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Wind-Solar Power Consumption Strategy Based on Neural Network Prediction and Demand-side Response

机译:基于神经网络预测和需求侧响应的风光功率消耗策略

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Facilitated by the increasing capability of harnessing the natural resources, China’s use of renewable energy has been soaring. However, the phenomena of wind-solar power curtailment still exist, which brings serious challenge to power system economic operation. In this paper, a systemic technical strategy to the current renewable energy consumption problem, focusing on demand-side response and time-of-use electricity price based on neural network prediction, was proposed. Then the optimization and the proficiency have been analyzed. Finally, the effectiveness of the proposed strategy was verified through model simulation.
机译:在利用自然资源的能力日益增强的推动下,中国对可再生能源的使用猛增。但是,仍然存在风电限电的现象,给电力系统的经济运行带来了严峻的挑战。本文提出了一种针对当前可再生能源消费问题的系统技术策略,重点是基于神经网络预测的需求方响应和分时电价。然后分析了优化和熟练程度。最后,通过模型仿真验证了所提策略的有效性。

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