The insufficient power system flexibility and transmission congestion are two fundamental reasons for wind power curtailment. As the scale of the wind power in the power system is growing rapidly, the two factors of wind power curtailment events coexist and have a certain coupling relationship. The configuration of the energy storage system can not only increase the flexibility of the system but also alleviate transmission congestion. Therefore, the joint planning of energy storage and transmission grid that takes into account the flexibility of the system and the transmission congestion is of great significance to solve the wind curtailment. Hence, this paper first decouples the insufficient flexibility and transmission congestion wind power curtailment, and quantitatively analyzes the impact of transmission capacity on the coupling relationship between the two; second, reveals the principle of joint planning of energy storage system and transmission congestion, and constructs an optimization model, and proposes to set up the capacity of the wind power which connects the power network. The solution procedure, which deals with grid planning and the energy storage system optimization in turn, not only ensures the accuracy of the model, but also significantly reduces the calculation cost. Finally, a case study of a wind power base in Northeast China and an improved Garver-6 system are carried out to verify the effectiveness of the proposed method.

This paper proposes a new oil-immersed transformer failure rate model based on Cox's time-dependent proportional hazards model (PHM). The proposed model takes both equipment aging process and equipment inspection information into consideration. The failure rate function of PHM consists of two parts: the baseline hazard function which represents the aging process, and the link function which represents the influence of covariant, such as the equipment health condition. In the proposed model, the baseline hazard function follows a winding hot spot temperature-based aging model. The quantity of the dissolved gas in oil is used to estimate the equipment health condition which is used as the covariate of the link function. The probability density function (PDF) of the time to failure is determined, and the maximum likelihood estimation (MLE) is used to estimate the unknown parameters. The case study shows that the proposed model is able to reflect the individual variation and customize the transformer failure rate reasonably and comprehensively. In addition, the maintenance effect can also be taken into account.

No abstract

No abstract