IoT – AI, Major Contributors to the Growth in Renewable Energy Capacity

The integration of cutting-edge technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) has revolutionized the landscape of renewable energies, bringing them to a crucial turning point in the fight against climate change. These technologies have not only improved the efficiency and sustainability of energy generation but have also radically transformed the management and distribution of energy resources. From the implementation of smart grids to the optimization of microgrids and real-time energy trading, IoT and AI are fundamental pillars in driving a cleaner and more resilient energy infrastructure

Renewable energies, whether solar, wind, hydro, or geothermal, have substantially shifted the energy industry, marking a significant step toward becoming the primary source of electricity generation in the near future. Over the past decade, the development of these energies and the transition towards them have become a matter of environmental responsibility and a strategic necessity to address the climate crisis.

By generating electricity while avoiding greenhouse gas emissions, the increase in the implementation and use of renewable energies is a fundamental factor in mitigating climate change. Their use improves air quality, reduces dependence on fossil fuels, thereby conserving their finite reserves, and minimizes the environmental impacts associated with their extraction and transportation. Furthermore, investment in renewable energy infrastructure stimulates economic growth, enhances competitiveness, and fosters innovation in clean technologies, contributing to sustainable development.

According to the latest report by the International Energy Agency (IEA), published at the beginning of 2024, the installed renewable energy capacity worldwide increased by 50% in 2023 compared to the previous year. The IEA forecasts that this capacity will experience unprecedented growth in the next five years, the largest in the last three decades, making it a real possibility to achieve the goal set by governments for COP28 to triple global capacity by 2030. However, current market trends and policies suggest that it will likely only increase by a factor of 2.5.

A Definitive Boost for Renewable Energies

In its 2023 statistics, the International Renewable Energy Agency (IRENA), an intergovernmental organization that supports countries in their transition to a sustainable energy future, reported a new global record in the deployment of renewable energies in the electricity sector, with a total installed capacity of 3,870 gigawatts (GW). China led the way with a 63% increase (297.6 GW) in its capacity, followed by Europe, the United States, and Brazil.

In this growing implementation and movement toward renewable energies, emerging technologies like AI, IoT, machine learning (ML), and blockchain play a leading role by enabling strong optimization in energy generation, system maintenance, grid management, and domestic consumption.

The implementation of these advanced technologies is based on and enhanced by massive and effective data collection through IoT sensors across the entire energy ecosystem. Their network communication capability is key to the effective application of AI, allowing for real-time data analysis and action, improving precision and efficiency. AI then facilitates the efficient integration of renewable energy resources into the grid, optimizing all processes.

For instance, smart grids, enhanced by AI and IoT sensors, optimize the generation, transmission, and distribution of electricity. Using real-time data from IoT devices and smart meters, they improve energy flow and reduce waste. By predicting demand and detecting anomalies, AI helps balance supply and demand more efficiently, reducing energy consumption. The immediate responsiveness of these grids not only enhances operational efficiency but also contributes to greater environmental sustainability.

Precision and Efficiency in Energy Forecasting and Management

This relevance also extends to microgrids, which are localized networks that can operate independently or in conjunction with the main grid, allowing for greater autonomy and resilience, especially in isolated regions or those vulnerable to natural disasters. In these microgrids, AI and machine learning optimize their operation by managing energy flow and efficiently integrating renewable sources. AI also enhances grid security by detecting and mitigating cyber threats in real-time. ML models analyze data patterns to identify potential attacks and implement countermeasures, ensuring the resilience and reliability of the grid.

The ability to process and analyze data in real-time improves the accuracy and speed of decision-making and automates crucial processes for the industry. Maximum efficiency is achieved with these IoT devices and AI algorithms in the performance of various renewable energy systems. For example, improving the efficiency of wind turbines and solar panels by adjusting their operations based on real-time data and predictive analysis. This not only optimizes the grid infrastructure but also increases energy production, reduces operational costs, and extends the lifespan of the equipment, a crucial factor in expanding renewable generation capacity.

These advanced technologies not only accelerate the transition to a more efficient and sustainable energy model but also facilitate predictive maintenance based on conditions that enhance safety. By incorporating AI and IoT, and efficiently managing complex variables, there is a significant cost reduction in the planning, development, and construction of renewable energy plants. AI-based predictive analyses have significantly improved the accuracy of energy forecasting, which is crucial for integrating renewable sources like solar and wind.

Energy Trading, a Smarter Market

On the other hand, precise predictions, with real-time data on prices and demand thanks to AI and ML algorithms, enable more efficient trading and better integration of renewable energy into the market. This anticipates fluctuations and ensures the stability and profitability of investments, while allowing operators to make informed decisions and optimize their energy portfolios.

Moreover, its influence extends to consumption, by analyzing patterns and predicting the best times to incentivize usage reductions. In this regard, AI optimizes these programs to maximize energy efficiency and minimize environmental impact, in a proactive approach that not only reduces costs for consumers but also supports long-term sustainability goals.

Among the values contributed by the increasing incorporation of AI and IoT in the development and implementation of renewable energies are: helping consumers manage their consumption more effectively, improving operational efficiency and energy management, driving innovation in energy service offerings, developing customized solutions tailored to changing market needs, contributing to environmental sustainability, and increasing the resilience of energy infrastructures to extreme weather events or other challenges.

Maximum Efficiency in Renewable Energy Systems Optimization

Committed to the Sustainable Development Goals, the Colombian multinational AZLOGICA®, with a presence in ten countries in Europe and America, stands out as a model of excellence in digital solutions for renewable energies. Leveraging the power of data analysis, automation, and decentralized systems, AZLOGICA® offers solutions like ECODRIVE®, an innovative energy management platform that helps reduce environmental impact.

ECODRIVE® provides online monitoring and control of mobile and stationary assets, measuring control variables and efficiency in environmental performance, energy consumption, usage habits, and emissions and waste, enabling quick decisions for effective environmental management. Similarly, AZLOGICA® offers Evolution®, a logistics-focused solution that encompasses all strategic, operational, and tactical levels, integrating and coordinating key activities, which even promote the modeling and development of new energy products, accelerating the transition to renewable energy and reducing innovation costs.

A notable application within AZLOGICA®‘s solutions in this field is its partnership with Biotermica Innovación, a company focused on the development and application of organic waste transformation processes, and which builds bioreactors and biorefineries to produce renewable energy, addressing social, environmental, and economic issues. AZLOGICA® contributes to the instrumentation, monitoring, and remote control of equipment, allowing the identification of various operations.

AZLOGICA®‘s AI and IoT solutions in the renewable energy field set standards of excellence for creating more inclusive, safe, and resilient spaces and infrastructures, providing the necessary tools for better informed decision-making, and contributing to the broader goal of sustainable development.

In conclusion, the synergy between AI and IoT is transforming the energy sector, providing the tools necessary to face future challenges. The ability of these technologies to optimize efficiency, improve sustainability, and reduce operational costs is crucial for the transition to a cleaner and more efficient energy system. With a continuous focus on innovation and efficiency improvement, AI and IoT will remain fundamental pillars in developing a cleaner and more responsible energy future. In this ongoing implementation, AZLOGICA® continues to contribute to the future of renewable energies, which seems more promising than ever, offering a clear path toward a decarbonized economy and a healthier planet.

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