Data-Intensive Computing in Smart Microgrids

This book examines the role of data-intensive analytics in optimizing smart microgrids, enhancing energy management and sustainability. Data-Intensive Computing in Smart Microgrids provides practical insights and research contributions.

In Data-Intensive Computing in Smart Microgrids, the author explores the transformative potential of microgrids as foundational elements of smart grid technology. By integrating distributed renewable energy sources, energy storage devices, and advanced load management systems, microgrids enhance power system reliability while promoting sustainable development and reducing carbon emissions. The book delves into how these systems not only improve energy efficiency but also empower consumers to manage their energy usage more effectively.

The rapid advancements in sensor and metering technologies, alongside developments in wireless communication and cloud computing, have resulted in the generation of vast amounts of data. This data, encompassing device status, energy generation, and consumption patterns, can be harnessed through big data analysis techniques such as forecasting and clustering. The author emphasizes that applying these techniques allows for real-time optimization of power generation and operation, ensuring that electricity demands are accurately predicted and managed.

Ultimately, Data-Intensive Computing in Smart Microgrids presents a collection of innovative research contributions that highlight the practical applications of data analytics in smart grid environments. By offering insights into effective decision-making for producers, operators, customers, and regulators, the book aims to foster a comprehensive understanding of smart energy management, covering aspects from generation to demand-side management. This work serves as a valuable resource for those interested in the intersection of data analytics and energy systems.