A comprehensive review of smart energy management systems for photovoltaic power generation utilizing the internet of things

IF 4.6
Challa Krishna Rao , Sarat Kumar Sahoo , Franco Fernando Yanine
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Abstract

Renewable energy represents the most reliable and widely recognized solution for meeting the escalating global energy demands. The optimization of solar energy generation necessitates a strong focus on predictive maintenance and advanced deployment methodologies. To enhance solar power utilization, Internet of Things enabled solar monitoring systems have been proposed for real-time data acquisition and analytics, facilitating performance forecasting and ensuring consistent power output. A critical challenge in demand-side energy management lies in optimizing the integration of renewable resources while maintaining cost efficiency and minimizing energy losses. Therefore, strategic planning for the integration of renewable energy sources is imperative. Intelligent energy management systems play a pivotal role in optimizing energy distribution, particularly in scenarios with high grid dependency. Cloud computing infrastructures address the complexities and scalability challenges posed by expanding smart grids, enabling real-time data processing and adaptive energy control mechanisms. This study explores the practical implementation of energy management system in industrial settings and research domains, both of which serve as key stakeholders in advancing smart energy solutions. A comprehensive review of internet of things applications in photovoltaic power generation highlights key research objectives and technological developments in the field. The evolving landscape of internet of things driven innovations presents numerous research opportunities, including the formulation of performance evaluation metrics and the development of novel optimization techniques. Additionally, the growing emphasis on energy management within intelligent architectural frameworks underscores the necessity for deeper investigations into adaptive control strategies and system interoperability. This ongoing research is essential for driving advancements in internet of things enabled energy solutions and enhancing the efficiency of smart grid ecosystems.

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基于物联网的光伏发电智能能源管理系统综述
可再生能源代表了满足不断增长的全球能源需求的最可靠和广泛认可的解决方案。太阳能发电的优化需要高度关注预测性维护和先进的部署方法。为了提高太阳能的利用率,已经提出了物联网太阳能监测系统,用于实时数据采集和分析,促进性能预测并确保一致的功率输出。需求侧能源管理的一个关键挑战在于优化可再生资源的整合,同时保持成本效率和最大限度地减少能源损失。因此,对可再生能源的整合进行战略规划势在必行。智能能源管理系统在优化能源分配方面发挥着关键作用,特别是在高度依赖电网的情况下。云计算基础设施解决了智能电网扩展带来的复杂性和可扩展性挑战,实现了实时数据处理和自适应能源控制机制。本研究探讨了能源管理系统在工业环境和研究领域的实际实施,这两者都是推进智能能源解决方案的关键利益相关者。全面回顾了物联网在光伏发电中的应用,重点介绍了该领域的主要研究目标和技术发展。物联网驱动的创新不断发展,提供了许多研究机会,包括制定绩效评估指标和开发新的优化技术。此外,对智能架构框架内能源管理的日益重视强调了深入研究自适应控制策略和系统互操作性的必要性。这项正在进行的研究对于推动物联网能源解决方案的发展和提高智能电网生态系统的效率至关重要。
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