Multi-temporal-spatial Scale Capacity Credit Assessment Method for Wind-photovoltaic-storage Systems

被引：0

作者：

Wang, Renshun ^{[1
]}

Wang, Shilong ^{[1
]}

Geng, Guangchao ^{[1
]}

Jiang, Quanyuan ^{[1
]}

Liu, Chun ^{[2
]}

Wang, Bo ^{[2
]}

机构：

[1] College of Electrical Engineering, Zhejiang University, Hangzhou

[2] National Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing

来源：

Gaodianya Jishu/High Voltage Engineering | 2024年 / 50卷 / 09期

关键词：

capacity credit; inter-provincial and inter-regional; multiple temporal-spatial scales; power supply capability; reliability assessment; wind-photovoltaic-storage systems;

D O I：

10.13336/j.1003-6520.hve.20240128

中图分类号：

学科分类号：

摘要：

The renewable energy is gradually transited into the main power supply and inter-provincial and inter-regional power exchange, thus characterizing the power supply capability of wide-area renewable energy systems is of significant importance for ensuring reliable power supply. Energy storage can effectively mitigate the volatility of renewable and enhance their power supply capability. Capacity credit (CC) serves as a crucial index for characterizing power supply capability of renewable and storage. Therefore, this paper proposes a multi-temporal and multi-spatial CC evaluation framework and calculation method for inter-provincial and inter-regional wind-photovoltaic-storage systems. The CC evaluation is extended to short-term operational, medium-term operational, and planning time scales, so as to better support the power supply requirements in key scenarios. Furthermore, the proposed method is investigated for wind-photovoltaic farms, provincial grids, and inter-regional grids, enabling the characterization of power supply capability for multi-area wind-photovoltaic-storage. Additionally, an accelerating simulation algorithm considering temporal and spatial dimensions for CC assessment is proposed to enhance calculation efficiency in such systems. Case studies on the RTS-GMLC system verify the validation and efficiency of the proposed method. The results indicate that key scenarios with peak hours have a significant impact on the CC of renewable and storage systems, and the multi-area complementarity and storage integration can effectively enhance the CC of renewable energy. © 2024 Science Press. All rights reserved.

引用

页码：3904 / 3913

页数：9

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