Kevin Paul Schneider

Rapid integration of distributed energy resources, such as solar photovoltaic (PV), can lead to overvoltage challenges in distribution feeders due to reverse power flow and low power factor at the substation interface. While existing literature extensively explores the utilization of smart inverter capabilities for reactive power flexibility using volt-var curve (VVC), obtaining time-varying operating points of such curves in real-time is challenging due to computational demands and communications requirements. Similarly, employing optimizationbased approaches for reactive power control and active voltage regulation in large-scale distribution feeders is difficult due to the complexity of the problem and the challenges in effectively engaging customer-owned resources. This paper proposes a twostage strategy to harness smart inverters for reactive power support. The first stage formulates short-term planning by optimally designing VVCs (sub-daily basis) for large-scale solar PVs based on projected system needs and communicating optimal curves to smart inverters in advance. Subsequently, the second stage employs a transactive-based method to involve customerowned PVs for reactive power support, effectively enhancing overall system performance and addressing real-time demands. The efficacy of this approach will be demonstrated using realworld distribution circuits provided by Vermont Electric Power Company (VELCO) and Vermont Electric Cooperative (VEC).

The increased installation of renewable grid-edge assets into an already complex power distribution system has driven extensive development of distributed optimal power flow (OPF) methods to coordinate such assets. However, existing distributed optimization algorithms applied to unbalanced systems require many communication-rounds among the distributed agents and may pose convergence challenges. Besides, the communication network parameters also significantly impact the algorithm's performance. In this paper, we propose a scalable, equivalent network approximation-based, distributed OPF method that employs a communication infrastructure using cyber-physical co-simulation platform to coordinate grid-edge renewable assets for three-phase unbalanced distribution systems. Additionally, the robustness of the proposed approach is validated under stressed communication scenarios. The results are thoroughly compared with the state-of-the-art algorithms and equivalent centralized optimal power flow (C-OPF) problems for medium IEEE-123 Bus Test system and large-scale PNNL R3-12.47-2 feeder distribution test systems.

With the emergence of low-inertia microgrids powered by inverter-based generation, there remains a concern about the operational resilience of these systems. Grid-forming inverters (GFMs), enabled by various device-level (primary) and system-level (secondary) control methods, are poised to play a significant role in achieving certain operational objectives, such as the effective utilization of clean energy resources while maintaining stability. However, despite the recent advances in GFMs, there is a lack of suitable controls that can ascertain resilience-constrained operations, like maintaining critical operational safety limits during transients under various cyber-physical disruptions. In this work, we develop decentralized autonomous controllers (DACs) that enforce resilience-constrained operation via local, minimally invasive adjustments (e.g., changes in set-points) while co-existing within the hierarchy of existing (primary and secondary) controls. The DACs work autonomously by sensing only local GFM measurements and act only when operational resilience constraints are violated. The proposed DAC scheme is computationally efficient (only algebraic computations), which enables fast, real-time execution and demonstrates the efficacy of the proposed control framework on GridLAB-D-HELICS-based control-grid co-simulations on the IEEE 123-node networked microgrid. Finally, we show how the developed DACs empower the grid by utilizing the available resources entirely to ensure resilience (maintain frequency safe limits).

The increasing deployment of distributed energy resources (DERs) and microgrids (MGs) in power distribution systems has enabled the adjustment of reactive power consumption as seen at the substation, which can be used to provide voltage support for the bulk power system (BPS). Leveraging this new capability will provide greater resiliency to the power system as a whole. The goal of this paper is to develop and compare three different algorithms, namely distributed optimal power flow, distributed consensus algorithm, and fully decentralized collaborative autonomy for unbalanced distribution systems for microgrid coordination. These algorithms use networked MGs to support the BPS voltage when a contingency at the bulk grid results in abnormally low voltages, which may be a precursor to voltage collapse. Our comparative analysis includes both qualitative and quantitative assessments of the three algorithms and a discussion of the trade-offs between the decentralized and distributed methods in normal and disrupted conditions. Each algorithm was evaluated on the modified IEEE 13-bus system and a real power distribution system in North America that encompasses more than 4500 buses. Each algorithm excels differently and may be suited for different scenarios depending on the condition, operations, and priorities of the power and communication systems.

Islanded microgrids may experience voltage and frequency instability due to uncontrolled state changes of voltage regulation devices and inaccurate demand forecasts. Uncontrolled state changes can occur if optimal microgrid restoration and dispatch algorithms, used for generating control commands for distributed energy resources, do not incorporate the behavior of automatic controllers of voltage regulation devices. Inaccurate demand forecasts may be encountered since post-outage demand of behind-the-meter net metered (NM) loads can vary significantly from their historical NM profiles. This paper proposes an optimization formulation which allows optimal control of voltage regulators and capacitor banks without remote control and communication capabilities. A generalized demand model for NM loads is proposed which incorporates the cold load pickup phenomenon and their time varying post-outage demand in accordance with the IEEE 1547 standard. The time dependent optimal control formulation and the NM demand model are integrated in a sequential microgrid restoration algorithm by linearization of the involved logic propositions. A detailed case study on the unbalanced IEEE 123-node test system in OpenDSS validates the effectiveness of the proposed approach.

Reconfiguring power distribution after an outage is commonly performed to restore service to the maximum number of end-use customers. However, the ability to reconfigure the system can be constrained due to voltage and thermal limits on equipment. This paper presents two transactive approaches that can be deployed to increase operational flexibility through mitigation of local constraints (voltage and thermal) by engaging the reactive-power capabilities of non-utility resources to increase the number of switching options and load restoration. The first approach enables energizing additional line segments, and the second approach enables reducing the voltage differential across reclosers enabling additional switching options. The developed methods are demonstrated on a model of an operational 12.47-kV distribution system with four distribution circuits and 3000+ electrical nodes. Simulations are conducted using the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS)-based framework to evaluate the effectiveness of the two methods to improve system reconfiguration. The performance of the developed transactive algorithms is evaluated under a range of operating conditions, including both normal and outage conditions. The proposed transactive approaches resulted in additional switching options for the distribution system operator, which, in-turn, yielded to an increase in additional load restored thereby improving the resiliency of the distribution system.

This document is a summary of a report prepared by the IEEE PES Task Force (TF) on Microgrid (MG) Dynamic Modeling, IEEE Power and Energy Society, Tech. Rep. PES-TR106, 2023. In this paper, the major issues and challenges in microgrid modeling for stability analysis are discussed, and a review of state-of-the-art modeling approaches and trends is presented. In the context of the IEEE 1547 standard, the document covers issues associated with component models for MG dynamic studies and simulations, including generator and grid modeling, full and average converter models, unbalanced and balanced system conditions, dynamic and static loads, protection requirements, and detailed and simplified controls considering communications delays, packet losses, and security issues. Considering the future integration of grids and MGs to form broad integrated networks, a discussion is presented of the use of phasor vis-à-vis electromagnetic transient simulation tools for MG dynamic stability studies, as well as modeling scale-up issues and MG equivalent models. Specifically white-, grey-, and black-box models, are presented. This TF paper and companion report constitute a modeling guide for R&D groups working on developments and standards of MGs with a focus on stability issues.