Zhendong Zhang , Hui Qin , Jie Li , Yongqi Liu , Liqiang Yao , Yongqiang Wang , Chao Wang , Shaoqian Pei , Jianzhong Zhou
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引用次数: 45
Abstract
Due to the deterioration of non-renewable energy resources, the operation of wind-solar-hydro hybrid systems has become a prominent research topic. However, owing to the uncertainties in such a hybrid system, such as those in wind speed, solar radiation intensity, and power load, it is difficult for a dispatcher to develop the power generation plan of the day following the planning day (referred hereafter as the next day). The purpose of this study is to consider the uncertainties in a short-term optimal operation model and obtain for each state variable, the probability density function of the operation process of the next day. The latter can provide a dispatcher with a large amount of reliable decision reference information. In this study, simulation-estimation method is proposed to characterize the uncertainty and estimate the probability density function of the operation process. First, three short-term optimal operation models are established to provide flexible options to dispatchers. Second, a stochastic simulation method based on probabilistic forecasting is proposed to generate simulation scenarios for the next day. Third, each simulation scenario is input into the constructed optimal operation model for obtaining the solution. Fourth, the kernel density estimation method is used to estimate the probability density function of the operation process of the next day. Finally, the constructed optimal operation model and proposed simulation-estimation method are applied to the wind-solar-hydro Experimental Base of the Yalong river basin in China. In this case, the differences between the three operation models in three typical seasons are compared. Based on the verification of the prediction mean scenario and observation scenario, the experimental results show that the proposed model and method of this study are practical and effective.
期刊介绍:
The journal Energy Conversion and Management provides a forum for publishing original contributions and comprehensive technical review articles of interdisciplinary and original research on all important energy topics.
The topics considered include energy generation, utilization, conversion, storage, transmission, conservation, management and sustainability. These topics typically involve various types of energy such as mechanical, thermal, nuclear, chemical, electromagnetic, magnetic and electric. These energy types cover all known energy resources, including renewable resources (e.g., solar, bio, hydro, wind, geothermal and ocean energy), fossil fuels and nuclear resources.