改进型遗传算法在风电场无功优化与比较-电气工程专业论文.docxVIP

摘 摘 要 万方数据 万方数据 摘 要 风电是现代新型能源中最为重要的资源之一，它的技术已经非常成熟，因 此受到了全世界广泛的关注，专家学者对于风电发电的研究成果也越来越多。 然而随着风电规模的不断扩大，电网中不确定因素也不断增加，主要问题有， 电压质量的下降，电压稳定性和供电可靠性的降低等等。因此对于风电的研究， 必须考虑其无功优化的问题，如果能够通过研究计算等方法解决该问题，那就 可以改善风电质量，其前景非常广阔。 针对所提出问题，本文需要研究风电场无功优化问题，提出了风电场模型， 无功优化模型，使得算例结果更接近实际情况。并引入了一种新型的潮流计算 方法，改进型遗传算法，该算法利用解法的特征，保证了潮流计算能够得到全 局最优解，不易陷入局部的最优的情况，在传统无功优化模型的基础上提出了 同时考虑有功损耗最小和无功补偿最小的多目标无功优化模型，来完成风电场 系统的无功优化。最后基于某仿真为例，分别对本文提出的目标进行无功优化， 并对比其优缺点，结果表明，改进型的遗传算法能够有效的控制网损和无功功 率，能够降低风电场接入电网后发生的不稳定情况。 关键词：风能；改进型；无功优化；遗传算法 I AB ABSTRACT ABSTRACT Wind power is one of the most important modern new energy resources, and its technology has been very mature, and therefore subject to a wide range of worldwide concern, experts and scholars for research of wind power generation is also increasing. However, with the continuous expansion of wind power, the grid uncertainties are increasing, there are major problems, drop voltage quality, stability and reliability of power supply voltage is reduced, and so on. Therefore, the study of wind power, wind farms must be considered reactive power optimization problem, especially after the optimization and network, to improve performance and quality of wind power has very important significance. In response to these problems, this paper studies the wind farm reactive power optimization problem, a wind farm model, reactive power optimization model, making the numerical results closer to the actual situation. And the introduction of a new trend calculations , improved genetic algorithm, the algorithm uses the solution characteristics to ensure that the flow calculation to get global optimal solution, easy to fall into local optimal circumstances, the traditional model of reactive power optimization made on the basis of taking into account the minimum power loss and reactive power compensation smallest multi-objective optimization model of reactive power, to complete the wind farm system reactive power optimization. Finally, based on a simulation of an example, t