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Day-ahead stochastic coordinated scheduling for thermal-hydro-wind-photovoltaic systems

机译:热-水-风-光伏发电系统的日前随机协调调度

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With the rapid development of electric power industry, the problem of dispatching renewable energy resources attracts worldwide attention. This paper presents a stochastic scheduling model to study the day-ahead coordination of a multi-source power system. The proposed stochastic scheduling model aims to find a base-case solution with relatively stable operation cost in the presence of uncertain renewable generation. Wind and photovoltaic generation uncertainties are modeled as scenarios using the Monte Carlo simulation method. Considering that wind and photovoltaic generations present complementary characteristics, scenarios are generated with correlations between wind and photovoltaic generations by Copula theory. To better reflect the characteristics of historical wind data, the fluctuation of wind power is also considered when scenarios are generated. The fast scenario reduction method is applied as a tradeoff between accuracy and computational speed. Numerical simulations indicate the effectiveness of the proposed approach in the coordinated scheduling of Thermal-Hydro-Wind- Photovoltaic systems. (C) 2019 Elsevier Ltd. All rights reserved.
机译:随着电力工业的飞速发展,可再生能源的调度问题引起了全世界的关注。本文提出了一种随机调度模型来研究多源电力系统的日前协调。所提出的随机调度模型的目的是在存在不确定的可再生能源发电的情况下,找到一种运行成本相对稳定的基本方案。使用蒙特卡洛模拟方法将风能和光伏发电的不确定性建模为情景。考虑到风能和光伏发电具有互补性,根据Copula理论,产生了风能和光伏发电之间具有相关性的情景。为了更好地反映历史风能数据的特征,在生成情景时还要考虑风能的波动。快速场景减少方法被应用为精度和计算速度之间的折衷。数值模拟表明,该方法在热风水光伏系统协调调度中的有效性。 (C)2019 Elsevier Ltd.保留所有权利。

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