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dc.contributor.authorPing He
dc.contributor.authorHaoran Jin
dc.contributor.authorZhiwen Pan
dc.contributor.authorLei Yun
dc.contributor.authorFushuan Wen
dc.contributor.authorHua Yang
dc.contributor.authorYukun Tao
dc.date.accessioned2023-08-16T19:12:11Z
dc.date.available2023-08-16T19:12:11Z
dc.date.issued2023/06/01
dc.identifier.otherJLEED9.EYENG-4927.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4292928
dc.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.
dc.publisherAmerican Society of Civil Engineers
dc.titleOptimal Strategy for Enhancing Probabilistic Small-Signal Stability in a Power System with Wind-PV-Thermal Bundled Transmission
dc.typeJournal Article
dc.journal.volume149
dc.journal.issue3
dc.journal.titleJournal of Energy Engineering
dc.identifier.doi10.1061/JLEED9.EYENG-4927
dc.journal.fristpage04023014-1
dc.journal.lastpage04023014-13
dc.page13
dc.treeJournal of Energy Engineering:;2023:;Volume ( 149 ):;issue: 003
dc.contenttypeFulltext


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