分散式风电场微观选址技术研究及其系统开发

发布时间：2018-03-24 21:44

本文选题：分散式风电　切入点：微观选址　出处：《东北大学》2014年硕士论文

【摘要】：近些年来我国经济一直保持高速发展。与此同时,由于能源的不合理利用造成的环境污染问题也日益严重。基于此,我国提出要发展绿色经济,走可持续发展道路。其中,风力发电是能源可持续发展的重要支撑,而分散式发电方式是近些年来利用风能的一大特点。在风能的实际应用中,首先应考虑风电场的选址问题。场址的选择对风能的利用率和经济性起到至关重要的作用。在宏观选址之后,微观选址的工作是在选定的小区域中进行风力发电机组的排列布置,以便使整个风电场的输出功率达到最大化,具有更好的经济效益。本文从经济、技术和环境等因素出发,研究了分散式风力发电的微观选址技术,并且开发了适用于分散式风电场微观选址的软件系统。本文首先介绍了风资源的基础知识。在此基础上,详细分析了如何利用风速的威布尔分布求风能评估参数,以及威布尔分布参数的估计；建立了风电场风机的Jensen尾流模型,采用该尾流模型计及风电场上下游风机之间相互遮挡的影响,确定了计算风电场任意风机位置的风速的方法。然后本文对分散式风电场微观选址方法进行了研究。针对离散空间的微观选址提出了自适应和声搜索算法,建立了微观选址的目标函数,提出了自适应的参数调整策略。通过仿真对比,验证了该方法的可行性；在分析离散化空间风电场微观选址局限性的基础上,针对连续空间的微观选址提出了动态和声粒子群算法。通过分析优化结果,验证了算法的可行性及较前述算法的优越性。之后结合上述分散式风电场微观选址方法进行了分散式风电场微观选址软件的开发。分散式风电场微观选址软件是在Visual Studio 2010编程环境中结合ArcGIS Engine来实现的,软件实现了风电场微观选址的各项功能,包括分散式风电场风图谱的绘制、风机优化定位等。通过与WAsP软件选址结果进行比较,验证了本软件的可行性和优越性。最后,总结了本文的工作内容,就理论研究和软件完善的方向进行了展望。
[Abstract]:In recent years, the economy of our country has been developing at a high speed. At the same time, the problem of environmental pollution caused by the irrational use of energy is becoming more and more serious. Based on this, our country proposes to develop the green economy and take the road of sustainable development. Wind power generation is an important support for the sustainable development of energy, and decentralized power generation is a major feature of wind energy utilization in recent years. First of all, we should consider the location of wind farm. Site selection plays an important role in the utilization and economy of wind energy. In order to maximize the output power of the whole wind farm and have better economic benefit, the micro-location work is to arrange the wind turbine in the selected small area. This paper starts from the factors of economy, technology and environment, etc. This paper studies the micro-location technology of decentralized wind power generation, and develops a software system suitable for micro-location of decentralized wind farm. Firstly, the basic knowledge of wind resources is introduced in this paper. This paper analyzes in detail how to use Weibull distribution of wind speed to obtain wind energy evaluation parameters and Weibull distribution parameter estimation, establishes Jensen wake model of wind turbine fan, The wake model is used to take into account the influence of mutual occlusion between upstream and downstream fans of wind farm. The method of calculating wind speed of arbitrary fan position in wind farm is determined. Then, the micro-location method of decentralized wind farm is studied in this paper. An adaptive harmonic search algorithm is proposed for the micro-location of discrete space. The objective function of micro site selection is established, and an adaptive parameter adjustment strategy is proposed. The feasibility of this method is verified by simulation and comparison, and the limitation of discrete space wind farm location is analyzed. A dynamic harmonic particle swarm optimization algorithm is proposed for the microscopic location of continuous space. The feasibility of the algorithm and the superiority of the above algorithm are verified. Then, the decentralized wind farm micro-location software is developed in combination with the above decentralized wind farm micro-location method. The decentralized wind farm micro-location software is developed. In the Visual Studio 2010 programming environment combined with ArcGIS Engine, The software realizes the functions of wind farm micro-location, including wind map drawing of distributed wind farm, wind turbine optimization location, etc. The feasibility and superiority of this software are verified by comparing with the result of WAsP software. The work of this paper is summarized, and the direction of theoretical research and software improvement is prospected.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM614

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