Traditional protection schemes face significant challenges when applied to microgrids with high penetrations of renewables with inverter-based resources (IBRs). The proliferation of advanced sensing and communication technologies has generated copious data, offering an opportunity to overcome these limitations using data-driven machine learning approaches. This work proposes a novel approach based on a support vector machine (SVM) for detecting faults within a 100% renewable microgrid. The approach encompasses a systematic offline training stage for the development of a linear SVM-based fault detection algorithm. This process covers offline data collection from the microgrid under study, the extraction of features such as positive- and negative-sequence components and the total harmonic distortion of the voltage and current measurements of the relays, and the design of the linear SVM-based classifier. During the online implementation, however, different classifiers can exhibit asynchronicity in detecting the fault inception at different subcycle-to-cycle period-level delays. To circumvent this asynchronicity issue, a separate algorithm is developed for each relay to estimate the fault inception time as close to the real fault time. The performance of the proposed SVM-based synchronized fault detection method is evaluated using online time-domain simulation studies on a microgrid test system. The results corroborate the reliability of the fault detection scheme when tested under various fault cases (fault types, locations, and impedances) and non-fault cases during both grid-tied and islanded operation modes.

This paper introduces a versatile electromagnetic transient dynamic model for grid-forming inverter-based resources using the PSCAD software platform. The model offers a range of features, including the ability to choose from different types and combinations of DC sources, such as ideal DC source modules, photovoltaic (PV) modules, battery modules, and combined PV and battery modules. It also allows for the selection of either switching or averaged inverter models. The model encompasses various controller algorithms, including Pf/QV-based droop control, virtual synchronous machine-based control, and conventional outer-voltage-inner-current control in different domains, such as the dq domain, the αβ domain, and sequence-domain control in the dq domain. Additionally, it provides options for different current-limiting schemes, such as saturation-based and latching-based current limiters, along with anti-windup protection. Moreover, the model is adaptable to different MVA ratings and complies with the IEEE Std. 2800 requirement of negative-sequence current leading negative-sequence voltage 90◦–100◦for interfacing transmission systems. The model’s flexibility in power circuits, its multifunctional capabilities in operation and control, and its detailed modeling of controls and dynamics make it suitable for the study of various power system aspects requiring detailed modeling, such as investigating transient stability for interconnection studies, and impacts on protection systems for fault studies.

A distributed controller for secondary control problems in microgrids with grid-forming (GFM) inverter-based resources (IBRs) is developed. The controller is based on distributed optimization and is synthesized and implemented distributively enabling each GFM IBR to utilize decentralized measurements and the neighborhood information in the communication network. We present a convergence analysis establishing voltage regulation and reactive power sharing properties. A controller-hardware-in-the-loop experiment is conducted to evaluate the performance of the proposed controller. The experimental results corroborate the efficacy of the proposed distributed controller for secondary control.

We consider the framework of distributed aggregation of Distributed Energy Resources (DERs) in power networks to provide ancillary services to the power grid. Existing aggregation schemes work under the assumption of trust and honest behavior of the DERs and can suffer when that is not the case. In this article, we develop a distributed detection scheme that allows the DERs to detect and isolate the maliciously behaving DERs. We propose a model for the maliciously behaving DERs and show that the proposed distributed scheme leads to the detection of the malicious DERs. Further, augmented with the distributed power apportioning algorithm the proposed scheme provides a framework for resilient distributed power apportioning for ancillary service dispatch in power networks. A controller-hardware-in-the-loop (CHIL) experimental setup is developed to evaluate the performance of the proposed resilient distributed power apportioning scheme on an 8-commercial building distribution network (Central Core) connected to a 55 bus distribution network (External Power Network) based on the University of Minnesota Campus. A diversity of DERs and loads are included in the network to generalize the applicability of the framework. The experimental results corroborate the efficacy of the proposed resilient distributed power apportioning for ancillary service dispatch in power networks.

Power-hardware-in-the-loop (PHIL) simulations of grid-forming (GFM) inverter systems facilitate the testing of drastic scenarios, such as on-grid to off-grid transitions and islanded microgrid operations without a stiff grid. To the authors’ best knowledge, most studies in the literature focus on PHIL simulations for grid-following inverter systems. Only a few studies focus on GFM inverters, and those are challenging and problematic, especially for high-power applications. This article proposes a novel PHIL simulation platform that enables interfacing high-power GFM inverter systems. The paper proposes the concept of a virtual GFM inverter as a part of the proposed PHIL interface. This addition of a virtual GFM inverter in the PHIL interface expands the conventional ideal transformer model (ITM) method and enables it to overcome the issues of instability of existing ITM methods. In the validation stage, a PHIL experiment is conducted on a three-phase, 480-V, 125-kVA GFM inverter system with the proposed interfacing method. The results corroborate that the proposed PHIL simulation method performs well and is stable for GFM inverter systems.

For smooth transition from islanded mode to grid-tied mode, synchronization to the incoming grid is required for any islanded microgrid. This paper is proposing a novel active synchronization method for such islanded microgrids. In this method, the proposed synchronization controller compensates the phase angle and voltage magnitude difference between islanded microgrid side and the incoming grid side to zero by adjusting the droop laws of all grid-forming (GFM) inverter systems of the microgrid dynamically via secondary control layer of microgrid hierarchical control architecture. It is analytically shown that compensation on only phase angle and voltage magnitude is sufficient for synchronization as frequency is compensated by this proposed method indirectly by the phase angle compensation. A systematic approach for tuning the proposed synchronization controllers are provided. For validation, a controller hardware-in-the-loop-based real-time simulation is conducted using OP5700 RT-simulator manufactured by OPAL-RT on a 3-phase, 480V, 500kVA, 55-bus urban microgrid system with 6 GFM inverters where control of 2 GFM inverters are realized on low-cost Texas-Instruments TMS28379D Delfino controller boards. The proposed method is relatively fast and enables a smooth re-connection of microgrid with grid with less transients.