A Morphing-Based Future Scenario Generation Method for Stochastic Power System Analysis

Yanna Gao, Hong Dong, Liujun Hu, Zihan Lin, Fanhong Zeng, Cantao Ye () and Jixiang Zhang
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Yanna Gao: Guangzhou Power Supply Bureau, Guangdong Power Grid Co., Ltd., Guangzhou 510620, China
Hong Dong: Guangzhou Power Supply Bureau, Guangdong Power Grid Co., Ltd., Guangzhou 510620, China
Liujun Hu: Guangzhou Power Supply Bureau, Guangdong Power Grid Co., Ltd., Guangzhou 510620, China
Zihan Lin: Guangzhou Power Supply Bureau, Guangdong Power Grid Co., Ltd., Guangzhou 510620, China
Fanhong Zeng: Guangzhou Power Supply Bureau, Guangdong Power Grid Co., Ltd., Guangzhou 510620, China
Cantao Ye: Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China
Jixiang Zhang: Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China

Sustainability, 2024, vol. 16, issue 7, 1-21

Abstract: As multiple wind and solar photovoltaic farms are integrated into power systems, precise scenario generation becomes challenging due to the interdependence of power generation and future climate change. Future climate data derived from obsolete climate models, featuring diminished accuracy, less-refined spatial resolution, and a limited range of climate scenarios compared to more recent models, are still in use. In this paper, a morphing-based approach is proposed for generating future scenarios, incorporating the interdependence of power generation among multiple wind and photovoltaic farms using copula theory. The K-means method was employed for scenario generation. The results of our study indicate that the average annual variations in dry-bulb temperature (DBT), global horizontal irradiance (GHI), and wind speed (WS) are projected to increase by approximately 0.4 to 1.9 °C, 7.5 to 20.4 W/m 2 , and 0.3 to 1.7 m/s, respectively, in the forthcoming scenarios of the four considered Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). It seems that accumulated maximum wind electricity output (WEO) and solar electricity output (SEO) will increase from 0.9% to 7.3% and 1.1% to 6.8%, respectively, in 2050.

Keywords: future scenario; weather morphing; climate change; cluster analysis; uncertainties (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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