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Active Optimal Dispatch of Microgrid Based on Improved Model Predictive Control

机译:基于改进模型预测控制的微电网主动最优调度

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In order to cope with the uncertainty of intermittent distributed power supply output in the microgrid, and to solve the problem that the prediction accuracy is declining with the increase of time scale, this paper uses deep learning technology to achieve accurate prediction of new energy output. Based on this, an optimal dispatch of micro-grid based on model predictive control is proposed to fine-tune the coordination and control of wind power, photovoltaic and energy storage equipment in the microgrid so as to maximize the dissipation of the intermittent distributed power supply and track the microgrid operation reference trajectories accurately.
机译:为了解决微电网中间歇性分布式电源输出的不确定性,并解决了随着时间尺度的增加,预测精度下降的问题,本文采用深度学习技术对新能源输出进行了准确的预测。在此基础上,提出了一种基于模型预测控制的微电网最优调度,以微调微电网中风电,光伏和储能设备的协调控制,以最大程度地减少间歇式分布式电源的耗散。并精确跟踪微电网运行参考轨迹。

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