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首页> 外文期刊>IEEE Transactions on Industrial Electronics >A neural-network-based controller for the cost-effective operation of a hybrid compensator for nonactive power
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A neural-network-based controller for the cost-effective operation of a hybrid compensator for nonactive power

机译：基于神经网络的控制器，用于无功功率混合补偿器的经济高效运行

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摘要

The need to eliminate distortion from power networks has led to the development of various compensator topologies. The increasing cost of electrical energy requires the choice of the most cost-effective compensator operation. An investigation of a neural-network-based controller that chooses the most cost-effective compensator mode of operation on the basis of a continuous analysis of load conditions and the operational losses of the elements in the compensator structure are reported. The modeling of operational losses of each subtopology and the required control strategy are discussed. The results show that the operational loss savings due to the neural-network-controlled hybrid compensator were 30%-70% as compared to the conventionally controlled hybrid compensator, while also conforming to other control strategy requirements.
机译：消除电力网络失真的需求导致了各种补偿器拓扑的发展。不断增加的电能成本要求选择最具成本效益的补偿器操作。报告了对基于神经网络的控制器的研究，该控制器在连续分析负载条件和补偿器结构中元件的操作损耗的基础上选择了最具成本效益的补偿器操作模式。讨论了每个子拓扑的操作损失建模和所需的控制策略。结果表明，与传统控制的混合补偿器相比，神经网络控制的混合补偿器可节省30％-70％的运行损耗，同时还符合其他控制策略要求。

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