With the rapid progress on many environmental issues, such as global warming, deforestation, extinction of animal species, and more, the development of possible contra-measurements increases in importance. Among such environment-protecting methods are segregating rubbish, sparing energy, reducing your use of plastic, utilizing green energy, and more.
Previously, the impact of technology on many of these prevention activities wasn’t considered a big deal. However, now, the rapid development of new technology, including AI and Machine Learning, has brought us to the point where technological advancements can be utilized for protecting our planet and ensuring environmental sustainability.
In this article, we talk about how AI benefits the renewable-energy industry, how it is implemented, and what to expect next.
Also, if you are interested in the combination of technology and saving the environment, consider reading these articles: 5 Ways AI can Improve Environmental Sustainability and How AI Helps Clean Oceans from Plastics.
For more on renewable energy, access this article: Top Renewable Energy Companies to Watch.
Energy and Environment: How Harmful Is It?
We use energy everywhere in our day-to-day lives: to charge our phones, light up our houses, heat and cool our apartments, fuel our vehicles, etc. So, first, we must define what types of energy help us perform all of these functions.
There are two main types of energy: renewable and non-renewable. Non-renewable energy encompasses all fossil fuels like gas, oil, or coal that cannot be replicated and substituted artificially (at least for now).
The usage of these energy sources is huge, and as they are irreplaceable, they can become entirely exhausted in the upcoming decades. Furthermore, fossil fuels are some of the main sources of greenhouse gas emissions, which are responsible for global warming.
Against this backdrop, the push for sustainable alternatives becomes critical, and the rise of renewable energy sources like solar and wind energy is growing more and more prominent. For instance, initiatives like the commercial EV charging station installation in Colorado Springs serve as practical examples of how a renewable energy approach can be integrated into everyday life. This movement not only reduces reliance on non-renewable energy sources, but it also presents an opportunity for technological innovation and societal progress. The coupling of such green initiatives with technologies like artificial intelligence can expedite the transition to cleaner energy while also making it more efficient and accessible.
On the other hand, renewable energy is one of the main focuses for many developed and developing countries worldwide. Governments prefer to be dependent on green energy rather than fossil fuels. However, the development of the renewable-energy industry is restrained by the current dependence on non-renewable energy sources.
Renewable energy can be defined as energy that is produced by renewable energy sources, such as sunlight, water, wind, and geothermal heat. Hence, the renewable-energy industry is oriented toward creating efficient energy facilities, popularizing the industry, and shifting the focus from non-renewable energy sources to renewable ones.
Renewable energy is increasing in popularity because of its eco-friendliness. On the other hand, when burned, fossil fuels release a lot of carbon dioxide (a greenhouse gas) into the atmosphere. Hence, the over-release of this chemical into the air leads to global warming, which triggers other environmental problems, including forest fires, the rise of the sea level, the destruction of natural habitats for animals, etc.
AI in the Renewable-Energy Industry
One of the branches where artificial intelligence is utilized is weather forecasting. You may want to ask, how is this connected to renewable energy? Renewable energy is fully dependent on such sources as sunlight, wind, and water movement. These, in their turn, depend on the weather, which humans cannot control. Hence, AI helps enhance the accuracy of weather forecasting by analyzing current and historical weather conditions. Energy companies can then utilize the forecasts and plan their next steps, for instance, producing and storing energy when the weather is good or implementing fossil fuels to keep the power supply uninterrupted.
Weather is not the only thing AI can predict. Artificial intelligence plays a pivotal role in understanding and estimating how much energy households may need in specific year seasons. For example, machine learning methods can draw energy consumption predictions based on last year’s data and the current year’s season, allowing energy companies to decrease production to avoid wastage or raise the amounts of produced energy.
Currently, among many well-known concerns regarding energy are unpredictable energy cuts that residents are not always informed about. However, AI can solve this problem by analyzing the system and predicting the parts that will need maintenance.
In this case, it will be much easier for energy companies to inform residents about upcoming maintenance works and schedule them appropriately.
One more way in which AI and ML can benefit the renewable-energy industry is by decreasing energy costs and reducing energy waste. For instance, smart heating, ventilation, and air conditioning systems utilize AI to optimize electricity sources by informing residents of various efficiency limitations. In this case, the problems that decrease the systems’ efficiency can be discovered and addressed way more quicker.
Additionally, scientists try to develop devices and vehicles that require fewer fossil fuels and, therefore, save customers’ expenses on gas and oil. For example, such AI systems as smart lights improve customers’ financial savings by controlling light usage.
The Future of AI in the Renewable-Energy Industry
With all the development opportunities artificial intelligence brings to the renewable-energy industry, it is evident that this technology will take its place in it in the future. As mentioned before, grid analysis and maintenance are some of the most crucial AI applications in this industry. For instance, Google’s subsidiary DeepMind claims that the company’s ML algorithms can significantly improve the accuracy of predicted energy outputs of a wind farm, which makes this wind farm more valuable to the energy grid as it can provide certainly defined amounts of power on time. As such, great developments in this field are expected in the future.
In addition to the aforementioned functions, artificial intelligence can predict grid capacity levels and perform time-based autonomous pricing and trading. Furthermore, data analytics and machine learning begin to be implemented in performance analysis and renewable energy model designing.
Solar panels are widely used for generating energy from sunlight. However, one problem regarding these panels remains unsolved. The technique for recycling solar panels after the end of their lifecycle has not been created yet, which arises a serious rubbish concern. Hence, scientists and researchers plan to utilize AI in testing various materials to define those that can be used for the development of next-generation solar panels.
In this case, artificial intelligence analyzes various materials and tries to find those that will be suitable enough to replace the existing solar panels.
One more probable future application of AI is the development of a centralized coordination layer for the generation, transmission, and utilization of energy. So, the technology can help identify patterns in data, predict collisions and complex situations, model possible outcomes, and learn from experience.
In a nutshell, the world is in need of new renewable-energy solutions, which AI can provide. With the help of this technology, companies can develop more effective energy-producing facilities and improve various processes connected within this industry.
