Even though most of our energy needs are being met by fossil fuels, the world’s energy sector has witnessed a massive evolution over the last century. The most reliable, efficient and environmentally friendly alternative to fossil fuels is renewable energy – with the leading power generation sources being wind and solar. Renewable energy has already majorly disrupted the traditional infrastructure of the energy sector; however, with the introduction of more innovative technologies; you can expect to witness an even massive transformation.
Despite all the advantages of renewable energy, the energy sector is still facing many daunting challenges. The conflicting views on global climate change is making commitment towards renewable energy sources less sure. However, major oil and gas, and renewables companies continue to work towards more reliable power supply for the public. Energy specific AI technologies, although arguably in their infancy, are offering very feasible solutions to the challenges present across the sector.
Artificial Intelligence (AI) is expected to improve the process of identifying new opportunities and production efficiency for traditional and evolving energy systems. With more oil companies and R&D departments increasing their investigations into leveraging AI, it is coming to light that AI is returning accurate results, however further investment is required to take AI beyond the lab and into real world, field applications.
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Centralized Control Centers
With advancements in technology, it’s no surprise that the energy grid can be interconnected with multiple sensors and devices to collect data. With the help of Artificial Intelligence, grid operators will gain better insight of existing infrastructure operations and use AI to maximise site availability, improve network communications, and increase OPEX reduction. . Energy providers are pushing for a smarter grid and considering how greater flexibility and efficiency can be applied to industrial equipment, battery storage, and cross-source supply.
Enhanced Integration of Microgrids
Adding additional community-level renewable energy generation units to the primary grid can create difficulties in establishing a balanced energy flow within the grid. Artificial Intelligence can greatly aid the integration planning of microgrids with existing energy systems. An AI-mechanized control system not only helps solve overall energy consumption efficiency, but also aids with congestion problems.
Programs such as Adaptive Dynamic Programming or multi-agent systems offer businesses the chance to control real-time operations while optimizing the entire system. Considering the introduction of more innovative energy generation devices and sources, learning AI algorithms is integral now.
Smart Grid with Intelligent Storage
Incorporating Artificial Intelligence (AI) with Intelligent Energy Storage (IES) is a very sustainable and highly reliable solution for the renewable energy industry. Using AI and IES together creates a smart grid that works efficiently at collecting and analyzing massive data quantities from multiple sensors. It’s also great for making timely decisions regarding energy allocation.
A smart grid enables microgrids to manage local energy needs while maintaining power exchange with the principle grid. Intelligent storage units can easily be adjusted depending on the supply flow of energy. Also, smart devices and advanced sensors serve the purpose of making load and weather predictions, improving the overall renewable energy system efficiency.
Weather Forecasting
Perhaps one of the leading challenges faced by renewable energy sources – such as wind and solar, is predictingthe weather for subsequent energy outputs. To create accurate weather predictions, most analysts rely on historical and real-time data sets from hundreds of weather satellites. Although extremely complicated and highly complex, companies such as IBM are increasing their investment in AI weather prediction.
Improving forecasting models is integral to the common challenge of improving efficiency during intermittent power serving, as well as competitive electricity prices and market bids.
Expand the Market
Artificial Intelligence technology has brought about changes and created opportunities in many industries. Although it is evident that AI has strong use cases in oil exploration, AI also has massive potential to contribute towards the renewable energy sector, enhancing the capabilities of energy suppliers and distributors – in terms of both energy forecasting and consumption.
AI-operated systems enable the assessment of energy-related data while providing detailed insights into energy consumption. This information is very helpful for suppliers, not only in optimizing their existing services but also in launching new service models. Retail suppliers can also benefit from AI as they’ll get the opportunity to reach out to new consumer markets.
Improved Safety and Reliability
Even though one of the main objectives of Artificial Intelligence in the renewable energy sector is to improve the efficiency of energy distribution, it also provides enhanced safety and reliability. Inspection firm WKA is using drones and AI to systematically inspect fleets of wind turbines and produce automated reports from the inspections conducted.
Additionally, AI learning algorithms can help gather data from solar panels or wind turbine sensors to assess their overall condition. This system will constantly monitor the health of the equipment and warn the operator in case any maintenance is required.
Conclusion
The notion of Artificial Intelligence as a feasible solution for amplifying the potential of the renewable energy sector is growing in strength. A growing number of energy-reliant industries are making considerable investments in AI, particularly for improved forecasting capabilities. An energy consulting case study can help you better understand the application of intelligence solutions across the sector as a whole.