Abstract:

Distributed wind power is a new type of wind power. Its advantage is to make full use of the wind energy around users, reduce the transmission cost and improve the reliability of power supply. However, due to its proximity to users, distributed wind farms have serious noise pollution. Previous studies often used noise reduction equipment or the method of reducing power generation to deal with the noise problem, and few scholars studied it from the perspective of optimizing the layout of wind turbines. For distributed wind farms, layout optimization is very critical and complex. The economy of distributed wind farms depends on the layout design, which is affected by complex factors such as wind fluctuation, wind turbine wake loss, cable wiring and so on. Therefore, in this study, combined with noise, wind speed distribution, wake loss, power curve and cable connection model, taking the maximum annual economic benefit of the wind farm as the objective function, genetic algorithm and steiner algorithm are used to optimize the wind turbine location distribution and cable wiring respectively, and ensure economy while minimizing noise impact.

Key words: wind energy, distributed wind farm layout, genetic algorithm, Steiner algorithm, noise simulation, optimization

摘要：

分布式风电是一种新型风电，其优势在于充分利用用户周围的风能，降低输电成本同时提高供电可靠性。然而，由于靠近用户，分布式风场存在严重的噪声污染。以往的研究对噪声问题常采用降噪设备或者降低发电功率的方法处理，少有学者从优化风机布局的角度研究。对于分布式风场而言，布局优化十分关键且较复杂。因为分布式风场的经济性取决于布局设计，而布局设计又受风力波动、风机尾流损失以及电缆布线等复杂因素影响。因此，本研究结合噪声、风速分布、尾流损失、风机功率曲线以及缆线连接模型，以最大风场年经济效益为目标函数，采用遗传算法和斯坦纳树算法对风机位置分布和电缆布线进行优化，以期提高风场经济性的同时降低噪声影响。

关键词: 风能, 分布式风场布局, 遗传算法, 斯坦纳树算法, 噪声模拟, 优化