters such as system overloads and can warn operators about potential transformer breakdowns.
Another way for AI to help in forecasting is in the sector of renewable energy. One persistent challenge with renewable energy sources such as wind and solar power is unreliability. Power sources that depend on the weather will often fluctuate in strength. In Colorado, energy provider Xcel is implementing methods to meet this challenge. Xcel used an AI-based data mining method to access weather reports with a higher level of accuracy. Due to this, greater precautions could be taken to harness and preserve the energy generated. The AI-system in Xcel digs up a combination of data from local satellite reports, weather stations, and wind farms in the surrounding area. It then identifies patterns within these data sets and makes predictions based on them.
AI-powered predictive capabilities allow the energy industry to dispatch their resources better, prepare for a sudden demand in advance, predict any issues, and save resources whenever possible.
The energy sector is witnessing a shift towards efficient energy production and preservation methods to meet the high demand for power supply by consumers. Hence, the sector works more on decentralization and decarbonization. Another responsibility the energy sector must meet is managing the imbalance in demand and supply while preserving energy.
AI can be used to help the industry tap into undiscovered data and connect it to the decentralized energy resources. Therefore, industries can use this to optimize energy use across various sectors. When AI is used with the core energy system of any organization, it can use machine learning and deep learning algorithms to provide insights into the energy operations. It then has the capability to analyze the data and suggest a proper approach to energy management. This can help reduce unnecessary energy use, save costs, and optimize the energy consumption of the organization.
Energy storage facilitation
Storing energy efficiently can be a difficult task since the amount of power to be stored is growing continuously. Storing renewable energy is particularly tricky as the production of this energy is periodical and even chaotic at times. AI-powered storage can greatly help energy storage management and minimize power losses.
Taking California-based Stem as an example; the company uses AI to help store energy on a large scale. Pairing AI energy storage allows the automation of energy cost savings by storing electricity when it is affordable and using it later when costs are high, therefore shifting energy away from the most expensive times of the day.
The world is on the verge of a technological revolution. Many industries are adopting AI to keep up with the times and maximize what they have to offer through it. The energy sector is one that is vital to every country’s economy. It needs to enforce AI into their systems because of the heavy dependence on it. We have seen how energy companies utilize AI to cut costs, save power, prepare for changing conditions, and provide better customer service. With further development, AI can be used to meet the global demand for energy supply or even completely change the core of how the energy industry functions.
- @SolarPowerWorld: How AI is changing energy storage O&M
- @AI News: AI & Machine Learning: The Next Transformation for Oil & Gas
- @AI News: Deep Learning getting simplified
- @CNBC: A Californian business is using A.I. to change the way we think about energy storage