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This paper develops a comprehensive dynamic-phasor-based small-signal model for the modular multilevel converter (MMC) system under unbalanced grid conditions, which takes into consideration the dynamics of the MMC system under a balanced grid condition as well as the other emerging internal harmonics produced by the unbalanced grid components and more complex controllers. The small-signal model is validated by comparing the time-domain responses from a detailed electromagnetic transient (EMT) simulation in PSCAD/EMTDC. Based on the eigen-analysis and PSCAD-based time-domain simulation studies, this paper reveals the poorly damped modes that cause unstable oscillations in MMC system under the unbalanced grid conditions. From the results, more poorly damped modes involved in the internal harmonics are emerging under unbalanced grid conditions compared with the modes under the balanced grid conditions, and can highly impact the system dynamic behaviors by the selection of the control parameters. It is also shown that, under the unbalanced grid conditions, the feasible region of the control parameters of the vector current control gets narrowed indicating the reduction of the stability margin, smaller (larger) value of proportional (integral) gain of the circulating current suppressing controller can enhance the system stability, and larger values of the proportional and integral gains of the negative-sequence current suppressing control can result in the harmonic instability of the MMC system. Besides, the parameters of multiple complex-coefficient filters for positive- and negative-sequence components extraction also have a big impact on the small-signal stability of the MMC system and are required to be properly selected. [ABSTRACT FROM AUTHOR]

Measurements from the on-board systems of marine vessels are increasingly available for data analysis and are growing in importance as the ship industry enters a phase of digitalization. The purposes of the data analysis from vessels in operation include the verification of the power system design in general and improvement of the electrical power load analysis in particular. In this paper, we show how to extract valuable information from the data-driven operational profile analysis, which reveals the real power demand, and how the vessel was operated. Using the real power range analysis, we emphasize the significance of rarely occurring high power demands, which are critical for power system design and optimization. We propose a methodology for the quantification of variability in the generated power, which explains the tails of probability distributions of a power signal based on signal decomposition. The proposed methodology makes use of the data and it can facilitate the selection of the optimal size, number, and configuration of generators or batteries when designing new power systems. Measurements from a data collection system are used to demonstrate the methodology for dynamic positioning mode of the operation of a platform supply vessel. [ABSTRACT FROM AUTHOR]

This paper describes the use of large electric grids in university electric power system courses. Since much actual power system information is not publicly available, the application of public domain synthetic grids developed by the authors is presented including a 2000-bus grid. Discussion of the educational applications utilized in a senior level class are given for power flow analysis and sensitivity, economic dispatch, contingency analysis, optimal power flow (OPF), security-constrained OPF, transient stability, and real-time dynamic operations. In each of these, the application of the large synthetic grids give students insights and experience with cases closer to actual power systems in complexity and size. [ABSTRACT FROM AUTHOR]

The paper proposes a new adaptive approach to power system model reduction for fast and accurate time-domain simulation. This new approach is a compromise between linear model reduction for faster simulation and nonlinear model reduction for better accuracy. During the simulation period, the approach adaptively switches among detailed and linearly or nonlinearly reduced models based on variations of the system state: it employs unreduced models for the fault-on period, uses weighted column norms of the admittance matrix to decide which functions to be linearized in power system differential-algebraic equations for large changes of the state, and adopts a linearly reduced model for small changes of the state. Two versions of the adaptive model reduction approach are introduced. The first version uses traditional power system partitioning where the model reduction is applied to a defined large external area in a power system and the other area defined as the study area keeps full detailed models. The second version applies the adaptive model reduction to the whole system. The paper also conducts comprehensive case studies comparing simulation results using the proposed adaptively reduced models with the linearly reduced model and coherency-based reduced model on the Northeast Power Coordinating Council 140-bus 48-machine system. [ABSTRACT FROM AUTHOR]

The system frequency response (SFR) model describes the average network frequency response after a disturbance and has been applied to a wide variety of dynamic studies. However, the traditional literature does not provide a generic, analytical method for obtaining the SFR model parameters when the system contains multiple generators; instead, a numerical simulation-based approach or the operators’ experience is the common practice to obtain an aggregated model. In this paper, an analytical method is proposed for aggregating the multi-machine SFR model into a single-machine model. The verification study indicates that the proposed aggregated SFR model can accurately represent the multi-machine SFR model. Furthermore, the detailed system simulation illustrates that the SFR model can also accurately represent the average frequency response of large systems for power system dynamic studies. Finally, three applications of the proposed method are explored, with system frequency control, frequency stability, and dynamic model reduction. The results show the method is promising with broad potential applications. [ABSTRACT FROM AUTHOR]

Interarea power oscillation damping enhancement in large interconnected power systems is often accomplished using supplementary controls at the synchronous machines involved and with the use of flexible ac transmission system devices. The power system literature has demonstrated that wide area signals could be more effective than the local signals for these controllers. In some cases where phasor measurement units are used, all the required control signals may not be available. To alleviate these cases, control signals are obtained using estimated signals from a “dynamic state estimator,” and a robust supplementary controller is deployed. In this paper, the cited strategy is illustrated using a static var compensator. The feasibility of the proposed method has been demonstrated on the IEEE 50-generator test system. [ABSTRACT FROM AUTHOR]

Power system simulation is an important means to study the dynamic behavior, to ensure the safety and stability, and to optimize the operation of a power grid. Pure physical simulation and digital simulation have their own advantages and disadvantages. A three-phase four-wire hybrid simulation platform integrating the advantages of both the digital simulation and physical simulation is developed by combining the physical simulation system and real-time digital simulator. The platform is rated at 400 V and 50 kVA with the short-circuit capacity of 500 kVA and can supply ten times the rated current to support the simulation of various short-circuit faults. An improved interface algorithm based on an ideal transformer model is proposed to extend the stability region of a hybrid simulation. Hybrid simulation experiments are conducted under two cases, and the comparison with the digital simulation demonstrates the performance of this platform and the potential applied to a modern power system. This platform has been equipped in a key laboratory of smart power grid technology. [ABSTRACT FROM PUBLISHER]