How is AI a game changer for Renewable Energy?

“A transition to clean energy is about making an investment in the future.”- Gloria Reuben

 

There is no doubt in this, renewable energy is the biggest insurance you can do for the globe. By reducing greenhouse gas emissions and fossil intake, renewable energy not only gives the planet a long life, but also helps in making it a better place for the coming generation. 

 

The continuous and unprotected use of non-renewable resources has already caused so many troubles to the planet, from global warming to pollution, it has its contribution in everything. In such circumstances, it becomes essential to manage and organize the sources of energy in a better way. 

 

Even the governments of different countries have taken efforts in this direction. One such global effort is the Global Wind Energy Council. The advent of technologies, IoT and AI has also contributed towards building the utilization and dependency of renewable energy.

 

In this blog we will study the role that AI has played in maintaining renewable energy.

 

(Take a look at the role played by AI in utility and energy sector)

 

 

What is Renewable Energy?

 

Energy is everywhere around us. It is the ability to do work. Energy can neither be created nor be destroyed, it just changes from one form to another. On the basis of renewable energy, energy has been classified into two types, renewable energy and non-renewable energy.

 

Renewable energy is the energy that can be replenished on a human timescale. Unlike non-renewable energy it doesn’t take millions of years for formation. Also utilizing renewable energy doesn’t create hazards to the environment as caused by combusting non-renewable sources. 

 

The major examples of renewable energy include Solar energy, Wind energy and Hydro energy.

 

Benefits of AI in organizing Renewable Energy Resources

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Role of AI in renewable energy

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Day by day, renewable energy is becoming an important part of our energy. Thus, it is important to ensure efficient and stable grids for this. AI, machine learning and automation can help in mitigating risks. The ways in which AI helps in maintaining and organizing the renewable sources are as follows:

 

1. Real-time Data

 

AI and its technologies help in collection of real-time data. The gathered real-time data helps in identifying the coming risks. This data is collected by sensor technologies by tracing the wind and solar records. 

 

Interestingly, the pictures collected by sky camera and satellites are used as data. The AI algorithms then interpret these data and predict capacity levels and downtime periods. It in turn helps in maintaining stable energy grids.

 

2. Optimize the use of power grids

 

The AI interpreted data assists the operators to optimize the use of power grids by tailoring operations as per the weather conditions. Also, AI predicts accurate decisions.

 

The accurate short-term decisions help in increasing the overall efficiency and better unit commitment of the energy plant. At the same time, it improves the reliability of the resources and reduces the unwanted expenses. 

 

“Now, with AI, we can predict more accurately what renewables are likely to do, so we can control other power plants more accurately, like coal plants that take many hours to ramp up.”

 - James Kelloway

 

3. Forecasts

 

As stated in the above point, AI helps in reducing generation costs and other wastage by making accurate predictions. At the same time, these forecasts help in predicting the requirements of the customers. 

 

It helps to crack the time when energy is required most by the customers. It plays a big role in managing the storage for the same and providing demand flexibility.

 

4. Energy Storage

 

Further AI helps in solving energy storage problems. The energy storage batteries are hard to activate. But through AI it can be activated very quickly to manage high energy demand periods. AI also helps in making energy management storage decisions. 

 

Again, these decisions are maintained by the predictive nature of AI and its ability to work on real-time data.

 

5. Maintenance and Recovery

 

Another important aspect of AI is maintenance of software as well as machineries. It can immediately detect the disturbance in the equipment and system malfunctions. It helps in identifying the kind of issue and the cause behind it.

 

At the same time, AI also suggests the list of precautions to avoid any such defaults and defects further. And keeps a record of the procedure to fix it and maintain the networks.

 

6. Global Sustainability

 

AI increases the global sustainability of energy resources. It helps in improving the efficiencies of cleantech operations. These operations assist and help in generating more energy using fewer resources.

 

And this generally doesn’t happen with applications of AI in renewable energy but is the sum of all the sectors. For example, with the advent of AI in the agriculture sector, efficient crops can be grown using less fertilizers. 

 

Similarly, AI in the mining sector helps in reducing the intake of electricity. Thus, overall AI helps in reducing the consumption of energy and achieving sustainability.

 

(Suggested Read - Nucleur Energy)

 

 

Limitations of AI in Renewable Energy

 

Everything loaded with pros always backfires some cons too. Similarly, there are the areas where the power of AI is limited or not utilised well. The disadvantages of AI in renewable energy are as follows:

 

1. Insufficient theoretical background

 

AI theories aren't supported by scientists and researchers. The lack of required knowledge prevents the industries and firms from incorporating AI in their procedures.

 

Many companies want to invest in AI but lack proper tools and resources too. Therefore the benefits of AI aren't fully utilized in several fields.

 

2. Insufficient Practical Experts

 

Unlike traditional operation, AI requires skilled workers who are aware of its technologies and its benefits. AI is still in its neonatal phase, especially in India. So only a small percentage of professionals have mastered it.

 

And, out of those small percentages only few can bring the direct application of AI into practical operations. Thus the utilization of AI is limited.

 

3. Technical Maintenance

 

The management of AI is quite a technical process and requires sufficient technologies and tools for the management.

 

Data gathering and then managing it with innovative challenges is a hard to achieve job. AI and its technologies are often stuck in challenges like unauthorised access, data loss, system failures and other technical disputes.

 

4. Lack of Finance

 

There's no doubt that implementation of AI and it's technologies is a costly process. And energy companies are already struggling with finance and profits. Though, smart energy is a best option but practically not possible to implement due to its cost reasons. Companies think 10 times before contributing their budget for AI.

 

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Summing up the whole conditions, it is the need of the hour to invest more in clean energy and renewable energy resources. We have already destroyed so many percentiles of this planet, if efforts are not taken to increase sustainability. 

 

The conditions can be worse than expected. Companies and firms need to allocate a particular part of their budget for renewable energy and its organization. 

 

AI has transformed many sections and the energy field is no exception. Already different studies and trials have suggested the scope of AI in organising renewable energy. Only, the final shot is left, that is its implementation and implications.