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)
We email you when a new notice or a question about this paper appears.
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
References11
11 more references, whose wording the paper’s licence keeps private.
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.