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IoT in Renewable Power Energy: A Comprehensive Review

A recent review article published in the journal Energies explored the transformative role of the Internet of Things (IoT) in modern power systems, focusing on its impact on integrating and managing renewable energy sources. The researchers conducted a comprehensive literature review to assess how IoT technologies improve renewable energy systems' efficiency, reliability, and sustainability.

internet of things, IOT, renewable energy

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Background

The global shift toward renewable energy is driven by the need to reduce greenhouse gas emissions and combat climate change. Technologies like wind, solar, and biomass have become cost-effective and efficient alternatives to fossil fuels. However, integrating these sources into the existing power grid poses challenges. This is where the IoT emerges as an essential system to optimize the performance of renewable energy systems.

IoT connects devices, sensors, and actuators, enabling seamless communication and data exchange. This interconnected network allows real-time monitoring of energy production, consumption, and grid conditions, enhancing demand response, load management, and energy storage. By collecting and analyzing data in real-time, IoT empowers energy providers and consumers to optimize energy use and improve grid stability.

About the Review

In this paper, the authors reviewed several leading scientific databases, such as Web of Science and Scopus, to investigate the diverse applications of IoT in the energy sector. They employed relevant keywords, such as "Internet of Things", "IoT", "renewable energy", "smart grids", "electric vehicle", and "EV" to capture a comprehensive understanding of the field.

By surveying 74 highly relevant papers, the study aimed to assess recent advancements and identify trends and challenges in integrating IoT systems with renewable energy technologies.

Key Findings

The study highlighted the significant impact of IoT on renewable energy integration and management. IoT-enabled data analysis, real-time monitoring, and automation significantly improved the performance of solar, biomass, and wind energy systems. Integrating IoT with these renewable sources supported efficient energy management, reduced greenhouse gas emissions, and enhanced grid stability.

IoT technologies transformed smart meters, distribution systems, and demand response mechanisms in smart grids. Smart meters, equipped with advanced hardware and software for measurement, communication, and data management, were essential for optimizing power management in smart grids.

IoT-enabled distribution systems use sensors, automated controls, and real-time data analytics to optimize electricity distribution, boosting grid stability and supporting renewable integration.

The study also examined IoT's role in microgrids, emphasizing its benefits in precise energy scheduling, improved grid reliability, and integrating distributed energy resources (DERs). IoT-based energy management systems (EMSs) in microgrids, such as those on university campuses, enhanced energy efficiency and reduced operational costs by incorporating demand response strategies.

The researchers explored the impact of IoT on the control and protection of power systems. IoT-enabled fault detection and real-time monitoring improved power systems' responsiveness to anomalies, ensuring safe and reliable operations.

Advanced IoT systems, such as sensors and smart meters, provide detailed information about energy consumption, supporting efficient energy use and dynamic pricing models.

Applications

Integrating IoT with electric vehicle (EV) technology significantly impacts energy management and grid stability. IoT-enabled smart grids can monitor and control EV charging in real-time, optimizing energy use based on grid demand and availability. This interaction helps reduce peak loads during high-demand periods, enhancing grid stability. Vehicle-to-grid (V2G) technology also allows EVs to supply stored energy to the grid during peak demand or emergencies, supporting grid resilience and providing extra income for EV owners.

Conclusion

The review summarized that integrating IoT with renewable energy technologies can revolutionize the energy sector by enhancing efficiency, sustainability, and reliability in power systems, ultimately contributing to a greener and more resilient future. However, challenges like privacy and data security concerns and standardized communication must be addressed to unlock IoT's full potential.

Moving forward, the authors suggested developing new business models, improving cybersecurity, and exploring new applications of IoT in the energy sector. They also recommended integrating artificial intelligence (AI) and machine learning (ML) with IoT to improve decision-making, predictive maintenance, and autonomous operations. They also emphasized collaborating with industry stakeholders, researchers, and policymakers to further improve the sustainable and resilient energy infrastructure, promote the adoption of renewable energy sources, and enhance the security and reliability of modern power grids.

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Source:

Jia, L.; Li, Z.; Hu, Z. Applications of the Internet of Things in Renewable Power Systems: A Survey. Energies 2024, 17, 4160. DOI: 10.3390/en17164160, https://www.mdpi.com/1996-1073/17/16/4160

Muhammad Osama

Written by

Muhammad Osama

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence.

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