入库径流预报误差分析及在水库群短期发电调度中的应用

发布时间：2019-06-02 23:40

【摘要】：选取合适的分布形式对入库径流预报误差分布规律进行定量分析,并在此基础上开展水电站水库群短期发电调度风险估计工作,对于提高水电站水库群短期发电调度的经济效益具有重要的理论意义和实际应用价值。本文首先将贝叶斯、最大熵和马尔可夫链蒙特卡罗这三种方法的优点进行了有机结合,建立了基于马尔可夫链蒙特卡罗的贝叶斯最大熵(MBME)方法；其次,将MBME方法应用于入库径流预报误差的分析,建立了基于MBME方法的径流预报误差分布模型,将该模型应用于“锦官电源组”三个水库的入库径流误差分布规律的研究中,同时考虑流域径流年内丰枯变化对其分布规律的影响,得到了不同径流系列不同时期不同预见期的径流预报误差后验分布函数,并通过与先验分布、理论正态分布和误差样本直方图进行对比分析,验证了模型的合理性和可行性；最后,考虑到径流预报误差对水电站水库群短期发电调度的影响,利用风险率和机会损失对其风险进行定量估计,建立了考虑入库径流预报误差的水电站水库群短期发电调度风险估计模型,结合实例对考虑入库径流预报误差的水电站水库群短期发电调度的风险进行了估计与量化,为水库调度部门提供了重要的理论基础与决策依据。
[Abstract]:The error distribution law of runoff forecasting in reservoir is quantitatively analyzed by selecting the appropriate distribution form, and on this basis, the risk estimation of short-term power generation operation of hydropower station reservoir group is carried out. It has important theoretical significance and practical application value for improving the economic benefit of short-term power generation operation of hydropower station reservoir group. In this paper, the advantages of Bayesian, maximum entropy and Markov chain Monte Carlo are combined organically, and the Bayesian maximum entropy (MBME) method based on Markov chain Monte Carlo is established. Secondly, the MBME method is applied to the analysis of runoff forecasting error, and a runoff forecasting error distribution model based on MBME method is established. The model is applied to the study of the runoff error distribution law of three reservoirs in Jinguan Power supply Group. At the same time, considering the influence of abundant and dry variation of runoff on its distribution law, the posterior distribution function of runoff prediction error in different periods and different prediction periods of different runoff series is obtained, and the posterior distribution function of runoff prediction error is obtained by means of prior distribution. The theoretical normal distribution and the histogram of error samples are compared and analyzed, and the rationality and feasibility of the model are verified. Finally, considering the influence of runoff forecasting error on short-term power generation operation of hydropower station reservoir group, the risk is quantitatively estimated by using risk rate and opportunity loss. The risk estimation model of short-term power generation operation of hydropower station reservoir group considering the prediction error of reservoir runoff is established, and the risk of short-term power generation operation of hydropower station reservoir group considering the prediction error of reservoir runoff is estimated and quantified with an example. It provides an important theoretical basis and decision-making basis for reservoir operation departments.
【学位授予单位】：华北电力大学(北京)
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TV697.12

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