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  • Open Access

    ARTICLE

    Research on Reactive Power Optimization of Offshore Wind Farms Based on Improved Particle Swarm Optimization

    Zhonghao Qian1, Hanyi Ma1, Jun Rao2, Jun Hu1, Lichengzi Yu2,*, Caoyi Feng1, Yunxu Qiu1, Kemo Ding1

    Energy Engineering, Vol.120, No.9, pp. 2013-2027, 2023, DOI:10.32604/ee.2023.028859

    Abstract The lack of reactive power in offshore wind farms will affect the voltage stability and power transmission quality of wind farms. To improve the voltage stability and reactive power economy of wind farms, the improved particle swarm optimization is used to optimize the reactive power planning in wind farms. First, the power flow of offshore wind farms is modeled, analyzed and calculated. To improve the global search ability and local optimization ability of particle swarm optimization, the improved particle swarm optimization adopts the adaptive inertia weight and asynchronous learning factor. Taking the minimum active power loss of the offshore wind… More >

  • Open Access

    ARTICLE

    Reactive Power Flow Convergence Adjustment Based on Deep Reinforcement Learning

    Wei Zhang1, Bin Ji2, Ping He1, Nanqin Wang1, Yuwei Wang1, Mengzhe Zhang2,*

    Energy Engineering, Vol.120, No.9, pp. 2177-2192, 2023, DOI:10.32604/ee.2023.026504

    Abstract Power flow calculation is the basis of power grid planning and many system analysis tasks require convergent power flow conditions. To address the unsolvable power flow problem caused by the reactive power imbalance, a method for adjusting reactive power flow convergence based on deep reinforcement learning is proposed. The deep reinforcement learning method takes switching parallel reactive compensation as the action space and sets the reward value based on the power flow convergence and reactive power adjustment. For the non-convergence power flow, the 500 kV nodes with reactive power compensation devices on the low-voltage side are converted into PV nodes… More >

  • Open Access

    ARTICLE

    A New Framework for Employing Responsive End-Users Using FAHP and PSO Algorithm

    Reza Etemad1, Mohammad Sadegh Ghazizadeh1, Mehrdad Ahmadi Kamarposhti2,*, Ilhami Colak3, Kei Eguchi4

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 951-964, 2023, DOI:10.32604/cmc.2023.032631

    Abstract The capacitor bank and synchronous condenser have been the only available sources of reactive power. Nowadays, most of the appliances use a power electronic interface for their connection. Applying a power electronic interface adds many features to these appliances. One of the promising features is their capability to interact with Volt-VAR programs. In this paper was investigated the reactive power interaction of the end-user appliances. For this purpose, the distribution network buses are ranked based on their effectiveness, followed by studying their interaction in the Volt-VAR program. To be able to consider the uncertainties, Probability Density Function (PDF) curve was… More >

  • Open Access

    ARTICLE

    Enhancement of Large Renewable Distributed Generation Penetration Levels at the Point of Common Coupling

    Akinyemi Ayodeji Stephen*, Kabeya Musasa, Innocent Ewean Davidson

    Energy Engineering, Vol.119, No.6, pp. 2711-2744, 2022, DOI:10.32604/ee.2022.023069

    Abstract The occurrence of distortion and over voltage at the Point of Common Coupling (PCC) of Renewable Distributed Generation (RDG) limits its penetration levels to the power system and the RDG integration is expected to play a crucial role in power system transformation. For its penetrations to be sustained without disconnection from the system, there must be a solution to the voltage rise, distortion, unbalanced current and grid reactive power control strategy at PCC. It is an IEEE-1547 requirement that RDG integration to the power system should be regulated at PCC to avoid disconnection from the network due to power quality… More > Graphic Abstract

    Enhancement of Large Renewable Distributed Generation Penetration Levels at the Point of Common Coupling

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