This article presents a low-voltage-stress asymmetric auxiliary resonant commutated pole (AARCP) topology that achieves zero-voltage switching (ZVS) for all main switches. As inverter penetration in future grids increases, high efficiency becomes critical; however, mitigating hard-switching losses remains challenging, which makes soft-switching techniques increasingly attractive. The proposed AARCP can be applied to a wide range of soft-switched inverter applications and enables ZVS without increasing the voltage stress on the main devices. The auxiliary MOSFET is subjected to only a small voltage stress and is turned off under zero-current switching (ZCS). Because the auxiliary zero-voltage-transition (ZVT) path conducts for only a small fraction of the switching period, its power consumption remains modest. The paper details the design and operation of the ZVT circuit and provides a component-level loss breakdown. A $500~\rm W$, $100~\rm kHz$ AARCP prototype using silicon carbide (SiC) devices is built to validate the analysis. Experimental results confirm full ZVS of the main switches and demonstrate a substantial efficiency gain for the ZVT commutation pole over hard switching, from $95.79\,\%$ to $98.75\,\%$ (for the chosen device with low on-state resistance), thereby highlighting the effectiveness and scalability of the proposed topology.

The growing incorporation of power electronics into the electricity distribution grid presents considerable difficulties for measuring real-time power. This is due to the injection of non-sinusoidal currents by various sources such as renewables, storage systems, and electric vehicle chargers. Although the significance of precise power measurement for various purposes such as billing, fault detection, and grid support is well recognized, current techniques face challenges to accurately quantifying power other than active power in distorted conditions. Existing solutions rely on the assumption of voltage and current pure sinusoidal behavior. Others, based on spectral decomposition, produce lagged or time-sparse results. This work aims to fill the existing gap in knowledge by examining different methods deemed capable of calculating power in real-time, and confront them against the IEEE 1459 standard, which is the most recent effort to clarify reactive power offline measurement. The focus is on assessing their computational requirements and accuracy in both steady-state and transient tests. Conclusively, the Fryze's approach was found to be the most effective in producing a result that exactly matches the "non-active power" defined by the IEEE standard with maximum relative error of 0.5 %. Nevertheless, it exhibits slow response (more than one fundamental cycle) in scenarios where reactance is dominant, and it incurs the highest computational expense, requiring up to 23.5 % CPU usage, well above the 1.32 % and 2.49 % of the Hilbert Power and Instantaneous Power counterparts. This discovery identifies important traits that future methods should consider considering the increasing prevalence of renewable energy and nonlinear loads.

Voltage-power factor (Volt-PF) control is introduced and compared with the popular voltage-reactive power (Volt-VAr) control for feeder voltage management. An inherent limitation of the Volt-VAr control is that the reactive power (Q) demanded from the distributed energy resources (DERs) is only a function of the terminal voltage and not the DER active power (P). This leads to an unfair allocation of the burden of Q support among the DERs, in the sense that those DERs generating lower P, and hence contributing less to overvoltage issues, may be required to provide more than their share of Q support, and operate at a very low power factor (PF). The proposed volt-PF scheme, where the Q support is inherently a function of both the voltage and P of the DERs, ensures fair allocation of the Q support burden and ensures that all the DERs operate at a high PF (0.9 to 1). The performance of the proposed scheme is validated through extensive static and dynamic simulations on a real, large (8000+ nodes) feeder with very high penetration (>200%) of DERs. The implementation of the proposed scheme in new and existing commercial hardware inverters is described.

Global efforts to reduce carbon emissions are driving a shift from traditional fossil fuel-based energy sources to inverter-based resources (IBRs) in power systems. Although IEEE Standard 2800-2022 has recently been approved, adoption is still in its early stages, and many IBR models have not yet integrated its requirements. This paper introduces a novel sequence-based current limiting method for IBRs, designed to enhance grid support by maximizing power injection while maintaining IBR current limits and meeting the LVRT requirements outlined in IEEE Standard 2800-2022. An electromagnetic transient simulation of an IBR plant using DIgSILENT PowerFactory demonstrates the proposed method’s performance across various case studies involving different fault types.

Adding photovoltaic (PV) systems in distribution networks, while desirable for reducing the carbon footprint, can lead to voltage violations under high solar-low load conditions. The inability of traditional volt-VAr control in eliminating all the violations is also well-known. This paper presents a novel coordinated inverter control methodology that leverages system-wide situational awareness to significantly improve hosting capacity (HC). The methodology employs a real-time voltage-reactive power (VQ) sensitivity matrix in an iterative linear optimizer to calculate the minimum reactive power intervention from PV inverters needed for mitigating over-voltage without resorting to active power curtailing or requiring step voltage regulator setting changes. The algorithm is validated using the EPRI J1 feeder under an extensive set of realistic use cases and is shown to provide 3x improvement in HC under all scenarios.

Motivation: High penetration of distributed energy resources (DERs) can lead to overvoltage and thermal violations, miscoordination of protection devices and potential adverse control interactions. The challenges are exacerbated by a lack of operator situational awareness of behind-the-meter DERs, and T&D interactions. Furthermore, the large attack surface of a DER environment creates significant cyber security challenges. The motivation is to address these barriers. Project goal: The main goal is to enable extreme levels of DERs in distribution systems while simultaneously enhancing their reliability and resiliency. This is achieved by a data-driven approach for operation, planning and control of distribution systems with total situational awareness and real-time DER control enabled by a network of edge intelligent devices, a cloud-based analytical platform, and secure communications. Major accomplishments: Development and validation of (1) integrated transmission and distribution (T&D) dynamic analysis framework for high penetration DER environment, (2) advanced edge intelligent device (EID) as a vendor-agnostic platform, (3) cloud-based, scalable, analytical and visualization platform called the end-to-end solar energy optimization platform (eSEOP), (4) end-to-end communication architecture, (5) strategies for real-time control of DERs through optimal dispatch from eSEOP and EIDs, (6) a new feeder voltage management concept called volt-PF control, (7) deep-learning based dynamic hosting capacity analysis methods, and (8) intrusion and anomaly detection systems for attack-resilient DER cyber physical system, and cyber situational awareness platform. Contributions to the understanding of the area investigated: The mutual impact of sub-transmission and distribution systems especially during various fault scenarios, and the need to consider them simultaneously are established; new end-to-end communication architecture with network of EIDs and eSEOP shown to be very effective in achieving high resolution situational awareness; real-time DER control is shown to be effective in mitigating violations without power curtailment and with minimal requirement on reactive power. The project has significantly added to the knowledge base on cyber-attack vectors, anomaly detection and alert correlation algorithms for DER environment. Technical effectiveness and economic feasibility: The proposed concepts, EIDs, and eSEOP and IDS/ADS performance have been demonstrated through extensive hardware-in-loop testbed that models a real feeder with more than 200% instantaneous PV penetration where significant overvoltage violations have been observed in the field. Proposed concepts and real-time control based on system-wide optimization have been demonstrated to mitigate all violations using less than 20% of the inverters for reactive power support. The developed EID is UL-rated, cost effective and vendor-agnostic. The scalability of the eSEOP to several thousands of DERs has been demonstrated. Public benefits of the project: The project has developed technologies for significantly increasing the solar hosting capacity of distribution feeders thereby allowing increased renewable energy in the generation mix and accelerating the clean energy transition. Total situational awareness achieved by this project helps with fault management and potentially supports advanced microgrid reconfiguration, contributing to grid resiliency.

The virtues of Wide Band Gap (WBG) devices and the increasing importance of inverters in the future grid have laid the foundation for high-frequency inverters to emerge as they offer miniaturization by reducing output filter size. Nonetheless, mitigating the high switching losses can be technically demanding, and hence the soft-switching inverters have become conspicuous. In this paper, we have proposed a low-loss zero-voltage-transition (ZVT) auxiliary circuit which helps realize a low device stress for a high-voltage application. The auxiliary voltage is obtained from a low-power flyback converter. Just one flyback converter is needed for all the poles of the inverter. While this ZVT circuit helps achieve zero voltage switching (ZVS) for the main switches, the auxiliary MOSFET turns off with zero-current switching (ZCS). The conduction time of the auxiliary ZVT circuit is minimal compared to the switching period, hence consuming low power. The ZVT circuit design and operation are validated with extensive simulation and experimental results.

With more distributed energy resources (DERs) being added on the grid to curb green house emissions, smart devices on the edge like inverters need to communicate with apps as well as centralized devices owned by local utilities to report pertinent data such as voltages and currents. In addition, central controllers also need to be able to send commands to inverters to help maintain the grid and sustain safe operating conditions. In this paper, 766 inverters based on a real distribution feeder are modeled in OPAL-RT and voltages, currents, real and reactive power measurements are sent to an SEL Real Time Automation Controller (RTAC) via DNP3, a supervisory control and data acquisition (SCADA) protocol. Voltage violations of +/- 5% (under 0.95 or over 1.05 per unit) are also modeled which need to be mitigated by sending commands to the inverters through the RTAC. The model was tested and validated first using Modbus which has read/write limitations not allowing an immediate holistic view of the system. As such, DNP3 was implemented which has no such limitations to prove the versatility of the model as well as validate the use of RTAC in an environment with a high penetration rate of DERs and their coordinated control. This paper will describe how the feeder model was created before diving into the intricacies of using SCADA protocols in OPALRT, connecting an RTAC to the OPAL-RT, and constructing a DNP3 map. Results will include seeing appropriate data in the RTAC's acSELerator program as well as voltage measurement changes due to inverter commands being sent from the RTAC.

The proliferation of distributed energy resources (DERs) im-poses new challenges to distribution system operation, e.g., power quality issues. To overcome these challenges and enhance system operation, it is critical to effectively utilize all available resources and accurately characterize unbalanced distribution networks in operational tools. This paper proposes a convex second-order-cone programming (SOCP)-based AC optimal power flow (ACOPF) model for three-phase unbalanced distribution net-works, including smart inverters and Volt-VAr controller (VVC) devices. Reactive power-voltage (Q-V) characteristics of smart inverters of solar photovoltaic (PV) units are also modeled. More-over, the settings of Q-V characteristics of VVC are co-optimized within the proposed ACOPF, considering the allowable range of the IEEE 1547-2018 standard. Furthermore, dynamic analyses are conducted to verify the stability of optimal settings of VVC. The proposed models are tested on an actual 1747-node primary distribution feeder in Arizona. The results illustrate the effective-ness of the proposed ACOPF for unbalanced systems in provid-ing a global optimal solution while capturing the non-linearity and non-convexity of ACOPF. By co-optimizing settings, system operation is improved due to the flexibility of adjusting reactive power output from PV units with VVC. The time-domain simu-lations show that the optimal settings result in a stable system

Passive voltage regulation in distribution grids using distributed energy resources (DERs) is becoming the standard for feeder voltage management in both under-voltage and over-voltage scenarios. Their simple control, ease of implementation, and fast response make them ideal for distribution feeders with high-DER penetration. This paper proposes a novel distributed voltage control for DERs based on the voltage at the point of com-mon coupling, inverter rating, and operating active power. The proposed control is designed to utilize feeder inverters efficiently to reduce the burden on the inverters in both under-voltage and over-voltage operations and increase the fairness in reactive power (Q) support in over-voltage operations. The proposed control is implemented in static and dynamic simulations of a real feeder to validate the performance. Results for the under-voltage scenario are also presented in the proposal.

Increasing photovoltaic (PV) penetration in the distribution system can often lead to voltage violations. Mitigation of these violations requires reactive power intervention from PV inverters. However, the unbalanced nature of the distribution system leads to mixed effects on the voltages of nearby nodes for each inverter injecting or absorbing reactive power. In particular, reactive power absorption to reduce over-voltage in one phase can exacerbate over-voltage in a different phase. In this paper, the factors impacting the incremental and decremental voltage effects of reactive power intervention are analyzed in detail. The result of these effects on the distribution system performance is presented to highlight their significance and the need to factor them in for any coordinated voltage control algorithm.

240$^\circ$-Clamped Space Vector PWM (240CPWM) is a lowest switching loss PWM method in cascaded architecture of DC-DC stage followed by DC-AC stage that reduces the switching loss by 85% in the DC-AC stage at unity power factor as compared to conventional space vector PWM (CSVPWM). 240CPWM requires unique six-pulse dynamically varying DC link voltage instead of constant DC link voltage which introduces low frequency harmonics predominantly around six times the fundamental frequency ($6f_{1}$). These low frequency harmonics distort the input DC current and AC line currents. Moreover, they change the operating point of maximum power point tracking (MPPT), reducing the efficiency of grid-connected Photovoltaic (PV) converter. In this article, three topologies are proposed to reduce the low frequency ripple in input DC current and AC line currents in three-phase grid-connected PV systems with 240CPWM. A three-phase 1.5 kW Silicon Carbide based hardware prototype in grid-connected mode is developed to validate the performance of the proposed topologies. Experimental results show that the maximum reduction of 68.8% in ($6f_{1}$) harmonic component in DC input current is achieved in active filter based Topology II without any significant detrimental effect on THD in AC line currents and inverter efficiency as compared to standard topology.

The widespread use of distributed energy sources (DERs) raises significant challenges for power system design, planning, and operation, leading to wide adaptation of tools on hosting capacity analysis (HCA). Traditional HCA methods conduct extensive power flow analysis. Due to the computation burden, these time-consuming methods fail to provide online hosting capacity (HC) in large distribution systems. To solve the problem, we first propose a deep learning-based problem formulation for HCA, which conducts offline training and determines HC in real time. The used learning model, long short-term memory (LSTM), implements historical time-series data to capture periodical patterns in distribution systems. However, directly applying LSTMs suffers from low accuracy due to the lack of consideration on spatial information, where location information like feeder topology is critical in nodal HCA. Therefore, we modify the forget gate function to dual forget gates, to capture the spatial correlation within the grid. Such a design turns the LSTM into the Spatial-Temporal LSTM (ST-LSTM). Moreover, as voltage violations are the most vital constraints in HCA, we design a voltage sensitivity gate to increase accuracy further. The results of LSTMs and ST-LSTMs on feeders, such as IEEE 34-, 123-bus feeders, and utility feeders, validate our designs.

As the electric power grid is brought up to date with state-of-the-art devices connected to the internet, pertinent information needs to reliably make its way from the edge to the cloud for system operators to visualize grid health. Conversely, control commands also need to be sent from the cloud to individual devices on the grid in order to maintain grid stability and safety, especially during unbalanced cases. This paper presents an affordable, brand-agnostic solution to grid data aggregation and communication using off-the-shelf products pieced together with IEC 61131–3 open source language for Programmable Logic Controllers (PLCs). A Phoenix Contact PLC along with some ancillary devices used to provide wireless communication capabilities were used to build an Edge Intelligent Device (EID) which interfaces with edge devices like solar inverters using Modbus protocol and the cloud using MQTT with an LTE backend for internet connection. The advantage of the EID over other similar devices is affordability and it is highly customizable. The EID was tested in both simulated and real-world applications: over 750 solar inverters were simulated in OPAL-RT and their data were transmitted to the cloud and visualized with Grafana in intervals under 30 seconds; data from a field testbed generating real data from solar panels and inverters, as well as another inverter built in-house powered by a grid simulator, was also transmitted through the EID. The paper will describe how the EID was built and coded, how the test beds were created, and show the results in Grafana.

Radiality and high R/X ratio branches cause EDNs to have low voltage profiles and insufficient security margins.This paper describes the application of a new meta-heuristic called the giant trevally optimizer (GTO) to find the best positions and sizes for capacitor banks (CBs) in low-voltage electrical distribution networks (EDNs) while taking into account various consumer types, including residential, commercial, industrial, and electric vehicles.By simultaneously lowering distribution losses, boosting the voltage profile, and improving the voltage stability margin, the major goal is thought to be to minimise the operational cost of annual energy loss.Different case studies on IEEE 33-bus and 69-bus EDNs are carried out in order to assess the computational effectiveness of the proposed GTO and are compared to the literature.Additionally, 50 independent runs are used to statistically quantify the convergence features of GTO and compare them to those of other meta-heuristics, particle swarm optimization (PSO), teaching-learning-based optimization (TLBO), cuckoo search algorithm (CSA), and flower pollination algorithm (FPA).Both comparative analyses demonstrated how GTO is more effective at finding global optima when tackling non-linear, non-convex optimisation problems with several types of variables and constraints.These technological and economic advantages demonstrate the methodology's capacity for real-time adaptation while taking emerging load trends and their loading patterns in low-voltage EDNs into account.

The high R/X ratio of typical distribution systems makes the system voltage vulnerable to the active power injection from distributed energy resources (DERs). Moreover, the intermittent and uncertain nature of the DER generation brings new challenges to the voltage control. This article proposes a two-stage stochastic optimization strategy to optimally place the photovoltaic (PV) smart inverters with Volt-VAr capability for distribution systems with high PV penetration to mitigate voltage violation issues. The proposed optimization strategy enables a planning-stage guide for upgrading the existing PV inverters while considering the operation-stage characteristics of the Volt-VAr control. One advantage of this planning strategy is that it utilizes the local control capability of the smart inverter that requires no communication, thus avoiding issues related to communication delays and failures. Another advantage is that the Volt-VAr control characteristic is internally integrated into the optimization model as a set of constraints, making placement decisions more accurate. The objective of the optimization is to minimize the upgrading cost and the number of the smart inverters required while maintaining the voltage profile within the acceptable range. Case studies on an actual 12.47 kV, 9-km-long Arizona utility feeder have been conducted using OpenDSS to validate the effectiveness of the proposed placement strategy in both static and dynamic simulations.

A new quadratic extended-duty-ratio (EDR) non-isolated boost converter is introduced here for ultra-high gain applications. The proposed converter is a combination of EDR boost converter and conventional quadratic boost converter. Quadratic boost converters can achieve high gain with lower component count while the EDR boost converter has low device stress while achieving high gain. A novel Quadratic EDR (Q-EDR) boost converter is proposed which is capable of attaining ultra high gain at moderate levels of duty with low voltage and current stress across different devices. Two different configurations of the proposed topology are presented with the interleaved version being able to reduce the current ripple further and the converter can be extended to $M$-phases in both the configurations. Detailed analysis of a 4-phase converter is presented along with converter design considerations. The performance of the proposed topology is validated through a 1 kW, 4-phase hardware prototype operating at 20 V-36 V input to 600 V output at 60 kHz. Experimental results corresponding to both interleaved and non-interleaved converter configurations are presented. Experimental results show that the converter can attain a conversion ratio of 30 at an operational duty close to 0.64 in the interleaved configuration. The switch voltage stress is limited to 150 V and quadratic stage diode voltage stress is limited to be less than 100 V for 600 V output condition enabling the use of low voltage devices. The converter is able to achieve a peak efficiency of 95.82% for 36 V to 600 V operation at 660 W.

The majority of technological advancements associated with the electrical grid, and particularly the increasing use of non-linear loads and power electronics in the distribution network, a weak network, challenge the fundamental assumption that voltages and currents exhibit sinusoidal waveforms. As extensively discussed by numerous authors, the electrical grid undergoes changes for which there are no conceptual foundations, measurement techniques, or practical validation strategies to address basic tasks such as energy consumption measurement, control of distributed generators, or the effective implementation of electrical protections in the non-sinusoidal environment. While the IEEE 1459 standard exists for such cases, it encounters conceptual complications regarding reactive power, as well as practical limitations requiring a complete spectral decomposition that can only be performed offline, preventing its use in real-time processes. Therefore, this study scrutinizes available techniques for online electrical power measurement in typical electrical disturbance scenarios, comparing their accuracy, dynamic response, and effectiveness in terms of the aforementioned standard.

As the penetration of inverter-based photovoltaic (PV) systems with various grid support functionalities increase rapidly, it becomes critical to examine their dynamic impacts on the distribution system. For dynamic studies in OpenDSS, the software provides a fixed-step size simulation framework, and users need to build their own model in a dynamic-link library (DLL) along with the integration algorithm. Model complexities may require the program to run at a small step size, which increases the unnecessary computational burden and results in a long simulation time. This paper proposes a new integrative simulation framework with adaptive step size in OpenDSS and the user-defined DLL. This new framework can increase the simulation efficiency significantly through adjusting the dynamic simulation step size in OpenDSS by evaluating the numerical integration accuracy within the DLL. The results show that the average step size utilized by the proposed simulation framework is over 9 times the fixed step size used by the original framework for the same dynamic simulation. Computational time consumption can also be saved by 70% using the proposed simulation framework.