包含风电机组的配电网多场景综合指标无功优化研究

发布时间：2018-06-21 21:01

本文选题：风力发电 + 无功优化　；参考：《山东大学》2017年硕士论文

【摘要】：随着全球化石能源的紧缺以及人们环保意识的增强,风力发电因其在节能减排方面产生的巨大效益,得到人们的普遍重视与大力发展。当风电机组接入配电网,不仅配电系统结构变得愈加复杂,同时,配电网络原有的潮流分布也将重新分配,此外,风机功率的流入对配电系统的节点电压、支路损耗和运行可靠性等方面也有重要影响。发挥双馈式风机的无功调控能力,将其作为无功源之一,与传统无功补偿设备共同参与配电网无功优化,能够有效地减少无功补偿设备的投资,极大地提高电网运行的稳定性,改善电压质量,并降低网络损耗。因此,研究风电机组接入配电网后的无功优化问题具有重要意义。本文针对风电机组接入配电网后的无功优化问题,主要做了以下研究:首先,针对风机输出功率的随机性问题,引入场景分析法将不确定性问题转化为确定问题求解,在传统无功优化模型的基础上,建立了包含风电机组的多场景综合指标无功优化模型。该模型旨在充分发挥双馈式风机的无功调控能力,研究风机对传统无功优化的影响。在优化过程中,风电机组采用PQ简化模型作为PQ节点代入潮流计算,当出现潮流不收敛或者电压超出标准范围时,采取在目标函数上添加惩罚项的方法来减小不良解被留下的几率。其次,根据和声搜索算法和粒子群算法的寻优原理,将两种算法相结合,充分利用和声搜索算法的全局寻优能力和粒子群算法的快速收敛能力,得到综合两种算法优点的混合型算法——自适应和声粒子群优化算法。将该混合型算法和其他几种算法应用到IEEE33节点系统中进行无功优化问题的对比求解,结果表明,自适应和声粒子群优化算法具有参数少、结构简单、收敛精度高、计算速度快、容易编程实现等优点,能够有效地解决无功优化问题,具有一定的实用性。再次,在同一优化目标不同场景下对包含风电机组的配电网进行无功优化,结果表明,当风电机组输出的无功功率参与配电网无功优化时,在一定范围内,增加无功补偿容量可以有效地减小网络损耗、提高节点电压水平、增大第一类电压稳定裕度,对电力系统来说,风机运行在欠功率模式时优化效果最好;另外,同一场景下,比较优化目标不同对优化补偿方案以及结果的影响,结果分析表明,将综合指标作为优化目标可以得到协调各目标的优化方案,更适合于实际电力系统运行的需要,可以作为实际补偿方案的参考。最后,初步探讨负荷变化对优化结果的影响,研究发现,随着负荷率的减小,网损和电压偏差指标呈减小的趋势,电压稳定裕度呈增加的趋势。而随着系统中容性负载的逐渐增多,网损和电压偏差也呈逐渐减小的趋势,但电压稳定裕度却逐渐减小,当所有负载均为容性负载这种极端情况出现时,系统极有可能失去稳定。
[Abstract]:With the shortage of fossil energy in the world and the enhancement of people's environmental protection consciousness, wind power generation has been widely paid attention to and developed greatly because of its huge benefits in energy saving and emission reduction. When the wind turbine is connected to the distribution network, not only the structure of the distribution system becomes more complex, but also the original distribution of the power flow in the distribution network will be redistributed. In addition, the inflow of fan power to the node voltage of the distribution system, Branch loss and operational reliability also have an important impact. Exerting the reactive power control ability of doubly-fed fan as one of the reactive power sources, and participating in the reactive power optimization of the distribution network together with the traditional reactive power compensation equipment, can effectively reduce the investment of the reactive power compensation equipment and greatly improve the stability of the power network operation. Improve voltage quality and reduce network loss. Therefore, it is of great significance to study the problem of reactive power optimization after wind turbine is connected to distribution network. In this paper, the reactive power optimization problem of wind turbine connected to distribution network is studied as follows: firstly, aiming at the randomness of fan output power, scene analysis method is introduced to solve the uncertainty problem into a deterministic problem. Based on the traditional reactive power optimization model, a multi-scene reactive power optimization model is established. The model aims to give full play to the reactive power control ability of doubly-fed fan and to study the influence of fan on traditional reactive power optimization. In the process of optimization, the simplified PQ model is used as the PQ node to calculate the power flow. When the power flow does not converge or the voltage exceeds the standard range, A penalty term is added to the objective function to reduce the probability of the bad solution being left behind. Secondly, according to the optimization principle of the harmonic search algorithm and particle swarm optimization algorithm, the two algorithms are combined to make full use of the global optimization ability of the harmony search algorithm and the fast convergence ability of the particle swarm optimization algorithm. An adaptive and acoustic particle swarm optimization algorithm, which combines the advantages of the two algorithms, is presented. The hybrid algorithm and several other algorithms are applied to solve the reactive power optimization problem in IEEE 33 bus system. The results show that the adaptive harmonic particle swarm optimization algorithm has the advantages of few parameters, simple structure, high convergence precision and fast calculation speed. It is easy to realize by programming and can solve the problem of reactive power optimization effectively. Thirdly, reactive power optimization of distribution network with wind turbine is carried out under the same optimization objective and different scenarios. The results show that when the reactive power output of wind turbine participates in the reactive power optimization of distribution network, it is within a certain range. Increasing the reactive power compensation capacity can effectively reduce the network loss, improve the voltage level of the node, and increase the voltage stability margin of the first type. By comparing the effects of different optimization objectives on the optimal compensation scheme and the results, the results show that the optimization scheme can be coordinated by using the composite index as the optimization objective, which is more suitable for the operation of the actual power system. It can be used as a reference for the actual compensation scheme. Finally, the influence of load variation on the optimization results is preliminarily discussed. It is found that with the decrease of load rate, the network loss and voltage deviation index decrease, and the voltage stability margin increases. With the increase of capacitive load in the system, the network loss and voltage deviation decrease gradually, but the voltage stability margin decreases gradually. The system is at great risk of losing stability.
【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM714.3

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