高载能负荷参与的集群风电场并网系统经济调度研究

发布时间：2018-03-31 18:32

本文选题：调度模式　切入点：高载能负荷　出处：《兰州理工大学》2017年硕士论文

【摘要】：我国现阶段风电场的主要调度模式是各省级风电调度中心直接面向所辖区域内的单个风电场。此调度模式,一方面加大了调度人员的工作量,另一方面限制了风电场之间的协调控制。再者,我国风电场主要位于电网末端,当地电网调节能力有限,严重限制了风电场的大规模并网,从而导致含风电场的并网系统难以实现经济调度。目前,我国风电总装机容量位居世界第一,并且风电行业还在快速发展,这使得实现大规模风电场并网系统的经济调度成为一个亟待解决的问题。首先,针对现阶段难以实现大规模风电场并网系统经济调度的实际情况,本文提出了将高载能负荷作为可调度资源的新调度模式。高载能负荷通过集群协调层与风电场进行协调调度。集群协调层内包括数量随机的高载能负荷和风电场,其中风电场的数量不能为零,而高载能负荷可以为零。一方面集群协调层整合群内风电场和高载能负荷的调度出力信息,将整合结果反馈给上级控制中心,以便上级控制中心做出最优调度策略;另一方面集群协调层在收到风电调度中心的调度指令后,合理安排控制域内高载能负荷的投、切。其次,本文在所提新调度模式的基础上建立了两种风电场并网系统经济调度的数学模型,并利用智能优化算法对其进行优化求解。第一种是二层优化模型,上层模型以实现电网的总成本最小为目标,下层模型以实现集群协调层的收益最大为目标。对于二层优化模型本文分别采用帝国竞争算法和二进制粒子群优化算法对上层和下层模型进行优化求解。第二种是多目标模型,此模型以实现调度中心的总成本最小及集群协调层的收益最大为目标,并采用改进多目标布谷鸟算法进行优化求解。两种模型在优化过程中,均不能同时实现每个目标,而是使相关联的目标达到协调最优。最后,分别对两种数学模型及其优化算法进行了仿真分析。仿真结果验证了所提调度模式和所建经济调度数学模型的正确性及算法的有效性。
[Abstract]:The main dispatching mode of wind farms in China at present is that each provincial wind power dispatching center is directly oriented to a single wind farm in the region under its jurisdiction. This dispatching mode, on the one hand, increases the workload of the dispatchers. On the other hand, it restricts the coordination and control between wind farms. Furthermore, wind farms in China are mainly located at the end of the power grid, and the local power grid has limited regulating capacity, which seriously limits the large-scale grid connection of wind farms. As a result, grid-connected systems with wind farms are difficult to achieve economic dispatch. At present, the total installed capacity of wind power in China ranks first in the world, and the wind power industry is still developing rapidly. This makes the economic dispatch of large-scale wind farm grid-connected system an urgent problem to be solved. Firstly, it is difficult to realize the economic scheduling of large-scale wind farm grid-connected system at this stage. In this paper, a new scheduling mode of high load load is proposed. High load load is coordinated with wind farm through cluster coordination layer. Cluster coordination layer includes a number of random high load and wind farm. The number of wind farms can not be zero, and the load of high load can be zero. On the one hand, the cluster coordination layer integrates the dispatching information of wind farm and high load in the cluster, and feedback the integration result to the superior control center. On the other hand, the cluster coordination layer, after receiving the dispatch order of the wind power dispatching center, reasonably arranges the input and cut of the high load load in the control domain. Secondly, On the basis of the proposed new scheduling model, this paper establishes two kinds of mathematical models of economic dispatching of wind farm grid connected system, and optimizes them by using intelligent optimization algorithm. The first one is two-layer optimization model. The upper model aims at minimizing the total cost of the power network. For the two-layer optimization model, the Imperial Competition algorithm and binary Particle Swarm Optimization algorithm are used to solve the upper and lower layer models respectively. The second is multi-objective model. The goal of this model is to achieve the minimum total cost of the dispatching center and the maximum revenue of the cluster coordination layer, and the improved multi-objective cuckoo algorithm is used to solve the problem. Neither model can achieve each goal simultaneously during the optimization process. But to achieve the optimal coordination of the associated goals. Finally, Two kinds of mathematical models and their optimization algorithms are simulated and analyzed respectively. The simulation results verify the correctness of the proposed scheduling model and the economic scheduling mathematical model and the validity of the algorithm.
【学位授予单位】：兰州理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM614;TM73

【相似文献】