With the development of renewable energy,the voltage support strength of multi-infeed systems with renewable energy is gradually decreasing,and there is an urgent need for strength evaluation methods.Considering that devices are all at the rated operation condition points,accurate quantification of strength can be achieved by utilizing existing power grid strength indices and threshold.However,the actual operation conditions of devices are diverse and complex,which disrupts the existing criteria for defining indices and causes existing methods to fail.Therefore,this paper focuses on the quantification problem of voltage support strength under actual operation conditions.Based on the perturbation theory of eigen-subspaces,an equivalent single-infeed system that can approximately characterize the stability of the actual system is solved.On this basis,the definition and physical significance of the generalized operational short-circuit ratio are provided,so as to rigorously quantify the strength under actual operation conditions using the generalized operational short-circuit ratio and the critical operational short-circuit ratio for devices.In addition,this paper reveals the specific mechanism of the actual operation conditions on strength with different stable forms.Finally,the effectiveness of the proposed method is verified through cases.
Accurate real-time topology identification of distribution networks is the basis for safe and stable operation of power systems,but with the access of renewable energy and the increasing scale of distribution network,the dynamic changes of the distribution network topology are more frequent and difficult to identify.However,the historical data used by the existing topology identification algorithms need to be labeled manually,and the topology identification time is long.So it is difficult to achieve real-time topology identification for distribution networks.Therefore,a real-time two-stage topology identification algorithm for distribution networks based on field programmable logic gate array(FPAG)is proposed.The proposed algorithm does not need to know the number of distribution network topology categories in advance,and can label and classify the existing historical data,and realize the real-time topology identification for distribution networks based on FPGA.The algorithm is divided into two stages.The first stage uses the variational Bayesian Gaussian mixture model to label and classify the existing historical data.In the second stage,the sparrow search algorithm is used to make the support vector machine converge quickly to get the optimal parameters,so as to realize the accurate topology identification for distribution networks.Based on this algorithm,a real-time topology identification platform is established by using FPGA parallel architecture and high speed and high density characteristics.Finally,the effectiveness and superiority of the proposed identification method are verified by case analysis.
Penetration of distributed renewable energy (DRE) is increasing in modern power systems. Integration of DREs have profound impact on transient voltage stability of bulk power systems, which has been observed in real-world power system event in USA and Australia. However, related studies are relatively rare in existing literatures. This paper utilizes a synthesis load model with renewables to study this issue. Two abnormal transient performances of DRE are revealed, which impact and interact with voltage of bulk power system. The performances are concluded as continuous low-voltage-ride-through (LVRT) of DRE and repeated LVRT of DRE, respectively. Sensitivities of the performances to DRE parameters are studied in weak power grid, with several novel and unexpected findings. Active power output of DRE significant influences the terminal voltage during LVRT, while impact of reactive output is not so prominent. Related results explain performance of several real power grids with high penetration of DREs.
As the proportion of wind power in new-type power systems increases year by year, its dynamic characteristics, especially fault ride-through characteristics, have a significant impact on power systems. To accurately analyze the impact of large-scale wind power on power systems, it is necessary to construct a white-box model that can characterize the actual dynamic characteristics of wind turbine. The white-box model has numerous parameters with interactive effects, and current parameter identification methods cannot achieve identification of the entire DFIG's fault ride-through, inner and outer controller parameters, limiting parameters, and electrical parameters, especially the accurate identification of parameters insensitive to external characteristics. To solve these problems, this paper constructs a frequency domain universal model for DFIG under fault ride-through conditions, which includes the DFIG itself and all controllers. The parameters are divided into four categories for step-by-step identification, proposing a categorized and integrated step-by-step identification method. The accuracy of the frequency domain universal model is verified through comparison with a simulation model, and the correctness of the proposed categorized and integrated step-by-step parameter identification method is validated by comparing the identified values with the real values.
The penetration of high-proportion renewable energy brings significant volatility and uncertainty to power grids.Thus the receiving end of the power system faces the problem of insufficient adjustable resource capacity.It requires the full utilization of a large number of flexible energy resources to participate in power system dispatch and provide auxiliary services.However,the vast number,wide distribution,and diverse characteristics of these flexible energy resources pose significant challenges to centralized dispatch and control.It is necessary to manage and dispatch these flexible energy resources in a clustered way.To accurately assess the role of clusters in the power system dispatch and control,it is essential to aggregate these flexible energy resources and evaluate their performance by using appropriate quantitative metrics based on application requirements.According to the application demands of flexible resource clusters in power system dispatch and electricity market,a quantitative metric system of flexibility for evaluating the adjustable capacity of flexible energy resource clusters is proposed.Based on their physical characteristics,these resources are categorized into three types:generator-like characteristics,storage-like characteristics,and common characteristics.For quantitative evaluation of the cluster flexibility metrics across various application scenarios,an aggregation reference model comprising an equivalent generator and an equivalent energy storage is proposed.This aggregation reference model has a clear physical interpretation,exhibits nested properties,and therefore is suitable for various time scales and energy forms.It can be used to calculate the quantitative metrics for specific application scenarios and widely applied in scenarios such as asynchronous dispatch of distributed energy resource clusters,joint optimization dispatch of integrated energy systems,and participation of virtual power plant in electricity market bidding.
