Stochastic Eigen-Analysis of Electric Power System With High Renewable Penetration: Impact of Changing Inertia on Oscillatory Modes
| Autor: | Gregor Verbic, Jae Woong Shim, Kyeon Hur |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
business.industry
020209 energy media_common.quotation_subject Energy Engineering and Power Technology 02 engineering and technology Inertia Wind speed Renewable energy Controllability Electric power system Modal Control theory 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering business Random variable Eigenvalues and eigenvectors Mathematics media_common |
| Zdroj: | IEEE Transactions on Power Systems. 35:4655-4665 |
| ISSN: | 1558-0679 0885-8950 |
| DOI: | 10.1109/tpwrs.2020.3000577 |
| Popis: | This article proposes a framework for stochastic eigenvalue analysis of electric power systems with a high penetration of inertialess renewable generation, focusing on the influential factors that affect the eigenvalue movement resulting from the inertia reduction. We analytically investigate the influence of the inertia and the variation in renewable generation on small-signal stability using stochastic Monte-Carlo based eigenvalue and modal controllability analysis. With the increasing penetration of renewable generation, power system behavior depends on meteorological conditions more, which results in the reduction of power system inertia due to the decommitment of generators and a consequent deterioration of power system stability. Against this backdrop, stochastic eigenvalue analysis is carried out to examine the movement of eigenvalues resulting from the variable operating conditions. The contribution of the generators to the oscillatory modes is theoretically proved using modal controllability in a power system with reduced inertia. For the verification of the research, the simulation is carried out using DIgSILENT/PowerFactory. |
| Databáze: | OpenAIRE |
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