风力发电机建模对混合可再生能源系统的影响

Hussein M. K. Al-Masri, M. Ehsani
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引用次数: 6

摘要

本文研究了风力发电机(WT)建模对约旦一个城市安装的混合风-光伏(PV)系统的影响。仔细观察影响输出功率的参数,以准确地对系统建模。这有助于监测涡轮机的性能、风电场的规模和整个混合动力系统,这肯定会影响单个WT以及整个风力涡轮机的年能量提取(AEE)。同时,混合动力系统的净现值成本(NPC)、电网运行成本(GOC)和能源成本(COE)等成本也会受到影响。为了了解新系统的规模和成本效应,混合优化多能源软件中添加了六个WT模型。给出了每个小波变换模型的逐步分析和设计及其对混合系统的影响。结果表明,当WT简化模型从三次、二次型向线性型转变时,所得到的系统在估计成本和AEE方面存在显著的百分比误差。此外,WTs的数量在系统级别增加,直到它成为线性模型中的仅风配置。但是,这是以不精确的规模解决方案为代价的,这会导致对项目投资的错误估计。因此,必须通过考虑许多参数(如空气密度,例如地理海拔)来精确地建模小波变换。结果表明,在海平面上设计的WT模型在AEE和系统成本上的估计与在实际温度或海拔(a.s.l)上设计的模型有误差。简单的小波变换模型不能提供理论计算的AEE。这种能源短缺将被更昂贵的并网传统发电厂燃料能源所取代。换句话说,为了解决实际问题,必须考虑影响WT模型的参数的实际值。同样的程序可以在世界其他地方应用。
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Impact of wind turbine modeling on a hybrid renewable energy system
This paper investigates the impact of the wind turbine (WT) modeling on a hybrid wind-photovoltaic (PV) system installed in a city in Jordan. A closer look is taken at the parameters affecting the output power to accurately model the system. This helps in monitoring the turbine performance, sizing of the wind farm and the entire hybrid system, which will definitely affect the annual energy extracted (AEE) from a single WT as well as the entire wind turbines (WTs). Also, the cost of the hybrid system such as the net present cost (NPC), the grid operating cost (GOC) and the cost of energy (COE) will be affected. Six WT models are added to Hybrid Optimization Multiple Energy Resources software in order to see the sizing and cost effects of the new system. A step-by-step analysis and design of each proposed WT model and its effects on the hybrid system are presented. Results show that as the WT simplified models change from the cubic, quadratic, toward the linear one, the resulting system has a significant percentage error in the estimation of the cost as well as AEE. Also, the number of WTs increases at the system level till it becomes a wind only configuration in the linear model. But, this is at the penalty of the imprecise sizing solution, which leads to wrong estimates for the project investment. Therefore, the WT has to be modeled accurately by considering many parameters such as the air density, e.g., geographic elevation. The results show that the WT model designed at sea level shows error estimates in both AEE and the system cost from the one designed at actual temperature or elevation above sea level (a.s.l). The simple WT models will not deliver the AEE theoretically calculated. This energy deficit will be substituted by the more expensive on-grid conventional power plant fuel energy. In other words, in order to solve a real problem, the real values for parameters affecting the WT model have to be considered. The same procedure can be applied in other locations around the world.
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