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机构地区:[1]电力系统及发电设备控制和仿真国家重点实验室(清华大学电机系),北京市海淀区100084
出 处:《中国电机工程学报》2015年第20期5135-5146,共12页Proceedings of the CSEE
基 金:国家863高技术研究发展计划(2012AA050203)~~
摘 要:在中国风电集中接入发展模式下,集群风电以虚拟机组(wind farm cluster virtual power generation unit,WCVPG)形式参与运行可提高其可调度性。对WCVPG出力特性的准确建模是将其纳入调度运行的基础。该模型的核心是风电的不确定性和波动性概率模型,其概率分布具有非平稳的特点,难以直接推导其解析表达式。该文提出一种建立WCVPG不同时段时变概率分布的方法。首先,基于非平稳随机过程概念,定义了概率分布和互相关系数时变特性;然后,基于实测数据论证了风电时变特性的客观存在。在此基础上,提出了一种基于离线时变状态相依模型集和在线蒙特卡罗抽样的WCVPG时变概率建模方法,基于实际系统和数据验证了其有效性,并证明了考虑风电概率分布时变特性可提高建模精度。Wind farm cluster virtual power generation (WCVPG) unit is a potential way to increase wind power's dispatch ability in China's centralized wind power development mode. Building WCVPG's output characteristic model is the foundation to consider WCVPG in dispatch strategy. Therefore, the main task here is to establish uncertainty and variability probabilistic distribution models. These probabilistic distribution models have the characteristic of non-stationary, which is difficult to obtain their analytic expression. Therefore, this paper proposed a method to build the time-varying probabilistic distributions for WCVPG during different time periods. Firstly, based on the concepts of non-stationary random process, the concepts of time-varying probabilistic distribution and time-varying cross correlation coefficient were defined. Afterwards, the existence of wind power's time-varying characteristic was demonstrated based on measured data. Then, a time-varying probabilistic distribution model method was proposed based on the offline time-varying state dependent model set and online Monte Carlo Sampling. Finally, the effectiveness of this method was verified by real system and measured data. The results show that considering the time-varying characteristic of wind power probabilistic distribution can increase the modeling accuracy.
关 键 词:集群风电 虚拟机组 时变概率分布 不确定性 波动性
分 类 号:TM614[电气工程—电力系统及自动化]
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