← 返回
电动汽车驱动 储能系统 DAB 可靠性分析 ★ 5.0

智能电网在可持续能源管理中的广泛应用与系统性综述:应对人工智能、可再生能源集成与前沿技术挑战

An Extensive and Methodical Review of Smart Grids for Sustainable Energy Management-Addressing Challenges with AI, Renewable Energy Integration and Leading-edge Technologies

语言:

中文摘要

能源管理通过提升能效、降低能耗与碳排放,显著改善系统运行性能。智能电网作为先进的能源基础设施,融合数字通信与多种前沿技术,增强电力系统在发电、输配过程中的可持续性、可靠性与效率。近年来,围绕智能电网的研究成果丰硕。本文系统综述其核心组件、技术进展、可再生能源整合、人工智能与数据分析应用、网络安全及隐私保护等关键议题。重点探讨间歇性可再生能源接入、网络攻击防御、电动汽车规模化并网等挑战,并分析人工智能在优化电网运行、提升可靠性和能源管理效能中的作用。最后指出当前研究的关键问题并提出未来研究方向。

English Abstract

Energy management decreases energy expenditures and consumption while simultaneously increasing energy efficiency, reducing carbon emissions, and enhancing operational performance. Smart grids are a type of sophisticated energy infrastructure that increase the generation and distribution of electricity’s sustainability, dependability, and efficiency by utilizing digital communication technologies. They combine a number of cutting-edge techniques and technology to improve energy resource management. A large amount of research study on the topic of smart grids for energy management has been completed in the last several years. The authors of the present study want to cover a number of topics, including smart grid benefits and components, technical developments, integrating renewable energy sources, using artificial intelligence and data analytics, cybersecurity, and privacy. Smart Grids for Energy Management are an innovative field of study aiming at tackling various difficulties and magnifying the efficiency, dependability, and sustainability of energy systems, including: 1) Renewable sources of power like solar and wind are intermittent and unpredictable 2) Defending smart grid system from various cyber-attacks 3) Incorporating an increasing number of electric vehicles into the system of power grid without overwhelming it. Additionally, it is proposed to use AI and data analytics for better performance on the grid, reliability, and energy management. It also looks into how AI and data analytics can be used to optimize grid performance, enhance reliability, and improve energy management. The authors will explore these significant challenges and ongoing research. Lastly, significant issues in this field are noted, and recommendations for further work are provided.
S

SunView 深度解读

该综述对阳光电源多产品线具有重要指导价值。在储能系统方面,AI优化算法可提升PowerTitan系统的能量管理效率和电网调度响应能力;网络安全技术可强化ST系列储能变流器的通信防护。在光伏逆变器领域,可再生能源间歇性应对策略可优化SG系列的并网控制算法,提升1500V系统稳定性。电动汽车规模化并网研究直接支撑充电桩产品的V2G技术开发和车载OBC的智能充电策略。构网型GFM控制技术可借鉴AI数据分析方法实现更精准的虚拟同步机参数自适应调节。iSolarCloud平台可融合智能电网的预测性维护技术,提升全产品线的运维智能化水平。