分布式光伏与储能产业的政策与经济效益

Xiuming Niu, Xu-feng Luo
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引用次数: 0

摘要

利用光伏组件将太阳能直接转化为电能的技术是分布式光伏发电。它经常在一个系统中使用,被称为分布式光伏发电系统。该系统在周边地区发电,并连接到邻近的公用电网。分布式能源存储(DES)系统是一种捆绑解决方案,可以存储能源以供将来使用。在短期内,太阳能储能最重要的问题之一是用于应用的电池仍然昂贵且巨大。电量越大,电池就必须越大。进一步的研究表明,最大限度地利用太阳能和风能可以最大限度地减少温室气体排放,降低能源的总成本。储存能量的能力对平衡至关重要,因为它使电网更具适应性和稳定性。能源节约和能源储存(ECES)的使命旨在帮助整合能源储存技术的研究、生产、部署和整合,以提高所有能源系统的能源效率,并使可再生能源取代化石燃料的使用增加。在可再生能源能源波动期间,从配电变压器负荷和存储支持的角度考察了存储效益。然而,结果表明,该方法推荐的框架是成功的,并获得了提高的性能,可靠性为95.6%。改进后的模型可靠性分析比为95.4%,性能分析比较比为98.6%,准确率分析比为91.3%,模型效率估计为95.6%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Policies and Economic Efficiency for Distributed Photovoltaic and Energy Storage Industry
The technique of directly converting solar energy into electricity using PV modules is distributed photovoltaic (PV) power generation. It is frequently used in a system and is referred to as a distributed PV power system. The system generates power in the surrounding areas and connects to the neighbouring utility grid. A distributed energy storage (DES) system is a bundled solution that stores energy for future use. In the short term, one of the most significant problems with solar power storage is that the batteries utilized for the application are still costly and giant. The more power requires the bigger battery must be. Further research revealed that maximizing solar and wind energies minimizes greenhouse gas emissions and lower the total cost of energy. The ability to store energy is crucial in balancing because it makes the grid more adaptable and stable. The mission of energy conservation and energy storage (ECES) aims to help integrate energy-storage technology research, production, deployment, and integration to improve the energy efficiency of all energy systems and enable the increased use of renewable energy in place of fossil fuels. Storage benefits are examined in terms of distribution transformer loads and storage support during energy fluctuations from renewable energy. However, the results show that the methodology’s recommended framework is successful and obtained with enhanced performance with a reliability of 95.6%. The proposed technique improves the Reliability analysis ratio of 95.4%, Performance analysis comparison ratio of 98.6%, accuracy analysis ratio of 91.3%, ECES model’s efficiency is estimated at 95.6%.
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