Due to the voltage level and current of feeders in distribution systems, power loss is high in such networks. With the proliferation of distributed generations, it has become more important to determine their location and rating. These goals can be obtained according to different purposes such as improving the voltage profile. Unlike fixed speed wind turbines, the variable speed type can produce or absorb the reactive power. Hence, this paper specifies the placement and sizing of variable speed wind turbines based on a multi-objective function and according to the reactive power management. In the first step, the variable speed wind turbine is modeled by using the practical curve and Levenberg–Marquardt algorithm and then, the objective functions are optimized simultaneously to achieve the locations and sizes. Also, the impact of wind speed uncertainty on the functions is evaluated. To validate the results, a comparison between variable speed and fixed speed wind turbines is also presented. The proposed model is implemented on an IEEE 33-bus standard test system and the results show a significant (42%) decrease in power loss by adding variable speed wind turbines. However, the investment cost is also increased. Moreover, with considering the uncertainty, power loss and investment cost are increased by about 8% and 15%, respectively. However, the robustness of the system is enhanced against the wind speed fluctuations.

中文翻译：

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确定变速风力涡轮机的尺寸和位置，以减少功率损耗并改善电压曲线

由于配电系统中馈线的电压水平和电流，在这样的网络中功率损耗很高。随着分布式世代的激增，确定其位置和等级变得越来越重要。这些目标可以根据不同的目的（例如改善电压曲线）来获得。与定速风力涡轮机不同，变速类型可以产生或吸收无功功率。因此，本文基于多目标函数并根据无功功率管理规定了变速风力涡轮机的布置和尺寸。第一步，使用实际曲线和Levenberg-Marquardt算法对变速风力涡轮机进行建模，然后同时优化目标函数以实现位置和大小。也，评估风速不确定性对功能的影响。为了验证结果，还提出了变速和定速风力涡轮机之间的比较。所提出的模型在IEEE 33总线标准测试系统上实现，结果表明通过添加变速风力涡轮机，功率损耗显着降低（42％）。但是，投资成本也增加。此外，考虑到不确定性，功率损耗和投资成本分别增加了约8％和15％。然而，该系统的鲁棒性针对风速波动而增强。所提出的模型在IEEE 33总线标准测试系统上实现，结果表明通过添加变速风力涡轮机，功率损耗显着降低（42％）。但是，投资成本也增加。此外，考虑到不确定性，功率损耗和投资成本分别增加了约8％和15％。然而，该系统的鲁棒性针对风速波动而增强。所提出的模型在IEEE 33总线标准测试系统上实现，结果表明通过添加变速风力涡轮机，功率损耗显着降低（42％）。但是，投资成本也增加。此外，考虑到不确定性，功率损耗和投资成本分别增加了约8％和15％。然而，该系统的鲁棒性针对风速波动而增强。