7 Ways Machine Learning Will Transform The Energy Industry

The energy sector is indispensable for the modern economy and so is AI. The confluence of the two fields can bring about many positive changes that will revolutionize the economy. As with all industries, the energy sector is now striving to incorporate AI and machine learning into its systems for higher performance and improved reliability.

Machine learning in renewable energy can facilitate the industry in orchestrating radical changes by leveraging the power of cutting-edge technology. Artificial intelligence in renewable energy systems will usher in a paradigm shift in the industry.

Here is how artificial intelligence can revolutionize the energy sector.

Table of Contents

1. Efficient Data Processing

Several industries in the entire world have made the shift to artificial intelligence but so far the energy sector has been somewhat slow in this aspect. AI can help the energy sector with data digitization, management, storage and collection, all of which can help to augment operational efficiency.

With so much potential for improvement, it is surprising then that the energy sector has still not utilized artificial intelligence, like other industries have. To increase its competitiveness and to usher in a new age of rapid modernization, the energy sector must make the transition from manual work to cutting-edge information systems.

2. Streamlined Data Management

AI will prove to be a game changer for the energy sector since the industry has to manage a lot of data and AI thrives on vast data quantities. Managing, processing and storing data can become much more efficient in terms of resources and manpower. The energy sector will be better poised to develop more streamlined operational methods for greater stability even during uncertain economic times.

AI can help energy companies to gain insights into trends and developments that can transform their fortunes.

3. Improved Forecasting

The global demand for energy is increasing at a phenomenal rate. However, it is necessary to accurately predict this rising demand for greater strategic planning and expansion. Thus, AI-powered data analytics will yield predictive insights that will help executives to formulate the best possible strategic decisions.

4. Better Predictive Analytics

AI can help to rapidly enhance predictive analytics that will, in turn, empower companies to provide better customer service, make them more resilient and adaptable to changing conditions, save power and cut costs. The energy sector can take forecasts to the next level with deep learning and machine learning. Intelligent systems can help the industry to make more accurate predictions in demand trends, system overload and even potential failure points. Being able to detect problems in energy production is paramount since errors can prove to be extremely detrimental both for the company as well as the economy.

Major players in the energy industry have already begun to make room for AI and machine learning. The global energy player GE Power, which produces around 30% of the world’s electric power, is developing a workflow that will benefit from AI systems. Besides energy production, the company will also be able to greatly enhance business processes through machine learning and AI.

Anodot is an example of how AI platforms can help the energy sector to step up its performance. The artificial intelligence startup supplies forecasts and real-time data that can help energy companies to detect problems and prepare for them in advance.

5. Stronger Resource Management

AI systems in renewable energy can help with improved resource management. AI-powered platforms provide advanced predictive analytics due to which energy companies can manage and process their resources better in anticipation of future demand trends. Thus, they are better poised to save on their resources and predict several issues related to resources before they can arise. This will also lead to improved customer experience since power companies will be able to provide more personalized services and reduce utility bills.

6. Facilitation Of Energy Storage

Efficient energy storage poses several technological challenges and is yet essential. Companies will need additional assets and better management systems to augment their energy storage capabilities. Through artificial intelligence and machine learning, companies can optimize energy storage.

Energy storage is even more important for renewable energy since its production can be quite unpredictable and sporadic. Integrating renewable energy sources with AI-powered energy storage solutions will make renewable energy more feasible and reliable in the future. In fact, AI and intelligent platforms are now considered essential for improving the competitiveness of renewable energy sources and decreasing the reliance on fossil fuels. AI systems will also help renewable energy and the electric grid to minimize losses and balance load in a better way.

7. Failure Prediction

AI systems will have access to IoT powered sensors and devices that are feeding them with real-time data. This will give them a powerful capability to predict impending failure, prepare for it and even act quickly to avert it.

Poor electricity transmission and system faults can create problems in more ways than what most people think possible. For instance, faulty electricity lines were responsible for instigating forest fires in California during 2018. Intelligent systems can predict such scenarios even before they have the chance of developing into full-fledged, thus greatly mitigating risk. If AI systems were in force, then the lethal California wildfires of 2018 may never have transpired. AI systems can present timely warnings to operators of transformer overloads, which can lead to breakdowns and expensive electricity outages. Intelligent systems can keep operators updated of areas where there is the risk of overload so that they can take advance to prevent such an occurrence.

Failure prediction and prevention is an extremely important area for the energy sector since electricity outages entail tremendous costs to businesses and the economy. In fact, power blackouts can bring entire economies to a standstill. AI systems can minimize such occurrences by keeping energy companies updated about the state of their infrastructure and pinpoint areas that are in danger of developing faults and failures.