光伏系统
平滑的
储能
计算机科学
最大功率点跟踪
太阳能
独立电源系统
光伏并网发电系统
电子工程
控制理论(社会学)
功率(物理)
工程类
汽车工程
电气工程
电压
分布式发电
可再生能源
控制(管理)
物理
人工智能
量子力学
计算机视觉
逆变器
作者
Miswar Akhtar Syed,Muhammad Khalid
标识
DOI:10.1109/powertech46648.2021.9494831
摘要
The increase in energy demand needs to be met with environmentally friendly resources to lower the production of greenhouse gases. Solar power is a popular choice as it is available in abundance and is relatively cheap. However, the large-scale penetration of intermittent solar Photovoltaic (PV) power causes multiple instabilities in the grid such as frequency issues and voltage deviations. To counteract these instabilities, Battery Energy Storage System (BESS) is integrated in the grid as it reduces the PV fluctuations and promotes optimal operation. However, storage systems are expensive and thus smoothing filters are also coupled with the BESS for cost reduction and power smoothing. Traditional filters such as Low Pass Filters (LPF) and Moving Average (MA) filters are capable of solar power smoothing but have poor power tracking capabilities. To compensate for the delayed power tracking, larger energy storage systems are required which in turn adds to the operational costs. This paper proposes a locally weighted filter for solar PV smoothing with BESS. The proposed filter has significantly better power tracking capabilities than both the LPF and MA filters. Thus, as compared to the conventional LPF and MA filters, the proposed filter can achieve better solar power smoothing with reduced time delay and optimum battery storage capacity.
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