AI technology to power energy companies to boost efficiency

Companies across the world see the need to reduce energy consumption and emission to attain their sustainability goals. One of the ways technology can help them achieve this is by incorporating artificial intelligence (AI) to energy providers.
Energy to invest in AICIOs are realizing that AI can not only predict machine failures but can also identify voltage failures. Investments in AI technology benefit the energy sector with agnostic solutions, such as bots, which can be used to service customers.

According to a research by Infosys, 48 percent of the respondents from energy, oil, gas, and utility industries consider AI to be a fundamental driving force behind their organization’s success. This is mainly because AI allows companies to improve their overall customer and work experience. Their self-healing grids run by AI ensure minimal use of resources as well as predict any form of energy shortage.

California-based Stem recently developed Athena, which uses artificial intelligence to identify energy usage. In Japan, Stem and partner Mitsui have developed a system using the assistance of Athena to produce batteries that will reduce energy consumption of the nation. This is needed for Japan because it has over 45,000 MW of solar capacity installed now and may increase to 64,000 MW by 2020.

In California, this June a heat wave caused a sudden rise of more than 100 degrees in temperature. This gave Stem’s Athena to prove its value by stabilizing the power grid. This also included Athena’s management across battery and inverter technologies to deliver energy and help stabilize the grid. That month, Stem was engaged in 60 customer energy storage facilities and created seven virtual power plants.

Siemens also released a software package known as active network management (ANM). ANM autonomously adjusts grids responsively and allows it to work with different loads of energy to increase efficiency.

Further, Siemens is using AI to improve the operation of gas turbines. Their systems that are run by AI are able to learn data produced by the operating systems and can reduce the emission of toxic gases. They also use artificial intelligence to improve the reliability and machine learning power of grids.

Drift, a start-up that has nearly 3,000 power producers, uses AI technology and machine learning to determine how much energy will be required the next day.

Their aim is to remove the problems surrounding the current wholesale power market, and provide energy at cheaper rates to consumers. Drift is initially rolling out its service in New York City and plans to expand to other parts of the country this year.

On 9 April 2018, Bidgely was recognized for pioneering AI disaggregation solutions for utilities with a 2018 New Energy Pioneer Award from Bloomberg New Energy Finance.

The company was awarded because of its response to changes and disruption in the energy system by incorporating machine learning and data analytics to its utility meter data. They combined the power of SaaS-based analytics with consumer-friendly web and mobile applications, to provide personalized data. This helped the company to gain insight on data relevant to their consumers.

In Colorado, energy provider Xcel is implementing AI to address their energy challenges. They work with AI systems that collect a combination of data from local satellite reports, weather stations and wind farms. These algorithms produced after the collection of data helps the company to produce the actual required energy, saving time and power.

GE Power acquired Boston-based machine-learning and data analytics start-up NeuCo. The companies together began working to improve its current system by upgrading to a new one run by AI. This began to improve the efficiency of its coal powered plants and also reduced the level of greenhouse gas emission.

AI is helping energy companies reduce their negative environmental and social impact. AI software helps to improve efficiency and reduce emission and allows companies to analyze large amounts of data.

With the ability of machine learning to also detect faults it helps in the overall influence of companies to enhance sustainable development, thus not only saving money and time, but it can also save lives.

Yadawanka Pala

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