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High-voltage direct current (HVDC) systems are increasingly incorporated into today's AC power grids, necessitating optimal power flow (OPF) tools for the analysis, planning, and operation of such hybrid systems. To this end, we introduce hynet, a Python-based open-source OPF framework for hybrid AC/DC grids with point-to-point and radial multi-terminal HVDC systems. hynet's design promotes ease of use and extensibility, which is supported by the particular mathematical model and software design presented in this paper. The system model features a unified representation of AC and DC subgrids as well as a concise and flexible converter model, which enable the compact description of a hybrid AC/DC power system and its OPF problem. To support convex relaxation based OPF solution techniques, a state space relaxation is introduced to obtain a unified OPF formulation that is analogous to the OPF of AC power systems. This enables the direct generalization of relaxation-related results for AC grids to hybrid AC/DC grids, which is shown for the semidefinite and second-order cone relaxation as well as associated results on exactness and locational marginal prices. Finally, hynet's object-oriented software design is discussed, which provides extensibility via inheritance and standard design patterns, and its robust and competitive performance is illustrated with case studies. [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]

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]

A method of modifying existing grid-connected inverter models for use in droop-controlled microgrids is presented. The modification involves combination with a model of a grid-forming inverter to accurately represent the coupling between complex power, bus voltage, and frequency. The combination is performed after the individual models are linearized, adding little in terms of computational complexity. The method is applicable to any three-phase inverter operating in a grid-supporting capacity and is scalable for any number of parallel inverters at the same point of connection. To examine the modification process and its effect on model performance, a generic grid-tied inverter model is derived and used as a test case. The newly derived model is modified according to the proposed method. The validity of this process is assessed through comparisons of model predictions—both from before and after modification—to results of hardware experiments. A simple design example is given to demonstrate the application of this process in the design of inverters in distributed-generation-based microgrids. [ABSTRACT FROM PUBLISHER]