Advantages and Disadvantages of Artificial Intelligence in Clean Energy Sector 0

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Artificial intelligence is revolutionizing the energy sector the same way it is doing for other industries like health, manufacturing, and more.

Are you ready to learn how technology is helping shape the energy sector?

Read on to learn how Artificial Intelligence is taking the energy sector by storm as well as the challenges that come with it.

According to Pro Essay Writing, a professional writing services provider, the energy sector has propelled the modern economy hugely. Unfortunately, most of the key players in the energy sector aren’t aware of their energy production potential. 

Perhaps due to lack of knowledge or manpower, most energy companies aren’t taking advantage of the latest technologies to enhance their operations.

Artificial Intelligence is undoubtedly transforming the energy industry. Apart from enhancing operations, the technology is also making the energy sector safer.

In this article, we’re going to discuss the advantages and disadvantages of artificial intelligence in clean.

But before that, let’s understand a few things. 

What is Artificial Intelligence?

Artificial Intelligence has grown popular over the past few years- and many sectors have felt its impact both negatively and positively.

Still, it’s not easy to get the exact definition of the term Artificial Intelligence.

That’s why it’s often confused with machine learning and other technologies.

At its core, Artificial Intelligence entails making and implementing independent decisions based on data concerning set goals.

That’s how Artificial Intelligence differs from natural intelligence attributed to humans and animals.

What Is clean energy?

What does clean energy mean? Clean energy is energy generated from renewable and zero-emission sources and stored through energy efficiency measures. 

Clean energy comes from sources that can constantly be replenished such as solar energy, bioenergy, biomass, hydropower, wind energy, etc.

The objectives of renewable energy 

What’s the main goal of using clean energy?

The main objective of deploying clean energy is to mitigate climate change.

Investing in clean energy sources has both environmental and economic benefits. For instance, it helps to produce energy that emits no greenhouse gas from fossil fuels and reduces some types of air pollution.

How AI is transforming the energy industry

There is no denying that the COVID-19 pandemic is slowly coming to an end. That means that we should expect the energy consumption in industry and services to increase.

The developing world is expected to increase its energy consumption hugely thus causing rapid growth of global primary energy demand of around 0.5% annually. In fact, unconfirmed studies suggest that by 2050, the energy global primary energy demand will increase by 25%.

A report by energy giant Total SE suggests that transportation will see massive electrification thus leading to decarbonization- no doubt there will be a need for rapid growth in renewable as a source of electricity.

This is where the application of Artificial Intelligence is expected to increase by up to 50%. To facilitate the growth of 21st-century grids while replacing those laid down in the 19th to 20th century in developed nations like China, Europe, Japan, and many others.

The grid consists of enormous systems of generation facilities of solar, nuclear, hydro, or gas connected by high voltage wire systems to transformers that are then connected to sub-stations and individual buildings and households.

Big energy companies are already working around the clock to supply electricity thousands of miles away from the point of generation.

For instance, Australia is sending sunshine to Singapore through a giant cable known as Sun Cable, a 2,400-mile undersea cable that’s expected to supply solar power to Singapore from Australia.

Nevertheless, there is a challenge:

Supplying energy through an undersea cable to thousands of miles is becoming tricky and inefficient because much of it is lost during transmission and distribution.

This is where Artificial Intelligence becomes useful.

AI combined with IoT can help optimize energy distribution and storage. For instance, IoT can help with remote controlling of systems, consumption tracking, data collection, and analysis whereas AI can help with decision making about where to supply energy, which generating capacity to activate or turn off the capacity of energy to store, and many other decisions.

Systems will be fitted with smart sensors and meters to capture mountains of information and exploit tons of cloud computing capacity as AI algorithms process mountains of data to make valuable decisions. 

Companies that are leading in technological development and implementation of AI in the energy sector include IBM Corporation, Intel Corp, Cisco Systems Inc., Mitsubishi Hitachi Power Systems Ltd, Microsoft Corp, and many others.

With that in mind, let’s answer the question of…how is AI used in the energy sector?

Given its potential, Artificial Intelligence can decrease energy waste, lower cost, and help and speed up the use of clean renewable energy sources in power grids globally.

Besides, AI has the potential to enhance planning, operation, and power system monitoring.

That being said, let’s take a look at the applications of AI in the energy sector.

How AI is utilized in the energy sector 

If we were to mention the most powerful and important technologies of the 21st century; it’s no doubt that AI will take the first position.

The technology has and is already transforming industries in leaps and bounds.

Currently, Artificial Intelligence is influencing the strategies of the most influential countries worldwide.

This includes the modernization of the energy sector and many others.

Here are several uses of AI in the energy sector:

Electricity/renewable energy trading 

AI forecasting is helping to alleviate dramatic energy problems. The technology helps to improve forecasts in electricity trading.

As the energy consumption by modern machines and the global population continues to increase tremendously, AI is helping with predictive analytics.

The technology is simplifying systematic evaluation of mountains of data (historical or weather data) in power trading including. 

Through efficient predictive analysis, energy companies can reduce energy costs, save power, and provide better customer service.

Machine learning and deep learning technologies are helping improve forecasting in the energy sector.

Energy companies need to foresee changes in demand, accurately predict possible failures, and system overloads as errors in the energy industry are high.

But that not’s all. Improved forecast enhances grid stability and supply security.

AI can help facilitate and accelerate the integration of renewables.

Examples of energy companies that are taking advantage of AI to improve power trading include GE Power that generates 30% of the global electricity.

The company is incorporating AI and machine learning to improve its energy distribution chain.

Another energy company leading in AI adoption is Anodot. The company provides real-time alerts and forecasts that help companies detect issues and solve them before they get out of hand.

AI In virtual power plant

Most of the data processing and forecast is done in the Virtual Power Plant. Artificial Intelligence algorithms help to generate accurate forecasts while coordinating various systems in the Virtual Power Plant.

The technology helps to determine which plant generates or uses how much power and when- based on data from power trading stations, live-feed-in data, weather forecasts, historical data, etc.

In fact, some AI algorithms are sufficiently intelligent that they can trade electricity without human intervention through the process known as automated trading, algorithmic trading, or algo- trading.

AI is also helping with auto-monitoring and analysis of trade on the power market. This way, energy companies are able to detect and prevent deviations from the norm like abuse of market power efficiently.

Energy storage facilitation

Energy company owners know that storing energy efficiently is no easy task. This is due to the continued growth of the amount of electricity to be stored that is leading to the need for additional capacity and modern management systems.

Through Artificial Intelligence, industry players can optimize their energy storage.

It’s worth noting that storing renewable energy can be challenging since the production of this energy is periodical and even chaotic.

Combining renewable energy with AI-enable storage can enhance energy storage management hence boosting business value while reducing power losses.

Stem is an energy startup that’s aiding companies to make smart energy strategies. The startup partners with over 80 top solar energy generators in the US to help them add storage capacity.

Data digitization of the energy sector 

The energy industry is lagging behind in terms of personalized digital services. Through AI, energy companies are able to enhance data collection, storage, and management to stay at par with times.

See, the energy industry is undoubtedly the most powerful and lucrative sector. However, much of the operations are done manually.

Key actors work with mountains of data that need to be stored managed, and processed in a cost-efficient manner. This is where AI becomes useful.

Through efficient implementation and adoption of innovative technology, the energy sector can stay competitive in times of unstable economy and develop better operational methods.

Besides, AI data management can provide new insights that can transform the way the industry works.

Failure prediction and prevention

Even though energy is a powerful resource it can cause more harm when not handled properly. In 2018, California experienced deadly wildfires due to faulty transmission lines.

With Artificial Intelligence, energy actors can detect and prevent such disasters.

For instance, AI can predict system overloads and alert operators about potential transformer failures.

The blockchain-enabled solution known as Trusted Analytics Chain developed by VIA is helping companies collect and analyze their data to predict system behavior.

PreNav, on the other hand, is helping energy actors digitize their infrastructure with the help of drones, deep learning, and Lidar. Their deep learning technologies are helping energy companies in detecting damages and threats like bad insulation, missing rivets, corrosion, and more.

Global sustainability

The application of AI systems in Cleantech operations improves efficiencies that help the sector generate more using fewer resources.

For instance, agricultural organizations can apply AI systems to grow and process tons of food using less energy, fertilizer, and water.

Key actors in the mining sector can also extract more minerals and metals from the ground securely without using too much fuel and emitting less waste.

Artificial Intelligence’s obstacles in the renewable energy sector 

There are many ways AI is helping the energy sector. However, the technology isn’t without its challenges.

Here are the key challenges of AI in the Cleantech sector.

Insufficient theoretical background 

Part of the reason for the why many businesses aren’t incorporating AI in their strategies is a lack of the required knowledge.

Many energy companies lack enough technical background knowledge that could help them understand how adopting AI to their operations could benefit their companies.

Many companies are, therefore, stuck with time-proven methods and tools instead of risking adopting new technologies.

Insufficient practical expertise 

Of all the latest technologies, AI is still a baby. That’s why only a few professionals have mastered it. Even though there are experts with ample theoretical knowledge of the subject, only a few professionals are able to design powerful AI-enabled systems with real practical value to the industry. 

Besides, the energy industry is uniquely conservative.

Of course, energy actors gather and manage data. However, managing and digitizing it with innovative technologies is the main challenge. This has led to poor customization, unauthorized access, data loss, system failures, and other dangers.

This is not to mention that the cost of error in the energy industry is high but companies are yet to try new technologies.

Lack of finance

Energy companies are struggling with financial pressure. Unfortunately, adopting innovative smart technology in the energy sector isn’t cheap, even though it’s the best option.

Besides, finding a reliable software service provider, creating and customizing software, adjusting, managing, and monitoring it takes time and resources.

To reap the benefits of incorporating AI and other technologies into their strategies, energy companies and businesses need to allocate a good amount of budget and accept the risks that come with switching from their outdated to modern energy systems.

Final thoughts 

Artificial Intelligence is the driving force behind many industries worldwide, and the Cleantech sector is no exception.

From the multiple studies and trials, it’s safe to say that AI has the potential to revolutionize the sector globally.

What are your thoughts about AI and the Cleantech sector?

Share your thoughts with us in the comment section.

Aziz Nickleson is a professor of climate change and energy working in London. She is a fellow of the Cambridge Judge Business School and a college paper writer who offers assignment help to students in the UK. If you’re looking for a professional essay writer for your technology essays about solar energy then Aziz is the guy you should link up with.
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