考虑随机场景生成及优选技术的分布式能源站选型定容规划研究

精准地把握风、光等可再生能源以及电、热等负荷的不确定性因素,可使规划后的分布式能源站更加经济、稳定地运行。针对这一问题,首先,提出了综合考虑时序自相关性和互相关性的随机场景生成及优选方法,得到一定数量具有代表性的随机场景;然后,建立了随机场景下分布式能源站的选型定容规划模型;其次,通过算例,分别将在不同随机场景生成方法下的分布式能源站规划结果与在传统的确定性场景下规划结果进行对比,验证了本文所提考虑随机场景生成及优选技术的分布式能源站选型定容规划方法的合理性和可行性,最后,分析了基于综合考虑时序自相关性和互相关性的随机场景生成及优选方法所规划的能源站运行特性。

DEPENDENCE ANALYSIS OF REGRESSION MODELS IN TIME SERIES

In this paper, the relative dependence of a linear regression model is studied. In particular, the dependence of autoregressive models in time series are investigated. It is shown that for the first-order non-stationary autoregressive model and the random walk with trend and drift model, the dependence between two states decreases with lag. Some numerical examples are presented as well.