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Register a new userHybrid EMT-TS Simulation Strategies to Study High Bandwidth MMC-Based HVdc Systems
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Modular multilevel converters (MMCs) are widely used in the design of modern high-voltage direct current (HVdc) transmission system. High-fidelity dynamic models of MMCs-based HVdc system require small simulation time step and can be accurately modeled in electro-magnetic transient (EMT) simulation programs. The EMT program exhibits slow simulation speed and limitation on the size of the model and brings certain challenges to test the high-fidelity HVdc model in system-level simulations. This paper presents the design and implementation of a hybrid simulation framework, which enables the co-simulation of the EMT model of Atlanta-Orlando HVdc line and the transient stability (TS) model of the entire Eastern Interconnection system. This paper also introduces the implementation of two high-fidelity HVdc line models simulated at different time steps and discusses a dedicated method for sizing the buffer areas on both sides of the HVdc line. The simulation results of the two HVdc models with different sizes of buffer areas are presented and compared.
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Protection against dc faults is one of the main technical hurdles faced when operating converter-based HVdc systems. Protection becomes even more challenging for multi-terminal dc (MTdc) systems with more than two terminals/converter stations. In this paper, a hybrid primary fault detection algorithm for MTdc systems is proposed to detect a broad range of failures. Sensor measurements, i.e., line currents and dc reactor voltages measured at local terminals, are first processed by a top-level context clustering algorithm. For each cluster, the best fault detector is selected among a detector pool according to a rule resulting from a learning algorithm. The detector pool consists of several existing detection algorithms, each performing differently across fault scenarios. The proposed hybrid primary detection algorithm: i) detects all major fault types including pole-to-pole (P2P), pole-to-ground (P2G), and external dc fault; ii) provides a wide detection region covering faults with various fault locations and impedances; iii) is more robust to noisy sensor measurements compared to the existing methods. Performance and effectiveness of the proposed algorithm are evaluated and verified based on time-domain simulations in the PSCAD/EMTDC software environment. The results confirm satisfactory operation, accuracy, and detection speed of the proposed algorithm under various fault scenarios.
This paper proposes a computational method to efficiently and quickly estimate stability regions of droop control slopes for modular multilevel converter (MMC)-based multiterminal dc (MTDC) systems. The proposed method is based on a general small-signal model consisting of a dc grid with arbitrary topology and MMCs with dq controllers. The general small-signal model developed by a systematic way can be used for small-disturbance stability analysis. To verify the developed small-signal model, a comparison between the developed model calculated in MATLAB and the detailed switching model simulated in PSCAD/EMTDC is conducted, which demonstrates the accuracy of the developed small-signal model. Based on the eigenvalues sensitivity and the Taylor Series of eigenvalues, a set of inequality constraints are derived and used to efficiently estimate the stability regions of all coupled slopes of the droop characteristics. It is helpful for efficiently designing and adjusting the droop controller parameters for the MMC-MTDC systems. The effectiveness of the proposed method is demonstrated by the several examinations including the supremum test and the stability region sketch on accuracy and feasibility.
Generalized short circuit ratio (gSCR) for gird strength assessment of multi-infeed high voltage direct current (MIDC) systems is a rigorous theoretical extension of traditional short circuit ratio (SCR), which allows the considerable experience of using SCR to be extended to MIDC systems. However, gSCR was originally derived based on the assumption of homogeneous MIDC systems, where all HVDC converters have an identical control configuration, which poses challenges to the applications of gSCR to inhomogeneous MIDC systems. To weaken this assumption, this letter applies modal perturbation theory to explore the possibility of applying gSCR in inhomogeneous MIDC systems. Results of numerical experiments show that, in inhomogeneous MIDC systems, the previously proposed gSCR can still be used without modification, but critical gSCR (CgSCR) needs to be redefined by considering the characteristics of HVDC converter control configurations. Accordingly, the difference between gSCR and redefined CgSCR can effectively quantify the pertinent ac grid strength in terms of static voltage stability margin. The performance of our proposed method is demonstrated in a triple-infeed inhomogeneous LCC-HVDC system.
Self-triggered control (STC) is a well-established technique to reduce the amount of samples for sampled-data systems, and is hence particularly useful for Networked Control Systems. At each sampling instant, an STC mechanism determines not only an updated control input but also when the next sample should be taken. In this paper, a dynamic STC mechanism for nonlinear systems is proposed. The mechanism incorporates a dynamic variable for determining the next sampling instant. Such a dynamic variable for the trigger decision has been proven to be a powerful tool for increasing sampling intervals in the closely related concept of event-triggered control, but was so far not exploited for STC. This gap is closed in this paper. For the proposed mechanism, the dynamic variable is chosen to be the filtered values of the Lyapunov function at past sampling instants. The next sampling instant is, based on the dynamic variable and on hybrid Lyapunov function techniques, chosen such that an average decrease of the Lyapunov function is ensured. The proposed mechanism is illustrated with a numerical example from the literature. For this example, the obtained sampling intervals are significantly larger than for existing static STC mechanisms. This paper is the accepted version of [1], containing also proofs of the main results.
In power system dynamic simulation, up to 90% of the computational time is devoted to solve the network equations, i.e., a set of linear equations. Traditional approaches are based on sparse LU factorization, which is inherently sequential. In this paper, an inverse-based network solution is proposed by a hierarchical method for computing and store the approximate inverse of the conductance matrix in electromagnetic transient (EMT) simulations. The proposed method can also efficiently update the inverse by modifying only local sub-matrices to reflect changes in the network, e.g., loss of a line. Experiments on a series of simplified 179-bus Western Interconnection demonstrate the advantages of the proposed methods.
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