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Prediction of water-light output in water-light complementary systems

机译：水光互补系统中水光输出的预测

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With the increasing demand of electricity consumption for social development, China has vigorously promoted the development of renewable energy such as wind and solar energy in recent years. Since photovoltaic power generation has the characteristics of randomness, intermittency and volatility, which are not conducive to dispatching and grid-connection, and hydroelectric power generation has the characteristics of fast start-up and good peak adjustment, etc. Therefore, through the study of multiple linear regression model neural network prediction model Markov chain and other methods, the hydraulic resource output prediction model and photovoltaic resource output prediction model are built. The combination of the two can be used to predict the output of water and light resources more accurately and promote the development of water and light complementary industry in China. At present, there are few researches on the coupling of hydroelectric output and photovoltaic output at home and abroad. In this paper, the prediction of water-light output in water-light complementary systems by other scholars is reviewed.
机译：随着社会发展的电力消费需求日益增加，中国近年来大力推动了风能和太阳能等可再生能源的发展。由于光伏发电具有随机性，间歇性和波动性的特点，这不利于调度和网格连接，并且水电发电具有快速启动和良好的峰值调整等特征，因此通过研究多线性回归模型神经网络预测模型Markov链和其他方法，构建了液压资源输出预测模型和光伏资源输出预测模型。两者的组合可用于更准确地预测水和光源的产量，促进中国水和轻互补行业的发展。目前，对国内外水电输出和光伏产量的耦合尤为近几季。本文综述了其他学者用水光补充系统中的水光输出预测。

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