| 引用本文: | 叶燕飞,王琦,陈宁,伏祥运,赵阳.考虑时空分布特性的风速预测模型[J].电力系统保护与控制,2017,45(4):114-120.[点击复制] |
| YE Yanfei,WANG Qi,CHEN Ning,FU Xiangyun,ZHAO Yang.Wind forecast model considering the characteristics of temporal and spatial distribution[J].Power System Protection and Control,2017,45(4):114-120[点击复制] |
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| 摘要: |
| 随着风电并网规模日益增加，风电功率波动对电网的影响将更加显著。风速预测可以辅助电网制定调度和运行控制决策，合理应对风电功率波动，降低风电功率波动对电网安全稳定运行的影响。考虑风电机组的地理分布和风速的时间、空间分布特性，建立等效风速模型。由该模型建立上、下游风电机组的风速关联关系，修正下游风电机组的风速。在此基础上，提出一种基于修正系数的风速预测方法，以提高预测精度。以实际风电场地理数据和风电机组参数为基础的仿真算例验证了该方法的可行性和合理性。 |
| 关键词: 风速预测 尾流效应 时空分布模型 修正风速 |
| DOI：10.7667/PSPC160251 |
| 投稿时间：2016-03-01修订日期：2016-05-26 |
| 基金项目: |
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| Wind forecast model considering the characteristics of temporal and spatial distribution |
| YE Yanfei,WANG Qi,CHEN Ning,FU Xiangyun,ZHAO Yang |
| (School of Electrical & Automation Engineering, Nanjing Normal University, Nanjing 210042, China;China Electric Power Research Institute, Nanjing 210003, China;Lianyungang Electric Power Dispatching and Control Center, Lianyungang 222004, China) |
| Abstract: |
| With the increasing of scale of wind power integrated into power system, the influence of wind power fluctuation to the power system is more serious. Wind speed prediction can help formulate electric power grid scheduling and make operational control decision, rational response to wind power fluctuations can reduce the impact of wind power fluctuations on grid safety and stable operation. This paper establishes an equivalent wind speed model considering the geographic distribution of wind turbines and wind speed distribution in time and space. The wind speed relationship between upstream wind turbine and downstream wind turbine is established based on this model, which is used to fix the wind speed of downstream wind turbine. In addition, a wind farm power forecasting method is proposed based on wind speed revision, in order to improve the prediction accuracy of wind power. The feasibility and rationality of the method is verified by simulation examples based on actual wind farms parameters and geographic data. |
| Key words: wind speed prediction wake effect spatio-temporal distribution model modified wind speed |
