Artificial Inteligence in Renewable

by Victor Akere

In Nigeria, renewable energy access is often impeded by a lack of reliable data and information. However, artificial intelligence (AI) has the potential to help overcome these challenges and provide insights that can help improve renewable energy access in the country. For example, AI can be used to analyses data from weather stations to better predict patterns of solar insolation, making it possible to more accurately forecast solar power output. This is particularly important in a country like Nigeria, where much of the population lives in rural areas without access to electricity.

Using new technologies, such as AI, is the key to building a lower-carbon future. Indeed, AI presents many opportunities for the Renewable Energy industry to develop sustainable and stable systems.

Benefits integrating Artificial Intelligence in Renewable Energy System

As our energy mix shifts from fossil fuels to renewables, predicting capacity becomes even more important. As an increasing amount of our energy comes from renewable sources, baseload generation from fossil fuels decreases. This could cause power grids to become less stable and more likely to experience blackouts.
AI can be used to develop new methods for mapping potential renewable energy resources. This is vital for countries like Nigeria that have large but underdeveloped renewable energy potential. By harnessing the power of AI, it may be possible to identify previously undiscovered renewable energy resources and help bring them into development.Ultimately, AI has the potential to play a significant role in overcoming the challenges associated with renewable energy access in Nigeria. By providing accurate data and insights, AI can help pave the way for a more sustainable future for the country. Artificial intelligence is a natural fit for this market as it is finding its way into many areas of our lives. It lends itself to the creation of a lot of value by providing real-time information about where and when to deploy resources, such as wind power, solar panels, or batteries.

One of the biggest threats to today’s energy grids is power outages. This can be mitigated by automation and AI. Collecting data from sensor technologies, as well as with historical weather data from satellite imagery and sky cameras, AI can help predict capacity levels and future downtime periods. Together, these help maintain a stable power grid. AI-powered data interpretation also allows power grid operators to use grids more efficiently. They’re able to tailor their operations to match whatever the weather is currently doing, which can lead to improved dispatch efficiency and unit commitment, and reduced reserves, ultimately making the grid more reliable.

Improved solar forecasts have been demonstrated to reduce operational electricity generation costs, lower start-up and shutdown costs of conventional generators, and decrease the on-demand power curtailment of solar generators.

With the help of AI, energy management storage systems can predict when consumers will need power and be able to provide it. Batteries can supply power for periods of high demand by being activated quickly and making sure demand is met across the network. And with AI, data that includes predictions of energy needs and an assessment of renewable sources will always factor into any calculations.

Artificial intelligence also has an important role to play when it comes to maintenance. It can almost instantly detect disturbances and system malfunctions. It can identify what kind of issues are happening and predict what kind of issues could happen in the future, making it a lot easier to fix and maintain networks.

The demanding situations of integrating AI into the Renewable Energy Sector

AI is great for Renewable Energy companies, but there are a few challenges that are slowing down its adoption. One of those challenges is that not enough decision-makers fully understand the technology behind it. Additionally, there’s a high cost of implementation because of the integration process, which has slowed wide-ranging adoption.

Although AI is becoming more prevalent in the industry, there’s still a lack of theoretical and practical knowledge. AI is relatively new, and few people have experience working with it. Practical experts within the field who can make it applicable to the real world are in high-demand.

One of the biggest challenges with Renewable Energy is maintaining an infrastructure that will work well with new technology. An outdated infrastructure can be a major barrier to modernisation and the adoption of AI-based technology within the industry. Gathering data and analysing it can be tough, which leads to many companies suffering losses when they are unable to process data efficiently.

Another drawbacks to majoring in renewable energy is that the cost can be prohibitive. However, these challenges also present opportunities, and there’s plenty to look forward to within the Renewable Energy Industry.

AI offers enormous potential for the energy industry and is key to transitioning to a cleaner energy future. It will bring about greater automation, making it easier and cheaper to do business, developing new products, and reducing expensive carbon emissions.

Experts predict that by 2025, 81% of the world’s power will be generated from renewables. This likely means more manpower and know-how will be needed to keep producing the structures and infrastructures necessary to carry global energy into a renewable future.


While there are challenges to integrating AI into renewable energy, the potential benefits make it worth investigating. With the right approach, AI could help us unlock new sources of renewable energy, improve the efficiency of existing systems, and reduce our reliance on fossil fuels. In a world grappling with climate change, the need for clean energy has never been greater. We hope that by harnessing the power of AI, we can meet this challenge and build a sustainable future for generations to come.

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