Laurent - stock.adobe.com
After some reluctance, AI is now providing solutions to some of the energy industry's bigger challenges. This includes increasing access and availability to energy sources, helping improve storage and usage of energy resources, securing and safeguarding those resources, and further reducing our reliance on fossil fuels.
Until recently, the adoption of AI in the energy sector had been somewhat slow, despite having an immense amount of data that could be utilized to help them streamline, automate and develop cost-effective and nature-friendlier energy solutions. Now that AI has proven its value in many other industries, however, the energy sector is seeing rapid adoption to address a range of challenges and opportunities in the industry.
The AI-enabled smart grid
In order to help with an array of challenges facing the digitization of the energy industry, companies, governments and regulatory agencies are looking at ways to make our energy consumption more efficient. One of the key sustainable and reliable solutions is the introduction of the smart grid, which uses a variety of operation and energy measures including smart meters, smart appliances, renewable energy resources and energy efficient resources to provide more data for energy operators, powering better decision-making and resource usage.
The vast amount of data captured from operations, whether that be asset performance data, customer data, advanced metering data or geographic information, only continues to grow. Smart grids continuously collect and synthesize huge amounts of data from millions of smart sensors to make timely decisions on how best to allocate energy resources.
AI in the energy sector is helping to empower the smart power grid, providing more effective and more profitable power trading and better regulation of power consumption. AI provides tremendous value by speeding up the processing, streaming, analyzing and interpreting of data that would otherwise not be possible with humans alone. The AI aspect of these smart grids enables them to learn from past usage, monitor current usage and use predictive analytics to help predict future consumption and avoid potential catastrophes.
AI systems are being increasingly used to facilitate allocation of production between a variety of energy sources including renewable and non-renewable energy resources. AI is also helping to monitor and optimize for energy availability and production costs, as well as looking at environmental factors that may also impact consumption and production. The UK's power and pipeline grid operator, National Grid, recently ended their collaboration with Google subsidiary DeepMind to introduce AI technology to the UK grid systems. With the use of AI, the company is hoping to reduce energy consumption by 10% providing both a financial and environmental benefit.
Traditional energy companies embracing AI
In order to stay competitive, traditional energy companies are increasingly investing in AI to broaden and deepen their technology portfolios to reduce their reliance on increasingly scarce energy resources. ExxonMobil and Chevron recently joined the Oil and Gas Climate Initiative (OGCI), a consortium of major global companies that have committed $1 billion to invest in innovative technologies to respond to climate change, per an OGCI report from 2018. Additionally, Shell recently announced that it intends to double its investment in renewables, including investments in solar power and electric automobile technology.
Other companies have embraced AI in the energy sector to help with areas such as tracking consumer energy usage and enabling the consumer to have a more tailored and personal energy consumption experience. Energy companies are increasingly using AI to enable autonomous grid operations capabilities or developing AI-enabled robotics that can maintain operations while enduring difficult living conditions or avoid malfunction and catastrophes. The UK's Grid Edge uses AI to provide solutions to optimize energy usage according to the consumer's own behavior patterns, thereby increasing efficiency.
Keeping up with consumers' changing preferences
Consumers are increasingly demanding renewable energy sources and want renewables included as part of their overall energy mix offered by providers. Additionally, companies, governments and organizations of all types are setting clean energy targets for themselves. In order to help them achieve these goals, traditional energy providers need to make sure they can fulfill these demands. AI systems in the energy sector are helping to manage energy usage and increase overall energy efficiency and conservation. Smarter systems play a crucial role as they can take many factors into consideration including weather forecasts to predict customers' demand for heat and power, and more accurately monitor grid network and real time consumption of oil and gas.
Additionally, consumers are increasingly investing in smart home gadgets that provide the ability to save on cost and lower usage needs by not only analyzing utility market trends but also by analyzing their own personal usage habits. In turn, this data provides the energy industry the ability to make consumer use more cost effective and personalized. Non-traditional energy companies are also entering the industry and are taking advantage of the market shift towards sustainable energy consumption. Stem, a California-based startup, uses AI to map out energy usage, allowing customers to track fluctuations in energy rates and more efficiently use storage. Siemens developed software that can autonomously operate grids, which stores data on how a grid interacts to different loads of energy and how it can adjust to increase efficiency.
In an industry with competition between fossil fuels, natural gas and renewable energy, AI is becoming prominent. The results that integrating AI will produce within the energy sector are vast, with growing interest and traction in the consumer, policy and business communities.