Microgrid systems, with diverse energy sources and decentralized control, are revolutionizing energy management. However, integrating renewable energy sources and consumer demands poses challenges to grid stability. Machine learning (ML) is a key tool for optimizing energy management and adaptive control in microgrids, enabling accurate load forecasting, renewable energy output prediction, and efficient resource utilization. This abstract discusses the potential of ML in revolutionizing microgrid systems by enabling adaptive control mechanisms, predictive maintenance, early fault detection, and proactive scheduling. ML also addresses cybersecurity concerns, providing sophisticated solutions for intrusion detection and secure data management. This approach optimizes operations, drives innovation, and ensures resilient, cost-effective, and sustainable energy infrastructures.
TopIntroduction
Microgrid systems are a new approach to traditional centralized energy distribution, offering a localized, adaptable system for power generation, distribution, and consumption. These systems consist of interconnected energy sources and loads, which can operate independently or in conjunction with the main grid, providing increased flexibility and resilience. They address challenges like aging infrastructure, climate change, and increased demand, making them a promising alternative (Chandraratne et al., 2020).
Microgrid systems utilize various energy sources like solar panels and wind turbines, along with energy storage systems. Advanced control systems and intelligent algorithms ensure efficient resource utilization. Microgrids offer improved energy reliability, especially in remote areas, and enable the integration of renewable energy sources, contributing to environmental sustainability by reducing reliance on fossil fuels and lowering carbon emissions. Microgrid systems offer a decentralized, reliable, and autonomous power supply, benefiting communities, businesses, and critical facilities (Barra et al., 2020). The evolution of microgrid technology is driven by advancements in control systems, energy storage, and smart technologies like IoT and machine learning. This evolution optimizes microgrid performance, enhances energy efficiency, and ensures seamless integration with the broader electrical infrastructure. Understanding and harnessing the potential of microgrid systems is crucial for shaping the future of energy distribution and consumption, as the world seeks more sustainable energy solutions (Kaur et al., 2021).
Microgrids are a revolutionary energy distribution system that offer localized, self-sufficient networks capable of generating, managing, and distributing electricity. They are smaller versions of traditional power grids, but possess unique characteristics that differentiate them from centralized systems. Microgrids are adaptable, resilient, and integrate diverse energy sources. They can operate connected to the main grid or autonomously, serving various purposes like supporting remote communities and optimizing energy use in urban environments. Their modularity allows for scalability, allowing them to be tailored to specific needs and expanded as demand increases (Khaleel, 2023).
Microgrids are energy systems that use renewable energy sources like solar panels, wind turbines, and biomass or hydroelectric. They are integrated with energy storage systems like batteries or flywheels to ensure continuous power supply even when renewable sources fluctuate. Advanced control and monitoring systems, using algorithms, real-time data analytics, and smart sensors, optimize energy flow, balance supply and demand, and ensure grid stability. These technologies also enable predictive maintenance, enhancing reliability and mitigating potential issues (Behera & Dev Choudhury, 2021).
Microgrids are crucial for grid resilience and energy management due to their decentralized approach to power generation and distribution. They reduce vulnerabilities to outages and enhance system reliability. As the energy landscape evolves, microgrids' adaptability, sustainability, and reliability make them essential for future energy infrastructure. Efficiency is a cornerstone in microgrid operations, optimizing resource utilization, enhancing cost-effectiveness, and ensuring power supply reliability (Leonori et al., 2020). This focus on efficiency encompasses energy generation, distribution, and system management. Microgrid efficiency is a system that optimizes energy resources by combining renewable sources like solar, wind, and hydro with conventional ones. This ensures clean and sustainable power, reducing dependency on non-renewable resources and minimizing environmental impact. Energy storage technologies, like batteries or flywheels, store excess energy during peak production periods, which can be used during high demand or less productive periods, ensuring a stable power supply. This approach significantly contributes to microgrid efficiency (Ramesh et al., 2021).