How to store renewable energy for longer period of time and which technologies are useful

Abstract

This thesis provides a comprehensive overview of various renewable energy sources, followed by an in-depth analysis of three key energy storage methods – batteries as short-term storage, hydrogen and methane as long-term storage. The first part of the thesis offers a detailed introduction to several renewable energy sources, emphasizing their potential and limitations. Subsequently, it delves into the complexity of battery technology, highlighting its suitability for short-duration energy storage. The focus then shifts to exploring hydrogen and methane as feasible solutions for long-term energy storage, examining their production processes, storage mechanisms, and potential applications.

The second part of the thesis bridges the gap between renewable energy storage and the latest technological advancements by introducing four cutting-edge methods: Internet of Things (IoT), big data, edge computing, and machine learning. This segment discusses how the Internet of Things (IoT) can improve the efficiency and reliability of energy storage systems by enabling real-time monitoring and management. The examination of big data’s role is important in enhancing storage system optimization and advancing predictive maintenance methodologies. Edge computing is presented as a solution for processing large volumes of data closer to the source, thereby reducing latency and improving response times in energy management. Lastly, the application of machine learning is discussed in terms of predictive analytics, which can forecast energy demand and optimize storage and distribution.