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contributor authorPing He
contributor authorHaoran Jin
contributor authorZhiwen Pan
contributor authorLei Yun
contributor authorFushuan Wen
contributor authorHua Yang
contributor authorYukun Tao
date accessioned2023-08-16T19:12:11Z
date available2023-08-16T19:12:11Z
date issued2023/06/01
identifier otherJLEED9.EYENG-4927.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4292928
description abstractTo address the challenges of integrating ever-increasing renewable energy generation such as wind power and photovoltaic (PV) to the power system concerned, the wind-PV-thermal-bundled (WPTB) transmission mode could be employed to mitigate the intermittent power output from wind and PV units. In this work, based on the mathematical models of thermal generation units, wind turbines and PV units, the WPTB transmission system model is developed. Each load demand is modeled as a random variable under various operating conditions of the concerned power system. The Lyapunov linearization method is used to obtain the system matrix of each operation mode, and then all eigenvalues of the system can be attained. According to the generator participation factor, the oscillation modes of the power system are classified. The eigenvalue and damping ratio of each oscillation mode are employed to formulate the objective function of the optimal strategy for enhancing probabilistic small-signal stability, and the particle swarm optimization algorithm is used for global optimization. The secure operation of the power system can be ensured in a wider range by the designed optimization strategy in this work. The effectiveness of the method is demonstrated by simulation results of a sample power system which can operate stably under some uncertain operation conditions.
publisherAmerican Society of Civil Engineers
titleOptimal Strategy for Enhancing Probabilistic Small-Signal Stability in a Power System with Wind-PV-Thermal Bundled Transmission
typeJournal Article
journal volume149
journal issue3
journal titleJournal of Energy Engineering
identifier doi10.1061/JLEED9.EYENG-4927
journal fristpage04023014-1
journal lastpage04023014-13
page13
treeJournal of Energy Engineering:;2023:;Volume ( 149 ):;issue: 003
contenttypeFulltext


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