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With the rapid development of China high-speed railway, the low frequency oscillation (LFO) of electrical quantities appears more often recently and leads to some severe problems of train operation. To improve the traction line-side converter control and suppress the phenomenon economically and effectively, a model-based predictive direct power control (MPDPC) approach is proposed in this paper. The approach adopts a discrete-time model of traction line-side converter in d–q reference frame to predict the future values of the input active and reactive power. The optimal switching state is selected by minimizing a cost function of power to evaluate the power errors at the next sampling time. Through the theoretical analysis and simulations, the performance of MPDPC is compared with traditional transient direct current control (TDCC) that is widely adopted in China Railway High-Speed 3 electric-multiple-unit. The real-time online simulations based on Real-Time Laboratory (RT-LAB) are also realized to further validate the results. Moreover, two vehicle-grid cascade simulation systems are constructed, and the LFO suppressing capability of MPDPC and TDCC is compared. Finally, the steady-state characteristic, dynamic characteristic, and LFO suppressing capability of MPDPC are demonstrated through the analysis of key performance indexes. [ABSTRACT FROM AUTHOR]

A load model is one of the most important elements in power system simulation and control. Recently, the constant impedance, constant current, and constant power load in combination with the induction motor load have been widely used as the composite load model, whose parameters are all identified from the field measurements in measurement-based load modeling practices so far. However, there is virtually no research conducted on whether all these parameters could really be identified. This paper investigates the possibility on reducing the number of composite load model parameters to be identified from field measurements. This paper first shows that direct application of the IEEE load motor parameters in the composite load model may be inadequate on describing the load dynamics over different operating status. Then the perturbation method is used to derive the trajectory sensitivities of the equivalent motor parameters, based on which the reduction on the identified parameters of the composite load model is presented. Two cases of measurement-based load modeling in North China and Northeast China are studied to illustrate the validity of the reduction method. It is shown that the reduction does not lose the model's capability on describing the load dynamics. The reduction on the number of identified parameters not only provides a possible way to solve the multi-valued load model problem based on the current practices on measurement-based load modeling, but it also facilitates building of the load model with more components included in it. Meanwhile, reducing the identified parameters reduces the identification time; thus, the proposed strategy significantly enhances the efficiency of the load modeling work. [ABSTRACT FROM AUTHOR]

The dynamic behavior of phasor measurement units (PMUs) is not only the key point to dynamic phasor algorithm improvement but also the basis for the successful implementation of PMUs in power system dynamic security monitoring and control. In this paper, the dynamic performance of PMUs is evaluated, and their dynamic behaviors are analyzed. PMUs from the four largest Chinese manufacturers are tested through the established PMU test system, and their dynamic performance is comprehensively evaluated. The dynamic behaviors of the PMUs are also analyzed. Analysis shows that the spectral leakage and the averaging effect of the discrete Fourier transform (DFT) under dynamic conditions are the key reasons that lead to their dynamic behaviors. The theoretical results are consistent with the experimental data and the simulation. Finally, to eliminate the spectral leakage, the DFT with a digital low-pass filter is adopted to obtain more precise phasor measurements. [ABSTRACT FROM PUBLISHER]

Load model is one of the most important elements in power system simulation and control. Based on more than 20 years of practice using load characteristic recorders in the measurement-based load modeling, this paper proposes the Expectation Composite Load Model to predict unseen data. The methods for load bus classification and parameter identification are also provided. The generalization capability of the proposed load modeling is validated by the measured load dynamics and system dynamics during two three-phase short circuit tests of the NE power grid in China. In order to evaluate the measurement-based load model, the Probabilistic Collocation Method (PCM) is applied to quantitatively analyze uncertainties of the simulation responses raised by the parameters. [ABSTRACT FROM AUTHOR]

Intelligent transportation systems (ITSs) have become increasingly important for public transportation in Shanghai, China. In response, ShanghaiGrid (SG) aims to provide abundant intelligent transportation services to improve traffic conditions. A fundamental service in SG is to locate the nearest desirable vehicles for users. In this paper, we propose an innovative protocol called ANTS to locate a desirable vehicle close to the querying user. The protocol finely mimics the efficient searching strategy adopted by a lost ant searching for its nest. Taking query locality into account, ANTS can retrieve the closest vehicles satisfying the query with high probability but incurs small query latency and modest network traffic. ANTS is a fully distributed and robust protocol and, therefore, has good scalability. Extensive simulations based on the real road network and the trace data of vehicle movements in Shanghai demonstrate the efficacy of ANTS. [ABSTRACT FROM AUTHOR]