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    Optimal Strategy for Enhancing Probabilistic Small-Signal Stability in a Power System with Wind-PV-Thermal Bundled Transmission

    Source: Journal of Energy Engineering:;2023:;Volume ( 149 ):;issue: 003::page 04023014-1
    Author:
    Ping He
    ,
    Haoran Jin
    ,
    Zhiwen Pan
    ,
    Lei Yun
    ,
    Fushuan Wen
    ,
    Hua Yang
    ,
    Yukun Tao
    DOI: 10.1061/JLEED9.EYENG-4927
    Publisher: American Society of Civil Engineers
    Abstract: To 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.
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      Optimal Strategy for Enhancing Probabilistic Small-Signal Stability in a Power System with Wind-PV-Thermal Bundled Transmission

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4292928
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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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