This paper proposes a comprehensive and efficient electromagnetic transient model of a switched reluctance motor drive system through a circuit-based representation. The machine’s model consists of interconnected electrical, nonlinear magnetic, and mechanical circuits. The nonlinear magnetic circuit includes nonlinear permeances to represent the ferromagnetic core, and variable permeances to model the airgap and the machine’s rotation. An analytical function is used to determine airgap permeance values at each time-step and is verified by a circuit-based implementation of the tooth-contour method. The proposed electromagnetic transient model is verified by the finite element-based model. Furthermore, the proposed machine model is integrated with a simultaneous solution within an external power system, including batteries, power electronics converters, and their related control, allowing for studying various transient phenomena and their effects on the performance of each component.

The optimal power flow (OPF) problem focuses on the operational efficiency of electric power systems. Modern grids include a variety of devices that are often omitted in traditional OPF formulations, namely, different types of generators, transformers, or power electronics-based devices. The modified and augmented nodal analysis (MANA) extends the traditional nodal analysis by expressing circuit equations in a generic sparse matrix representation. The MANA approach can seamlessly accommodate constraints from various types of devices commonly encountered in modern networks. This, in turn, allows their straightforward inclusion as constraints in OPF by modelling them through MANA using their current and voltage equations. This work proposes a new OPF formulation based on MANA and the corresponding power flow constraints, which we refer to as MANA-OPF. The non-convex MANA-OPF is solved using a nonlinear solver, namely, IPOPT in Julia. The formulation is tested on several test cases. The results are compared to a standard approach used by PowerModels.

The Impedance-based stability assessment (IBSA) methods are widely used to identify control interaction issues between inverter-based resources (IBRs) and transmission grid. The IBR impedance models can be obtained and analyzed in different reference frames and forms, such as positive sequence single-input single output (SISO) and dq-frame multi-input multi-output (MIMO) forms. Accordingly, different IBSA methods should be applied. In this paper, six IBSA methods are reviewed, compared, and their applications are demonstrated. Merits and shortcomings of each method are discussed, and recommendations are presented for engineers and researchers. The IBSA results are compared with electromagnetic transient (EMT) simulations in two test systems involving doubly-fed induction generator (DFIG) and full-size converter (FSC)-based wind parks (WPs).

This paper presents state-space models for both doubly-fed induction generator (DFIG) and full-scale converter (FSC)-based wind parks (WPs) that can be used to investigate the WP control interaction (CI) problems. The presented models are tested on a series capacitor compensated WP benchmark which exhibits different type instability phenomenon for DFIG and FSC-based WP connection scenarios. The obtained results are validated through simulations using EMTP®. The presented models can be used to develop a state-space analysis (SSA) tool for large-scale multi WP systems to identify the potential WP related instability conditions.

Accurate initialization of large-scale power systems involving inverter-based resources can significantly reduce the computation time needed for reaching steady-state conditions in electromagnetic transient simulations. This paper presents a novel method for initializing detailed Photovoltaic Park models for electromagnetic transient simulations. The proposed approach uses the load-flow simulation results of the system to initialize electrical components and control variables of the PV park. The validity of the proposed initialization is demonstrated through the EMT simulations of aggregated and detailed representations of the PV park and its integration into a large-scale power system via three case studies. The results indicate that the existing initialization method significantly reduces the computational time required to reach steady-state, compared to the existing technique.

Impedance-based stability assessment (IBSA) is an effective method to study sub-synchronous control interaction (SSCI) with inverter-based resources (IBRs) in modern power systems. An IBR's required frequency-dependent impedance model can be obtained via the positive sequence scanning method. In this paper, single-sinusoidal signal and multi-sinusoidal signal-based methods for frequency scanning are investigated and evaluated. To benefit from the advantages of both schemes, hybrid scanning is proposed including perturbation signal, amplitude, and frequency segmentation settings. Additionally, a modified quadratic phase shift scheme is proposed for reducing the high magnitudes of multi-sinusoidal signals. All methods are validated and compared using the average value model of a doubly fed induction generator. The guidelines and recommendations are provided for the proper usage of the proposed hybrid scanning in the sub-synchronous frequency range.

One key factor in the operation of droop-controlled islanded microgrid (IMG) systems is its maximum loadability. In this paper, the effect of droop controllers on loadability of IMGs is studied. Moreover, the effect of different unbalanced conditions, droop functions, reactive droop coefficients, and also inverse droop on the IMG loadability are taken into account. The proposed model is examined on an unbalanced 38-bus and IEEE 906-bus ac IMGs. The findings substantiate that for conventional and inverse droop cases, respectively, reactive (Q-droop) and active droop functions (P-droop), due to their intentional voltage deviation, highly affect the IMG loadability.

Rigorous evaluation of a synchrophasor network in terms of communication network quality, cybersecurity, and phasor data concentrator (PDC) performance is presented. To this aim, a cosimulation platform is designed based on the multiagent environment for complex system cosimulation platform. The proposed platform is characterized by particular features including scalability (no limitation in terms of nodes/buses of communication/power systems), compatibility with the functional mock-up interface standard, and capability of synchronized integration of any two abstract simulators (in this article, NS-3 for communication network and MATLAB/Simulink for power system). The simulations are performed for the detailed model of the IEEE-34 bus distribution network including phasor measurement units and the PDC. The simulations include (1) evaluation of widely used synchrophasor communication technologies (i.e., user datagram protocol and transmission control protocol), (2) evaluation of the PDC performance under both relative and absolute wait time logics, and (3) assessment of cybersecurity vulnerabilities of the synchrophasor network. The proposed platform can be utilized for implementation and evaluation of communication technologies/protocols of synchrophasor networks in terms of bandwidth, packet missing, latency, and cybersecurity vulnerabilities. Data pushing mechanism of the PDC can be also evaluated using the proposed platform.

Distributed energy resources (DERs) often rely on renewable sources whose random power fluctuations bring about voltage disturbances in distribution networks. Under such circumstances, voltage regulation through centralized control of DERs requires reliable detection and coordination mechanisms. This article proposes a new data-driven approach for event-triggered and coordinated control of DERs based on features of voltage disturbances. Synchrophasor datasets are processed to construct disturbance matrices that quantify spatio-temporal features of voltage disturbances. The estimated features are employed in clustering and control of DERs to suppress incipient events before exceeding a critical time. The proposed approach is tested in the IEEE 123-bus network, which has 15 solar photovoltaic sources with battery energy storage systems. The simulation results validate reliability and efficiency of the proposed method, and confirm that feature extraction combined with coordination of DERs can improve reliable and economic operation of distribution grids with renewables.