含大规模风电场的电力系统备用容量优化研究

发布时间：2018-07-04 08:42

本文选题：风电场 + 备用容量　；参考：《华北电力大学》2014年硕士论文

【摘要】：近年来，，风能作为一种可再生清洁能源，对其的开发利用已成为缓解能源危机和减少环境污染的重要手段之一。随着风电装机并网容量的不断增大，其出力变化的随机性和间歇性对现有电力系统的影响日益突出，风电并网后，系统为维持频率稳定，需要更加合理的备用容量配置。因此本文对大规模风电场并网后，电力系统备用容量优化进行了研究，并针对风电并网带来的备用容量需求增大的问题，提出了含风电场的互联电力系统备用容量优化模型。首先，针对风电并网后带来的不确定因素，基于机会约束规划，建立了含大规模风电场的电力系统备用容量优化模型。模型考虑了大规模风电场并网发电的情况，对发电机组的故障停运、负荷预测误差和风电场出力预测误差等不确定因素进行了建模，以系统的安全稳定运行的概率作为备用容量的约束条件。模型采用基于Monte-Carlo随机模拟的遗传算法作为求解算法。其次，大规模风电并网后，系统的备用容量需求将急剧增大，对此本文建立了含风电场的互联电力系统备用容量优化模型。模型针对构成互联电力系统的各子系统的备用容量配置特点，将其划分为备用容量富足子系统和稀缺子系统，然后分析各子系统不同的备用容量调用方式，分别建立了各自基于机会约束规划的安全稳定约束。模型充分考虑了影响备用容量配置的各种不确定因素，并且量化了共享备用的容量大小，明确了共享备用在各子系统间的调用过程。最后，本文以IEEE标准测试系统为算例，通过MATLAB编程实现算法，对上述两模型的可行性进行了验证。算例分析表明：大规模风电场并网后，电力系统对备用容量的需求增大，且增大程度远大于同规模的负荷备用需求；通过互联电力系统备用容量联合优化，在保证系统安全稳定的前提下，该模型能有效降低系统总的备用配置容量，同时备用容量富足子系统能够为含风电场的稀缺子系统提供备用支持，这为解决大规模风电场接入后备用容量配置问题提供了新的思路。
[Abstract]:In recent years, wind energy as a renewable clean energy, its development and utilization has become an important means to alleviate the energy crisis and reduce environmental pollution. With the increasing of wind power grid connection capacity, the randomness and intermittency of wind power output change have more and more influence on the existing power system. After wind power grid connection, the system needs more reasonable spare capacity configuration to maintain frequency stability. Therefore, this paper studies the optimization of reserve capacity of power system after large-scale wind farm is connected to grid, and puts forward an optimization model of reserve capacity of interconnected power system with wind farm in view of the problem of increasing demand for reserve capacity caused by wind power grid connection. Firstly, aiming at the uncertainty caused by wind power grid connection, a power system reserve capacity optimization model with large-scale wind farm is established based on opportunistic constrained programming. The model takes into account the large-scale wind farm grid-connected power generation, and models the uncertain factors such as fault outage, load forecasting error and wind farm output prediction error. The probability of safe and stable operation of the system is taken as the constraint of reserve capacity. The genetic algorithm based on Monte-Carlo random simulation is used as the solving algorithm. Secondly, after large-scale wind power is connected to the grid, the demand for reserve capacity of the system will increase sharply. In this paper, an optimization model of the reserve capacity of interconnected power system with wind farm is established in this paper. According to the characteristics of spare capacity configuration of each subsystem, the model divides it into spare capacity abundant subsystem and scarce subsystem, and then analyzes the different standby capacity transfer modes of each subsystem. Security and stability constraints based on chance constraint programming are established respectively. The model takes into account all kinds of uncertain factors that affect the configuration of standby capacity, quantifies the capacity of shared standby, and clarifies the call process of shared standby between subsystems. Finally, taking IEEE standard test system as an example, the feasibility of the above two models is verified by MATLAB programming. The analysis of example shows that the demand for reserve capacity of power system increases after large-scale wind farm is connected to grid, and the increase degree is much larger than that of load reserve demand of the same scale, and the reserve capacity of interconnected power system is optimized by the joint optimization of reserve capacity of interconnected power system. On the premise of ensuring the safety and stability of the system, the model can effectively reduce the total reserve configuration capacity of the system, and the spare capacity abundant subsystem can provide backup support for the scarce subsystem including wind farm. This provides a new idea for solving the problem of standby capacity allocation after large scale wind farm is connected.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM614

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