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Probabilistic small signal stability analysis of power system with wind power and photovoltaic power based on probability collocation method

Cai Yan, Linli Zhou, Wei Yao and 2 more

Global Energy Interconnection · 2019

doi:10.1016/j.gloei.2019.06.003 (opens in a new tab)

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Abstract

Recently, with increasing improvements in the penetration of wind power and photovoltaic power in the world, probabilistic small signal stability analysis (PSSSA) of a power system consisting of multiple types of renewable energy has become a key problem. To address this problem, this study proposes a probabilistic collocation method (PCM)-based PSSSA for a power system consisting of wind farms and photovoltaic farms. Compared with the conventional Monte Carlo method, the proposed method meets the accuracy and precision requirements and greatly reduces the computation; therefore, it is suitable for the PSSSA of this power system. Case studies are conducted based on a 4-machine 2-area and New England systems, respectively. The simulation results show that, by reducing synchronous generator output to improve the penetration of renewable energy, the probabilistic small signal stability (PSSS) of the system is enhanced. Conversely, by removing part of the synchronous generators to improve the penetration of renewable energy, the PSSS of the system may be either enhanced or deteriorated. Keywords: Renewable energy, Probabilistic small signal stability, Probabilistic collocation method, Wind power, Photovoltaic power

Abstract licence: CC BY-NC-ND

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