How Artificial Intelligence Can Improve Electricity Savings

 

The world's electricity consumption has continuously grown over the past half a century, reaching approximately 25,300 terawatt-hours in 2021. Between 1980 and 2021, electricity consumption more than tripled, while the global population increased by roughly 75 percent.

It would not be wrong to say that growth in industrialization and access to electricity across the world has further increased the demand for electricity. In fact, the industrial sector is the second largest consumer of energy in any country, with energy consumption accounting for a third of manufacturing’s operational costs. About 70% of all produced electricity powers factories and buildings, but 60% of that energy is wasted. This wasted energy represents billions of dollars spent on generated energy that we would not have consumed.

Multiple contributing factors such as the existence of electricity-intensive industries, household sizes, living situations, equipment and efficiency standards, and access to alternative heating fuels determine the amount of electricity the average person requires in each country. The ever-increasing needs of electricity, forecasting, coordination and supply management indicate that new solutions are needed to save electricity. That is what you can achieve with Artificial Intelligence.

Artificial Intelligence plays an important role in energy saving, it not only can control operations, but can also perform tasks more efficiently and much faster than humans. Now the energy sector is using AI to increase energy efficiency by reducing consumption, improving energy storage and grid stability, making predictions about energy consumption, to have more accuracy to find oil & gas and many other applications.

As AI gradually becomes mature, it is also being applied in the energy management field. Today many Internet of Things (IoT) companies are using AI to help businesses reduce energy consumption and expenses.

Global electricity consumption,

The traditional way to save energy has always been to invest in new equipment, new machines or better infrastructure. Nevertheless, in 2019, the world's total final electricity consumption reached 22,848 TWh, up 1.7% from 2018. In 2019, the OECD's total final electricity consumption was 9,672 TWh, down 1.1% from 2018, while non-OECD countries had 13 final electricity consumption. 176 TWh, an increase of 3.8% from 2018.

Global electricity demand grew by 389 TWh (+3%), in line with average historical demand growth for 2010-2021. Total global demand reached 13,393 TWh in the first half of 2022, up from 13,004 TWh in the same period last year.

How AI plays an important role in optimizing energy savings,

Today artificial intelligence becomes more and more important in the energy industry; it has great potential for the future design of the energy system. Typical areas of application are electricity trading, smart grids, or the sector coupling of electricity, heat and transport.

Artificial intelligence (AI) has the potential to cut energy waste, lower costs, and accelerate the use of clean renewable energy sources in power grids globally, along with improving the operation, maintenance, control, planning, and plan execution of power systems. AI powers electrical grids that allow two-way communication between utilities and consumers.

Artificial intelligence monitors, collects information, controls, evaluates and manages energy consumption in buildings and factories. AI controls energy usage and reduces it during peak hours, identifies and signals problems, and detects equipment failures before they occur.

AI has the ability to compress and analyze large sets of data that can help monitor and interpret the data produced by energy industries to optimize energy consumption.

Prerequisites for an increased use of AI in the energy system are the digitalization of the energy sector and a correspondingly large set of data that is evaluable. AI helps make the energy industry more efficient and secure by analyzing and evaluating the data volumes.

Energy consumption solutions using artificial intelligence (AI) aim to make the manufacturing process more efficient by forecasting energy demand, and in particular, by anticipating machinery usage and predicting malfunction. Energy management software can shift the focus of managers from the daily routine of mundane tasks and monitoring workflow to strategic development.

AI is thus closely tied to renewable, clean as well as affordable energy that is necessary for development. AI is also employed to reduce the environmental impacts from thermal power plants, improve their performance and thus play a more efficient role in supplying power to the grid.

Energy consumption machine learning (ML) solutions can reduce energy bills by optimizing complex manufacturing processes in any industry.

On the other hand, AI itself consumes a lot of power. The processing of large amounts of data consumes a lot of electricity. When using AI for energy system transformation, it is crucial to analyze as well how to design the data centers themselves to be energy-efficient and as climate-neutral as possible. Possible solutions to this dilemma include the physical proximity of data centers and renewable energy generation plants, the postponement of power-intensive computing operations to times when a lot of power is available, more energy-efficient IT hardware, or programming that requires as little computing power as possible.

Artificial intelligence routinely produces startling achievements, as computers learn to recognize images, converse, beat humans at sophisticated games, and drive vehicles. But all those advances require staggering amounts of computing power and electricity to devise and train algorithms. And as the damage caused by climate change becomes more apparent, AI experts are increasingly troubled by those energy demands.

In the energy industry, AI offers a multitude of suitable application scenarios that will support the energy transition and a climate-friendly energy system. It will be crucial, however, to protect user data and make the use of AI transparent and comprehensible.