城市取水风险理论及优化方法研究
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摘要
取水可靠性是城市供水安全的重要保障,基于风险分析的取水优化方法不仅能提高供水系统的安全,而且可节省大量的工程投资和日常运行费用,因此具有安全性和经济性双重意义。城市取水工程涉及了市政工程、水利和环境等多学科交叉,包括的内容多、范围广,目前尚没有系统的风险分析理论和优化方法指导工程设计及运行管理,因此有必要对取水的水质、泵站的风险理论及优化方法进行深入系统地研究。在广泛查阅国内外文献的基础上,本文进行了如下几个方面的研究工作:
(1)针对河流水质模型参数最小二乘(LS)估计方法关于有色噪声和较高水平白噪声干扰不具鲁棒性,噪声干扰使估计参数“漂离”系统真值,本文提出了一种水质模型参数的鲁棒估计方法——基于M-估计的估计方法,采用信赖域算法对估值模型进行求解。仿真试验表明,M-估计对于有色噪声和白噪声干扰具有鲁棒性,且估值精度、收敛性、抗噪性均优于LS估计。当河流水质监测数据序列较长时,采用小波消噪对监测数据进行预处理,仿真结果表明,小波消噪可消除随机噪声对水质模型参数估计的干扰,并能从监测数据分离出随机噪声,估计其噪声水平,为确定M-估计的阀值提供依据。
(2)分析了影响水环境水质风险的不完善性和模糊性因素,提出了河流水质超标的模糊随机风险率计算模型。计算结果表明,将河流水质系统的不确定性归结为随机性,是不合理的,模糊风险率模型的计算结果与实际情况基本吻合。采用二种水质模糊安全状态定义对水质超标模糊风险率进行了计算,结果表明定义形式没有本质区别。引入了模糊事件信息熵评价隶属函数特征值取值的可靠程度,定量描述了隶属函数特征值与风险率的关系,提高了特征值的计算精度。
(3)现行取水泵站的设计和调度方法使取水泵站存在很高的电机超载和泵站过流风险率。本文分析了取水泵站的工况特点及其影响因素,根据江河水位的变幅及其概率分布,建立了取水泵站运行过程中机组电机过载和泵站过流模糊随机风险率计算模型,计算结果与实际吻合,可为取水泵站的优化设计、科学调度提供科学的决策依据。
(4)本文引入水污染控制总成本概念提出了多目标水质规划优化模型,以河流排放口的污水处理费用最小和水污染经济损失最小为优化目标。采用连续函数模拟退火算法对优化模型求解,提高了运算效率和稳定性。基于水质超标模糊风险率的水污染经济损失计量模型可将水质风险转化为经济损失,既考虑水质系统中的不确定性因素和水质风险性,又兼顾了河流水质规划经济性,使规划方案更
Safety of municipal water supply depends on reliability of water intake resources and works. Carrying out optimization of water intake resources and works based on risk analysis is very significant, not only improving reliability of water supply systems, but also saving construction investment and operation cost. Municipal water intake engineering, involving in mult1-sciences and engineering such as water resource management, environmental science and water engineering, has very extensive contents. However, nowadays there is not systemic risk analysis and optimization method being used in design and operation management of the municipal water intake engineering. It is necessary to further strengthen systemic theoretical research on risk analysis and optimization of municipal water intake engineering. After reviewing references, the following aspects are thus studied in this dissertation:
1. Least squares (LS) estimation of water quality model parameters is not robust in case of occurring colored noises and high-level white noises, since the random noises drift the estimated parameters away from their true values. Based on M-estimation, a robust identification method for water quality model parameters was proposed, using trust region algorithm to solve parameter estimation model. The calculation results indicated that M-estimation has strong robustness to overcome the disturbance of noises, and comparison between the LS estimation and M-estimation further demonstrated that trust region algorithm based on M-estimation possessed high accuracy, excellent performance against noises and strong robustness as well as uniform convergent, which is obviously superior to LS estimation. In case of long serial data of water quality, the data was pre-treated using wavelet de-noise. Simulation results showed that wavelet de-noise did minimize the noises disturbance and estimated noise level in which aided to determine range of M- estimation.
2. Both the imperfection and fuzziness which affecting water environmental quality were analyzed according to the fuzzy and random uncertainties in the systems of water environment. A method of fuzzy-stochastic risk for water quality risk analysis in water environment was proposed based on the fuzzy probability theory. The results of calculation are consistent with the facts and uncertainties of river water quality can not be considered stochastic. The risk rate of concentrations exceeding the threshold was calculated using two kinds of definition of fuzzy safety conditions and results showed that the two definitions are the same in essence. The theory of entropy was introduced to assess the credibility of selecting the characteristic value of the membership function, and the numeric calculation on fuzzy degree of risk was carried
(1)针对河流水质模型参数最小二乘(LS)估计方法关于有色噪声和较高水平白噪声干扰不具鲁棒性,噪声干扰使估计参数“漂离”系统真值,本文提出了一种水质模型参数的鲁棒估计方法——基于M-估计的估计方法,采用信赖域算法对估值模型进行求解。仿真试验表明,M-估计对于有色噪声和白噪声干扰具有鲁棒性,且估值精度、收敛性、抗噪性均优于LS估计。当河流水质监测数据序列较长时,采用小波消噪对监测数据进行预处理,仿真结果表明,小波消噪可消除随机噪声对水质模型参数估计的干扰,并能从监测数据分离出随机噪声,估计其噪声水平,为确定M-估计的阀值提供依据。
(2)分析了影响水环境水质风险的不完善性和模糊性因素,提出了河流水质超标的模糊随机风险率计算模型。计算结果表明,将河流水质系统的不确定性归结为随机性,是不合理的,模糊风险率模型的计算结果与实际情况基本吻合。采用二种水质模糊安全状态定义对水质超标模糊风险率进行了计算,结果表明定义形式没有本质区别。引入了模糊事件信息熵评价隶属函数特征值取值的可靠程度,定量描述了隶属函数特征值与风险率的关系,提高了特征值的计算精度。
(3)现行取水泵站的设计和调度方法使取水泵站存在很高的电机超载和泵站过流风险率。本文分析了取水泵站的工况特点及其影响因素,根据江河水位的变幅及其概率分布,建立了取水泵站运行过程中机组电机过载和泵站过流模糊随机风险率计算模型,计算结果与实际吻合,可为取水泵站的优化设计、科学调度提供科学的决策依据。
(4)本文引入水污染控制总成本概念提出了多目标水质规划优化模型,以河流排放口的污水处理费用最小和水污染经济损失最小为优化目标。采用连续函数模拟退火算法对优化模型求解,提高了运算效率和稳定性。基于水质超标模糊风险率的水污染经济损失计量模型可将水质风险转化为经济损失,既考虑水质系统中的不确定性因素和水质风险性,又兼顾了河流水质规划经济性,使规划方案更
Safety of municipal water supply depends on reliability of water intake resources and works. Carrying out optimization of water intake resources and works based on risk analysis is very significant, not only improving reliability of water supply systems, but also saving construction investment and operation cost. Municipal water intake engineering, involving in mult1-sciences and engineering such as water resource management, environmental science and water engineering, has very extensive contents. However, nowadays there is not systemic risk analysis and optimization method being used in design and operation management of the municipal water intake engineering. It is necessary to further strengthen systemic theoretical research on risk analysis and optimization of municipal water intake engineering. After reviewing references, the following aspects are thus studied in this dissertation:
1. Least squares (LS) estimation of water quality model parameters is not robust in case of occurring colored noises and high-level white noises, since the random noises drift the estimated parameters away from their true values. Based on M-estimation, a robust identification method for water quality model parameters was proposed, using trust region algorithm to solve parameter estimation model. The calculation results indicated that M-estimation has strong robustness to overcome the disturbance of noises, and comparison between the LS estimation and M-estimation further demonstrated that trust region algorithm based on M-estimation possessed high accuracy, excellent performance against noises and strong robustness as well as uniform convergent, which is obviously superior to LS estimation. In case of long serial data of water quality, the data was pre-treated using wavelet de-noise. Simulation results showed that wavelet de-noise did minimize the noises disturbance and estimated noise level in which aided to determine range of M- estimation.
2. Both the imperfection and fuzziness which affecting water environmental quality were analyzed according to the fuzzy and random uncertainties in the systems of water environment. A method of fuzzy-stochastic risk for water quality risk analysis in water environment was proposed based on the fuzzy probability theory. The results of calculation are consistent with the facts and uncertainties of river water quality can not be considered stochastic. The risk rate of concentrations exceeding the threshold was calculated using two kinds of definition of fuzzy safety conditions and results showed that the two definitions are the same in essence. The theory of entropy was introduced to assess the credibility of selecting the characteristic value of the membership function, and the numeric calculation on fuzzy degree of risk was carried
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