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    Wyświetlanie 1-3 z 3
    Tytuł:
    Multiobjective Improved Particle Swarm Optimisation for Transmission Congestion and Voltage Profile Management using Multilevel UPFC
    Autorzy:
    Rao, Mallavolu Malleswara
    Ramadas, Geetha
    Powiązania:
    https://bibliotekanauki.pl/articles/1193696.pdf
    Data publikacji:
    2019
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    congestion
    unified power flow controller
    improved particle swarm optimization
    modular multilevel converter
    voltage profile
    Opis:
    This paper proposes a multiobjective improved particle swarm optimisation (IPSO) for placing and sizing the series modular multilevel converter-based unified power flow controller (MMC-UPFC) FACTS devices to manage the transmission congestion and voltage profile in deregulated electricity markets. The proposed multiobjective IPSO algorithm is perfect for accomplishing the close ideal distributed generation (DG) sizes while conveying smooth assembly qualities contrasted with another existing algorithm. It tends to be reasoned that voltage profile and genuine power misfortunes have generous upgrades along ideal speculation on DGs in both the test frameworks. The proposed system eliminates the congestion and the power system can be easily used to solve complex and non-linear optimisation problems in a real-time manner.
    Źródło:
    Power Electronics and Drives; 2019, 4, 39; 79-93
    2451-0262
    2543-4292
    Pojawia się w:
    Power Electronics and Drives
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Novel Fuzzy-Based Self-Adaptive Single Neuron PID Load Frequency Controller for Power System
    Autorzy:
    Eissa, M. Abdullah
    Powiązania:
    https://bibliotekanauki.pl/articles/1193688.pdf
    Data publikacji:
    2019
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    power system
    load frequency
    Intelligent Control
    PID
    Single Neuron
    Opis:
    This paper proposes a newly adaptive single-neuron proportional integral derivative (SNPID) controller that uses fuzzy logic as an adaptive system. The main problem of the classical controller is lacking the required robustness against disturbers, measurement noise in industrial applications. The new formula of the proposed controller helps in fixing this problem based on the fuzzy logic technique. In addition, the genetic algorithm (GA) is used to optimize parameters of the SNPID controller. Because of the high demands on the availability and efficiency of electrical power production, the design of robust load-frequency controller is becoming increasingly important due to its potential in increasing the reliability, maintainability and safety of power systems. So, the proposed controller has been applied for load-frequency control (LFC) of a single-area power system. The effectiveness of the proposed SNPID controller has been compared with the conventional controllers. The simulation results show that the proposed controller approach provides better damping of oscillations with a smaller settling time. This confirms its superiority against its counterparts. In addition, the results show the robustness of the proposed controller against the parametric variation of the system.
    Źródło:
    Power Electronics and Drives; 2019, 4, 39; 141-150
    2451-0262
    2543-4292
    Pojawia się w:
    Power Electronics and Drives
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Application of artificial bee colony algorithm to auto-tuning of state feedback controller for DC-DC power converter
    Autorzy:
    Tarczewski, T.
    Niewiara, Ł. J.
    Grzesiak, L M.
    Powiązania:
    https://bibliotekanauki.pl/articles/1193254.pdf
    Data publikacji:
    2016
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    artificial bee colony algorithm
    state feedback controller
    DC-DC power converter
    SiC MOSFET
    Opis:
    The article presents an auto-tuning method of state feedback voltage controller for DC-DC power converter. The penalty matrices employed for calculation of controller’s coefficients were obtained by using nature-inspired artificial bee colony (ABC) optimization algorithm. This overcomes the main drawback of state feedback control related to time-consuming trial-and-error tuning procedure. The optimization algorithm takes into account constraints of selected state and control variables of DC-DC power converter. In order to meet all control objectives (i.e., fast voltage response and chattering-free control signal) an appropriate performance index is proposed. Proper selection of state feedback controller (SFC) coefficients is proven by simulation and experimental tests of DC-DC power converter.
    Źródło:
    Power Electronics and Drives; 2016, 1, 36/2; 83-96
    2451-0262
    2543-4292
    Pojawia się w:
    Power Electronics and Drives
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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