含风电的电力系统备用决策及小扰动随机稳定分析

发布时间：2018-01-10 00:33

本文关键词：含风电的电力系统备用决策及小扰动随机稳定分析　出处：《华北电力大学》2014年博士论文　论文类型：学位论文

【摘要】：风力发电是开发利用可再生清洁能源的主要形式。大力发展风电对优化能源结构、实现能源供应多元化、应对气候变化、保护生态环境具有非常重要的意义。大规模、集中开发,远距离、高电压输送是我国风电发展的主要特征。与常规电源的可调可控相比,风电机组的调节能力弱且其出力具有随机波动性,大规模风电接入给电力系统的安全稳定运行带来很大影响。传统的基于确定性状态方程的稳定性分析方法在解决风电随机波动引发的稳定问题时受到局限,有必要借助随机微分方程和随机稳定理论对风电接入后的电力系统稳定性进行系统研究。而目前这方面的研究还很薄弱。本文针对风电随机性进入电力系统状态方程的不同层面,有针对性地对含风电电力系统的运行优化和小扰动随机稳定机理展开探索研究：针对风电不确定性给系统运行平衡点带来的影响,研究风电不确定性建模和含风电电力系统的备用和调度决策模型；以风电机组随机动态建模为突破口,基于随机微分方程理论研究随机激励和随机系数下的电力系统小扰动随机稳定性建模及分析方法。研究旨在将电力系统稳定性建模和分析方法拓展到随机空间下。具体的研究内容及成果如下： 1.基于场景法对风电功率的不确定性进行了建模研究。针对传统场景缩减算法无法有效处理海量初始场景的问题,提出了一种基于粒子群优化算法的改进场景缩减方法。该场景缩减算法的寻优空间是整个初始场景集,但粒子迭代寻优时的速度更新仅与自身之前的最优位置及粒子群中和其Kantorovich距离最小的粒子有关,相比传统算法,寻优时不需要对初始场景集进行遍历,计算耗时大大减少,从而有效解决了海量场景的缩减问题,为进一步的含风电电力系统优化调度研究打下了基础。 2.针对风电出力不确定性对系统运行平衡点的影响,研究了含风电电力系统的备用决策和调度问题。基于故障场景集提出了一种综合反映电源、负荷不确定性的可靠性指标,并推导了风电接入后系统备用需求的量化表达式,进而建立了含风电的电力系统发电和备用协调优化模型。利用该模型,不仅可以得到系统每个时段所需的运行备用总量,还可得到每个时段机组间的最优发电和备用分配方案。通过算例仿真验证了模型的有效性。所提方法很好地解决大规模风电接入后备用容量的量化和分配问题,给出的优化调度方案,为计算系统稳态运行平衡点提供了依据。 3.在梳理随机微分方程及随机稳定理论的基础上,研究了受随机激励影响的电力系统小扰动随机稳定机理。将异步风机机械功率视为随机过程,基于Ito随机微分方程建立了随机激励下的异步风力发电机动态模型,该模型克服了Riemann积分无法处理被积函数中随机项的局限,将电力系统的动态模型由确定性的常微分方程框架拓广到了随机微分方程框架下；在此基础上提出并证明了系统随机均值稳定和均方稳定的判据；并进一步推导得到了系统小扰动响应过程期望和方差的计算方法。推导得到的系统状态变量统计特征解析表达式准确地描述了随机激励下系统的动态过程。论文还通过数值方法进行了仿真验证,证明了所提分析方法的有效性和合理性。 4.研究了考虑随机系数的电力系统小扰动随机稳定机理。进一步考虑风机随机功率波动与系统其它电气量之间的耦合作用导致的状态方程系数的随机性,建立了基于Ito随机微分方程的含随机系数的系统动态模型；应用Ito公式将该系统的随机均方稳定性问题转化为确定性系统的均值稳定性问题,利用Lyapunov函数证明了这种系统的随机均方稳定判据；之后结合电力系统随机参数灵敏度分析方法得到了系统随机稳定概率的计算方法；并通过算例仿真验证了所提方法的合理性和有效性。该方法可有效且快速的计算有随机系数的电力系统稳定概率,其本质是解析的,虽然结果保守,但方法严谨可靠,且计算量较小。
[Abstract]:Wind power is the main form of exploitation and utilization of renewable and clean energy. The development of the wind power to optimize the energy structure, realize the diversification of energy supply, climate change, has very important significance to protect the ecological environment. The large-scale, centralized development, long-distance, high voltage transmission is the main feature of China's wind power development and conventional power supply. Adjustable and controllable compared regulating capacity of wind turbine and its output is weak with stochastic volatility, large-scale wind power access brings great impact to the safe and stable operation of power system. The traditional stability analysis methods based on deterministic state equation in solving the stability problem of wind power fluctuation caused by random limitations, it is necessary to use random differential equation and stochastic stability theory, a systematic research on the stability of the power system after wind power access. And the current research in this area is still very weak. The needle The different levels of wind power system state equation into random, targeted operation optimization of power system containing wind power and small perturbation stochastic stability mechanism research: in view of the influence of the uncertainty of wind power system operation to balance the backup and scheduling decision model of wind power uncertainty and modeling the power system with wind power; in a random dynamic model of wind turbine power system as a breakthrough, the stochastic differential equation theory of stochastic excitation and random coefficients of the small signal modeling and analysis method based on stochastic stability. The aim of the research on the stability of power system modeling and analysis method is extended to random space. The main research contents and contributions the following:
1. based on the scene of the uncertainty of wind power was researched. According to the traditional scenario reduction algorithms cannot effectively deal with the problem of the initial scene, a method for reducing the improvement of scene based on particle swarm optimization algorithm. The algorithm to reduce the search space of the scene is the initial scene set, but the optimal location and particle particle swarm iterative optimization speed when the update is only with their own before and its Kantorovich distance of particles, compared with the traditional algorithm, the optimization does not need to traverse the initial scenarios, the computing time is greatly reduced, so as to effectively solve the problem of massive cut scenes, including wind power system scheduling research it laid a good foundation.
2. for the wind power uncertainty on the system operation of the balance point of reserve decision and scheduling problem with wind power system. The fault scenario set presents a comprehensive reflection of the power based on the reliability index of the load uncertainty, and the quantitative expression of wind power system reserve demand is derived, and then the establishment of the power system with wind power generation and reserve coordination optimization model. Using this model, the total operating reserve can not only obtain the required period of each system, also can get the optimal power and standby time between each unit allocation scheme. The simulation results verify the validity of the model. The proposed method is very good to solve the large-scale wind power integration reserve quantification and capacity allocation problem, optimal scheduling scheme, provides the basis for the calculation of steady-state operation point of balance.
3. on the basis of stochastic differential equations and stochastic stability theory, the power system under random excitation of small perturbation stochastic stability mechanism. The asynchronous wind turbine mechanical power is considered as a stochastic process and Ito stochastic differential equation is established based on the random excitation asynchronous wind generator dynamic model, the model overcomes the Riemann integral unable to deal with the limitations of random integrand function, the dynamic model of the power system by the framework of ordinary differential equations are extended to the framework of deterministic stochastic differential equations; based on this system and stochastic mean stability and mean square stability criterion is proved; and further deduced the calculation method of response process of expectation and variance the small disturbance system. Analysis of the state variables of the system are derived from statistical characteristics accurately describes the dynamic process under random excitation system. The paper also The validity and rationality of the proposed method are proved by numerical simulation.
4. of the power system with random coefficients small perturbation stochastic stability mechanism considered. Further considering random coefficient equation of state leads to the coupling effect between the fan power fluctuation and other electric quantity of the system, establishes the system dynamic model with random coefficient Ito based on stochastic differential equation; application of Ito formula will mean the stability problem the stochastic mean square stability problem is transformed into a deterministic system, using the Lyapunov function to prove the system stochastic mean square stability criterion; then combined with power system stochastic parameter sensitivity analysis method to obtain the calculation method of stochastic stability probability; and validate the rationality and validity of the simulation calculation. This method can effectively and quickly the power system stability probability random coefficient, its essence is analytical, although the results are conservative, but The method is rigorous and reliable, and the amount of calculation is small.

【学位授予单位】：华北电力大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TM614

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