【作者】 苏学灵；

【导师】 纪昌明；

【作者基本信息】 华北电力大学（北京） ， 管理科学与工程， 2010， 博士

【摘要】 改善电源结构,充分利用可再生能源,加快蓄能水电站建设,提高蓄能水电站的运行管理水平,对构建资源节约型和环境友好型社会及推动电力工业可持续发展具有重要作用。本文以混合式蓄能水电站为研究对象,从优化调度算法、风险分析方法、中长期优化调度、实时调度、调度风险分析和评价等不同角度深入探讨了电站的优化调度管理问题,并取得了如下主要成果：(1)混合式蓄能水电站的优化调度是一个多阶段、非线性和组合性的问题,针对目前采用的基本粒子群算法在求解时存在易陷入局部最优和早熟的缺点,提出以随机动态改变惯性权重机制来选取惯性权重因子、以混沌变量生成机制增加粒子的多样性、以逐步优化和随机生成相结合增加粒子生成的有效性的改进粒子群算法(APSO)进行求解,为混合式蓄能水电站的优化调度提供了一种有效的方法。(2)针对目前水库调度运行管理实际,基于事件与事件的目标,即事件发生的途径空间和目标空间是可变的思想,提出了概率最优化风险分析方法(POMR),深入地刻画出风险与效益的对立关系,为调度人员的决策提供了基础理论方法。(3)针对发电量最大和调峰效益最大、上库和下库联合调度,存在着多维、多阶段和多约束条件等具有高度复杂性的问题,建立了混合式蓄能水电站中长期优化调度模型,并采用APSO求解。实例研究证明了所建模型的合理性和算法的有效性,所建模型对解决混合式蓄能水电站中长期优化调度运行管理问题具有重要的理论价值和广阔的应用前景。(4)建立了基于调度函数的混合式蓄能水电站实时调度模型。把时间、空间和能量因子作为待选变量,提出用逐步回归原理建立混合式蓄能水电站的调度函数。在考虑电站自身发电、综合利用及电站出力等约束的基础上,采用调度函数对某混合式蓄能水电站进行实际运行模拟,并对模拟结果与优化调度结果进行了对比。结果表明调度函数基本保留了优化调度方案的成果和效益,同时具有良好的可操作性和解释性,为混合式蓄能水电站寻找调度规律、拟定运行方案提供了一种新的方法。(5)在构建发电调度风险评价指标体系的基础上,运用不确定性理论和POMR方法建立了混合式蓄能水电站调度风险分析的期望值模型,并给出简便实用的求解方法。实例应用表明,该模型实现了水库在承担一定风险的情况下,可以追求电站效益的最大化,并通过灵敏度分析建立目标空间与因子空间的关系,达到通过控制风险因子改善较优可行方案的目的,对调度方案决策具有重要指导意义。(6)针对围堰漫堰的主要风险因子,建立了基于POMR方法的围堰漫堰风险分析模型,并把此模型应用于向家坝水文站一期围堰漫堰风险计算。在对横江洪水特点和顶托分析的基础上,采用3层BP神经网络对向家坝水文站水位变化进行预测,探讨了汛期横江洪水入流对向家坝一期围堰河段水位的顶托影响,并建立了向家坝一期围堰漫堰风险模型,为管理决策人员提供了汛期围堰安全度汛的依据。更多还原

【Abstract】 It is very important to improve the power source structure, make full use of renewable energy and enhance the operation and management level of pumped-storage power stations for constructing a resource-saving and environment-friendly society and sustainable development of power industry. The operation and management of mixed storage power station are further discussed by adopting different ways such as the optimal scheduling algorithm, risk analysis and evaluation, long-term optimal scheduling, real-time scheduling, etc. in this paper. The conclusions are as follows:(1) In order to solve multi-stage, non-linear and other difficult problems of optimal operation of mixed storage power station, a novel and efficiency algorithm, Advanced Particle Swarm Optimization (APSO) is presented in the thesis. The mechanism of random dynamically changing inertia weight and the generation mechanism of chaotic variables are introduced to increase the diversity of particles which can avoid the local optimization and premature of the PSO algorithm.(2) Based on events and their goals, in another way, the way space and target space can be changed when events have happened, Probability Optimization Method for the Risk Calculating (POMR) which discusses the antagonistic relationship between risks and benefits is proposed after analyzing the actual operation and management of reservoirs. And this antagonistic relationship is very important when dispatchers make the decision.(3) The long-term optimal scheduling model of mixed storage power station is constructed to solve the complex problems, for instance, the Multi-constrained, multi-stage and non-linear in the joint reservoir operation and energy maximization.(4) The real-time scheduling model of storage power station based on the scheduling function is founded. Time, space and energy factor are variables to be elected in this scheduling function which is design by using regression theory. Taking all the aspects into account, this paper compares the simulation results calculated by the scheduling function with the optimal scheduling results. The results show that the model based on the scheduling function can receive better plan and provide a new approach for the operation of mixed storage power station.(5) In the base of risk evaluation index system for generation scheduling, expectations model for risk analysis of mixed storage power station is established by using the POMR methods and uncertainty theory, and simple and practical solution method is presented. The applications show that the model can pursue the maximal efficiency of power plant in a certain risk circumstances, and establish the relationship between target space and factor space through sensitivity analysis also can improve the operation by controlling the risk factors. So this model is significant for making the operation scheduling.(6) Risk analysis model of cofferdam based on the POMR method which is adopted to solve the risk factors is proposed in this paper. It has been applied to calculate the risk in the first cofferdam of Xiangjiaba Hydrometric. After analysis the flood features and the backwater of hengjiang, three-layer BP neural network is used predict the water level of Xiangjiaba Hydrometric. Then the influence of the hengjiang inflow to the first cofferdam of Xiangjiaba also discussed. The risk model of the first cofferdam of Xiangjiaba is also established. This provids the basis for the flood season cofferdam security for managers decision-making.更多还原