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.

This paper investigates the stability of low-inertia microgrid systems with two control strategies that have different percentages of grid-forming (GFM) inverters. The first control strategy has approximately 50% GFM inverters, and all the battery inverters are working in GFM control mode. Originally, the second control strategy has approximately 10% GFM inverters, with only two battery inverters working in GFM control mode and the rest working in grid-following (GFL) PQ control mode based on current control, which cannot stabilize the microgrid system. Then, the second control strategy is modified to change the GFM inverters from droop control to isochronous control and the GFL battery inverters from traditional current control to voltage control for power control. Both control strategies can maintain system stability; however, the first control strategy can better handle contingency events. The study indicates that 1) a microgrid system with a higher percentage of GFM inverters has better stability; and 2) a microgrid with a lower percentage of GFM inverters can have poor stability, but improved control strategies in inverters can improve system stability. This study improves the understanding of how different percentages of GFM inverters and inverter control strategies affect the system stability of low-inertia microgrids.

Consensus-based distributed algorithms are well suited for coordination among agents in a cyber-physical system. These distributed schemes, however, suffer from their vulnerability to cyber attacks that are aimed at manipulating data and control ow. In this article, we present a novel distributed method for detecting the presence of such intrusions for a distributed multi-agent system following ratio consensus. We employ a Max-Min protocol to develop low cost, easy to implement detection strategies where each participating node detects the intrusion independently, eliminating the need for a trusted certifying agent in the network. The effectiveness of the detection method is demonstrated by numerical simulations on a 1000 node network to demonstrate the efficacy and simplicity of implementation.