Showing papers on "AC power published in 2021"

Grid Forming Inverter Modeling, Control, and Applications

Abstract: This paper surveys current literature on modeling methods, control techniques, protection schemes, applications, and real-world implementations pertaining to grid forming inverters (GFMIs). Electric power systems are increasingly being augmented with inverter-based resources (IBRs). While having a growing share of IBRs, conventional synchronous generator-based voltage and frequency control mechanisms are still prevalent in the power industry. Therefore, IBRs are experiencing a growing demand for mimicking the behavior of synchronous generators, which is not possible with conventional grid following inverters (GFLIs). As a solution, the concept of GFMIs is currently emerging, which is drawing increased attention from academia and the industry. This paper presents a comprehensive review of GFMIs covering recent advancements in control technologies, fault ride-through capabilities, stability enhancement measures, and practical implementations. Moreover, the challenges in adding GFMIs into existing power systems, including a seamless transition from grid-connected mode to the standalone mode and vice versa, are also discussed in detail. Recently commissioned projects in Australia, the UK, and the US are taken as examples to highlight the trend in the power industry in adding GFMIs to address issues related to weak grid scenarios. Research directions in terms of voltage control, frequency control, system strength improvement, and regulatory framework are also discussed. This paper serves as a resource for researchers and power system engineers exploring solutions to the emerging problems with high penetration of IBRs, focusing on GFMIs.

An Enhanced IEEE 33 Bus Benchmark Test System for Distribution System Studies

Abstract: The transformation of passive distribution systems to more active ones thanks to the increased penetration of distributed energy resources, such as dispersed generators, flexible demand, distributed storage, and electric vehicles, creates the necessity of an enhanced test system for distribution systems planning and operation studies. The value of the proposed test system, is that it provides an appropriate and comprehensive benchmark for future researches concerning distribution systems. The proposed test system is developed by modifying and updating the well-known 33 bus distribution system from Baran & Wu. It comprises both forms of balanced and unbalanced three-phase power systems, including new details on the integration of distributed and renewable generation units, reactive power compensation assets, reconfiguration infrastructures and appropriate datasets of load and renewable generation profiles for different case studies.

Distributed Finite-Time Secondary Frequency and Voltage Control for Islanded Microgrids With Communication Delays and Switching Topologies

Abstract: This article is concerned with the distributed secondary frequency and voltage control for islanded microgrids. First, the distributed secondary control problem is formulated by taking both communication delays and switching topologies into account. Second, by using an Artstein model reduction method, a novel delay-compensated distributed control scheme is proposed to restore frequencies of each distributed generator (DG) to a reference level in finite time, while achieving active power sharing in prescribed finite-time regardless of initial deviations generated from primary control. Third, a distributed finite-time controller is developed to regulate voltages of all DGs to a reference level. Fourth, the proposed idea is also applied to deal with the finite-time consensus for first-order multiagent systems. Finally, case studies are carried out, demonstrating the effectiveness, the robustness against load changes, and the plug-and-play capability of the proposed controllers.

Peer-to-Peer Energy Trading in Transactive Markets Considering Physical Network Constraints

Abstract: In recent years, the rapid growth of active consumers in the distribution networks transforms the modern power markets’ structure more independent, flexible, and distributed. Specifically, in the recent trend of peer-to-peer (P2P) transactive energy systems, the traditional consumers became prosumers (producer+consumer) who can maximize their energy utilization by sharing it with neighbors without any conventional arbitrator in the transactions. Although a distributed energy pricing scheme is inevitable in such systems to make optimal decisions, it is challenging to establish under the influence of non-linear physical network constraints with limited information. Therefore, this paper presents a distributed pricing strategy for P2P transactive energy systems considering voltage and line congestion management, which can be utilized in various power network topologies. This paper also introduces a new mutual reputation index as a product differentiation between the prosumers to consider their bilateral trading willingness. In this paper, a Fast Alternating Direction Method of Multipliers (F-ADMM) algorithm is realized instead of the standard ADMM algorithm to improve the convergence rate. The effectiveness of the proposed approach is validated through software simulations. The result shows that the algorithm is scalable, converges faster, facilitates easy implementation, and ensures maximum social welfare/profit.

Two-Stage Volt/Var Control in Active Distribution Networks With Multi-Agent Deep Reinforcement Learning Method

Abstract: The high penetration of intermittent renewable energy resources in active distribution networks (ADN) results in a great challenge for the conventional Volt-Var control (VVC). This article proposes a two-stage deep reinforcement learning (DRL)-based real-time VVC method to mitigate fast voltage violation while minimizing the network power loss. In the first stage, on-load tap changer (OLTC) and capacitor banks (CBs) are dispatched hourly based on the optimal power flow method. The optimization problem is formulated as a mixed-integer second-order cone programming (MISOCP) which can be effectively solved. In the second stage, the reactive power of photovoltaics (PVs) is regulated dynamically to mitigate fast voltage fluctuation based on the well-learned control strategy and local measurements. The real-time VVC problem is formulated and solved using a multi-agent deep deterministic policy gradient (MADDPG) method, which features offline centralized training and online decentralized application. Rather than using the critic network to evaluate the output of the actor-network, the gradient of the action-value function to action is derived analytically based on the voltage sensitivity method. The proposed approach is tested on the IEEE 33-bus distribution system and comparative simulation results show the enhanced control effect in mitigating voltage violations.

Six-Switch Step-Up Common-Grounded Five-Level Inverter With Switched-Capacitor Cell for Transformerless Grid-Tied PV Applications

Abstract: Photovoltaic string inverters with transformerless grid-connected architecture are the most commonly used solar converters owing to their appliance-friendly and cost-effective benefits. A novel circuit configuration for these converters is presented in this article, which seeks to address the shortcomings of most of the conventional topologies such as the problem of leakage current, voltage ratio transformations, and power quality. The proposed structure is based on the series–parallel switching conversion of the switched-capacitor (SC) cell and is comprised of only six unidirectional power switches with a common-grounded (CG) feature. Through the use of the SC cell and the CG connection of active and passive used elements, not only is the number of output voltage level enhanced by up to five but also a two times voltage boosting feature with a single-stage operation as well as elimination of the leakage current is acquired. Herein, to inject a tightly controlled current into the grid, a peak current controller approach has been used which can handle both the active and reactive power supports modes. Theoretical analysis, design guidelines, comparative study, and some experimental results are also given to corroborate the feasibility and accurate performance of the proposed topology.

Soft-Switching Solid-State Transformer With Reduced Conduction Loss

Abstract: Solid-state transformers (SSTs) are a promising solution photovoltaic (PV), wind, traction, data center, battery energy storage system (BESS), and fast charging electric vehicle (EV) applications. The traditional SSTs are typically three-stage, i.e., hard-switching cascaded multilevel rectifiers and inverters with dual active bridge (DAB) converters, which leads to bulky passives, low efficiency, and high electromagnetic interference (EMI). This article proposes a new soft-switching solid-state transformer (S4T). The S4T has full-range zero-voltage switching (ZVS), electrolytic capacitor-less dc link, and controlled dv/dt , which reduces EMI. The S4T comprises two reverse-blocking current-source inverter (CSI) bridges, auxiliary branches for ZVS, and transformer magnetizing inductor as a reduced dc link with 60% ripple. Compared with the prior S4T, an effective change on the leakage inductance diode is made to reduce the number of the devices on the main power path by 20% for significant conduction loss saving and retain the same functionality of damping the resonance between the leakage and resonant capacitors and recycling trapped leakage energy. The conduction loss saving is crucial, being the dominating loss mechanism in SSTs. Importantly, the proposed single-stage SST not only holds the potential for high power density and high efficiency but also has full functionality, e.g., multiport dc loads integration, voltage regulation, and reactive power compensation, unlike the traditional single-stage matrix SST. The S4T can achieve single-stage isolated bidirectional dc–dc, ac–dc, dc–ac, or ac–ac conversion. It can also be configured input-series output-parallel (ISOP) in a modular way for medium-voltage (MV) grids. Hence, the S4T is a promising candidate for the SST. The full functionality, e.g., voltage buck–boost, multiport, etc., and the universality of the S4T for the dc–dc, dc–ac, and ac–ac conversion are verified through the simulations and experiments of two-port and three-port MV prototypes based on 3.3 kV SiC mosfet s in dc–dc, dc–ac, and ac–ac modes at 2 kV.

A Scalable Real-Time Non-Intrusive Load Monitoring System for the Estimation of Household Appliance Power Consumption

Abstract: Smart-meter technology advancements have resulted in the generation of massive volumes of information introducing new opportunities for energy services and data-driven business models. One such service is non-intrusive load monitoring (NILM). NILM is a process to break down the electricity consumption on an appliance level by analyzing the total aggregated data measurements monitored from a single point. Most prominent existing solutions use deep learning techniques resulting in models with millions of parameters and a high computational burden. Some of these solutions use the turn-on transient response of the target appliance to calculate its energy consumption, while others require the total operation cycle. In the latter case, disaggregation is performed either with delay (in the order of minutes) or only for past events. In this paper, a real-time NILM system is proposed. The scope of the proposed NILM algorithm is to detect the turning-on of a target appliance by processing the measured active power transient response and estimate its consumption in real-time. The proposed system consists of three main blocks, i.e., an event detection algorithm, a convolutional neural network classifier and a power estimation algorithm. Experimental results reveal that the proposed system can achieve promising results in real-time, presenting high computational and memory efficiency.

Delay-Tolerant Predictive Power Compensation Control for Photovoltaic Voltage Regulation

Abstract: Voltage regulation is imperative for the successful operation of electricity distribution networks, especially with a high penetration level of photovoltaic (PV) systems. Power compensation control (PCC) that uses both reactive power compensation and active power curtailment has shown promising results in alleviating voltage rise problems. It crucially relies on real-time communications among distributed PV systems. However, the transmission of state measurements and control signals in PCC is hampered by inevitable communication delays. Therefore, it is important to not only estimate the maximum tolerable communication delay (MTCD) but also develop an alternative technique for PCC under abnormal communication delay (ACD) conditions. This article presents a delay-tolerant predictive PCC for voltage regulation in distribution feeders. After estimating the MTCD based on voltage and power mutation, it uses normal PCC for effective operation when communication delay is within MTCD, or switches to predictive PCC under ACD conditions. An accurate prediction is achieved using a double neural network with online adjustment of weights and samples. Simulations on a sample distribution network demonstrate the effectiveness of our presented approach.

Reverse and Forward Engineering of Local Voltage Control in Distribution Networks

Abstract: The increasing penetration of renewable and distributed energy resources in distribution networks calls for real-time and distributed voltage control. In this article, we investigate local Volt/VAR control with a general class of control functions, and show that the power system dynamics with nonincremental local voltage control can be seen as a distributed algorithm for solving a well-defined optimization problem (reverse engineering). The reverse engineering further reveals a fundamental limitation of the nonincremental voltage control: the convergence condition is restrictive and prevents better voltage regulation at equilibrium. This motivates us to design two incremental local voltage control schemes based on the subgradient and pseudo-gradient algorithms, respectively, for solving the same optimization problem (forward engineering). The new control schemes decouple the dynamical property from the equilibrium property, and have much less restrictive convergence conditions. This article presents another step toward developing a new foundation—network dynamics as optimization algorithms—for distributed real-time control and optimization of future power networks.

Unified Power Quality Conditioner With Advanced Dual Control for Performance Improvement of DFIG-Based Wind Farm

Abstract: The weakness of low voltage ride-through capacity, power oscillations under asymmetrical fault and the instability of the output power are three major difficulties that need to be urgently addressed in the field of doubly fed induction generator (DFIG). To simultaneously deal with these issues, this article proposes a cost-effective energy storage device-based unified power quality conditioner (ESD-UPQC) to improve the low voltage ride through capability of the DFIG, suppress voltage oscillations under unbalanced faults and regulate DFIG output power during fluctuated wind speed conditions. A comprehensive protection scheme is carried out that the series side converter of the ESD-UPQC is controlled using dual control to suppress the post-fault voltage oscillations under transient conditions, while three advanced control targets are proposed for the parallel side converter aiming at regulating DFIG output power during wind gust, and suppress power oscillations during symmetrical and asymmetrical grid faults. Simulation results attest the feasibility of the proposed controller. The robustness of the proposed ESD-UPQC controller is validated through a series of comparisons based on a lead-acid battery scheme and an ESD-DFIG scheme for power smoothing and LVRT enhancement respectively.

Power Quality Improvement in Modular Multilevel Inverter Using for Different Multicarrier PWM

Abstract: Pulse width modulation (PWM) is a powerful technique employed in analog circuit convert with a microprocessor based digital output. Besides, Pseudo Random Multi Carrier (PRMC) involves in two random PWM strategies to minimize the harmonic order for 9- level cascaded multilevel H-bridge (CHB) inverter and 9-level Modular Multilevel inverter are introduced. The design mainly focuses on the (Pulse Width Modulation) PWM method, in which two nearest voltage levels are approached in estimated output voltage prediction based on the Partial swarm optimization (PSO) algorithm, and it conveys a random variation in the pulse position of output by Pseudo Random Multi Carrier- Pulse Width Modulation (PRMC-PWM). The CHB and the Modular inverters generate low distortion output by using PMRC. The simulation and prototype circuit are developed for the nine level output using sixteen switches and ten with Resistive-Inductive (R-L) load variation condition. The power quality is improved in CHB and Modular inverter (MoI) with minimized harmonics in various modulation index (MI) as varied from 0.1 up to 0.8. The circuit is designed by using a Field Programmable Gate Array (FPGA), Implementing a PSO algorithm for both CHB, and MoI are proposed. The comparisons of results are verified with lower order harmonics and find the best switching angle across the MLI switches. Modular inverter furthermore investigates with PRMC, Random Nearest level (RNL) modulation scheme are presented, and the proposed circuit is along with the respective degree of the output voltage were synthesized in non-linear load by the development of reactive power across a motor load.

Direct Power Control of Shunt Active Power Filter Using Space Vector Modulation Based on Supertwisting Sliding Mode Control

Abstract: This article proposes direct power control (DPC) associated with space vector modulation (SVM) for a shunt active power filter (SAPF). This control is suggested in order to overcome the drawbacks of the conventional DPC, where the SVM is able to decrease the high active and reactive power ripples maintaining a fixed switching frequency. In addition, the performance of the proposed scheme is improved by replacing PI controllers with supertwisting second-order sliding mode controllers (ST-SMCs) in the active and reactive power control loops. This technique provides high robustness and dynamics for external perturbations. The proposed control DPC-SVM based on ST-SMC is investigated by simulation and practical implementation using MATLAB/Simulink with a real-time interface based on a dSPACE 1104 board.

Voltage Stability of Power Systems with Renewable-Energy Inverter-Based Generators: A Review

Abstract: The main purpose of developing microgrids (MGs) is to facilitate the integration of renewable energy sources (RESs) into the power grid. RESs are normally connected to the grid via power electronic inverters. As various types of RESs are increasingly being connected to the electrical power grid, power systems of the near future will have more inverter-based generators (IBGs) instead of synchronous machines. Since IBGs have significant differences in their characteristics compared to synchronous generators (SGs), particularly concerning their inertia and capability to provide reactive power, their impacts on the system dynamics are different compared to SGs. In particular, system stability analysis will require new approaches. As such, research is currently being conducted on the stability of power systems with the inclusion of IBGs. This review article is intended to be a preface to the Special Issue on Voltage Stability of Microgrids in Power Systems. It presents a comprehensive review of the literature on voltage stability of power systems with a relatively high percentage of IBGs in the generation mix of the system. As the research is developing rapidly in this field, it is understood that by the time that this article is published, and further in the future, there will be many more new developments in this area. Certainly, other articles in this special issue will highlight some other important aspects of the voltage stability of microgrids.

Risk-Averse Coordinated Operation of a Multi-Energy Microgrid Considering Voltage/Var Control and Thermal Flow: An Adaptive Stochastic Approach

Abstract: With an increasing penetration level of intermittent renewable energy sources and heterogeneous energy demands, the secure and economic operation of multi-energy microgrids (MEMGs) becomes more and more critical. Under this circumstance, this paper proposes an adaptive (two-layer) stochastic approach to obtain optimal MEMG operation decisions by taking advantage of distinct energy properties. First, rather than merely focusing on the active power economic dispatch, voltage/var control (VVC) scheme is involved to co-optimize the active and reactive power flow while guaranteeing voltage security; Second, a battery degradation model and a comprehensive thermal network model with thermal energy flow and transmission delay are presented to derive practical and efficient operations; Third, a conditional value-at-risk (CVaR)-based risk evaluation method is included to avoid over-optimistic solutions. The original nonlinear operation problem is reformulated as a mixed-integer linear programming (MILP) model to achieve high solution quality with acceptable computation performance. Finally, case studies are conducted to indicate that our proposed approach can effectively coordinate the dispatch of active/reactive power as well as thermal flow, thus ensuring system security with minimal operating costs and risks.

Data-driven Optimal Control Strategy for Virtual Synchronous Generator via Deep Reinforcement Learning Approach

Abstract: This paper aims at developing a data-driven optimal control strategy for virtual synchronous generator (VSG) in the scenario where no expert knowledge or requirement for system model is available. Firstly, the optimal and adaptive control problem for VSG is transformed into a reinforcement learning task. Specifically, the control variables, i.e., virtual inertia and damping factor, are defined as the actions. Meanwhile, the active power output, angular frequency and its derivative are considered as the observations. Moreover, the reward mechanism is designed based on three preset characteristic functions to quantify the control targets: (1) maintaining the deviation of angular frequency within special limits; (2) preserving well-damped oscillations for both the angular frequency and active power output; (3) obtaining slow frequency drop in the transient process. Next, to maximize the cumulative rewards, a decentralized deep policy gradient algorithm, which features model-free and faster convergence, is developed and employed to find the optimal control policy. With this effort, a data-driven adaptive VSG controller can be obtained. By using the proposed controller, the inverter-based distributed generator can adaptively adjust its control variables based on current observations to fulfill the expected targets in model-free fashion. Finally, simulation results validate the feasibility and effectiveness of the proposed approach.

A Field Enhancement Integration Design Featuring Misalignment Tolerance for Wireless EV Charging Using LCL Topology

Abstract: This article proposes a magnetic integration design for EV wireless power transfer (WPT) systems, where the compensation and transmitting coils overlap one on top of the other to share the ferrite layer without any decoupling consideration. The magnetic field generated by both the compensation and transmitting coils are exploited to transfer power. To this end, a compensation method is proposed to enable magnetic field enhancement without any reactive power flow between the compensation and the transmitting coils, and to achieve input zero phase angle and constant current output. In addition, an efficient finite element analysis-based coil optimization algorithm is proposed to improve the coil misalignment tolerance on the horizontal plane, in which a reversely connected inner coil is used to stabilize the system output under misalignment conditions. Analytical and simulation results confirm transmission flux density enhancement and reduced leakage field characteristics of the proposed coil design. Finally, a scaled-down WPT prototype is built and tested to verify the performance and effectiveness of the design. The proposed design achieves 91.17% efficiency and misalignment tolerance up to 200 mm in any XY-direction while maintaining the power transfer and its efficiency. The results of this work provide insights into magnetic integration design of high-order compensation topologies featuring higher compactness, less ferrite usage, magnetic field enhancement, and misalignment tolerance for WPT systems.

Distributed Coordinated Reactive Power Control for Voltage Regulation in Distribution Networks

Abstract: In this article, a novel distributed coordinated control framework is proposed to handle the uncertain voltage violations in active distribution networks. It addresses the problem of coordination of different types of devices in a distributed manner. In our control design, on-load tap changers (OLTCs) are firstly employed to handle the potential voltage violations based on the prediction of renewable outputs and load variations. During real-time operation, once an unmanageable voltage violation is detected, the reactive power of distributed energy resources (DERs) will be coordinated immediately to provide fast corrective control. The control schedules of OLTCs are calculated by solving a multitime-step constrained optimization problem via the alternating direction method of multipliers, whereas the reactive power injections of DERs are determined by a novel online distributed algorithm. The effectiveness of the proposed control framework is verified on the modified IEEE 34-bus and 123-bus test feeders.

MPC-Controlled Virtual Synchronous Generator to Enhance Frequency and Voltage Dynamic Performance in Islanded Microgrids

Abstract: The use of high penetration converter-interfaced renewable energy (RE) based microgrids (MGs), due to the absence of rotational masses from conventional synchronous generators (SGs), may lead to a lack of inertia, which may lead the steeper frequency and voltage fluctuations that may in turn cause instability issues and challenges the normal operation of sensitive loads. To suppress these fluctuations and enhance the MGs stability, a novel model predictive control (MPC)-controlled virtual synchronous generator (VSG) for an energy storage system (ESS) is introduced. The proposed method can provide inertia support during transient states and enhance the dynamic characteristics of system voltage and frequency. By establishing the prediction model of VSG and designing the cost function for frequency and power, the increments of the needed active and reactive power are calculated then superposed on the power reference of VSG. The results show that the suppression performance of the voltage and frequency variations under loading transition with the proposed method is better than those of other techniques. Simulation and hardware-in-the-loop (HIL) results further demonstrate the effectiveness of the proposed method.

Grid Impedance Estimation Through Grid-Forming Power Converters

Abstract: In more-electronics power systems, grid-forming power converters, which operate as ac voltage sources, regulate the grid frequency and voltages in replacement of synchronous generators. Notably, grid impedances greatly influence the small signal and voltage stability of grid-forming converters. As such, prior knowledge of grid impedances can be very helpful for controller design. However, grid impedance estimation schemes are normally designed for current-controlled grid-following converters. Moreover, they are either very complicated or only yield grid inductances in a generally intrusive way. To fill this research gap, an impedance estimation method well suited to grid-forming converters is proposed. The method consists of four operating modes, which work well in voltage and power control cases. In the voltage control case, the voltage amplitude perturbation or phase angle information is exploited. Subsequently, the grid inductance and resistance are derived from power measurement. Alternatively, the active or reactive power information serves to estimate the grid impedance in the power control case. The proposed method features an easy implementation without any harmonic distortion, safety concern, or dependence on control parameters. Moreover, the method operates nonintrusively in most scenarios. Furthermore, a novel Kalman filtering scheme is proposed to provide added incentives. Finally, simulation and experimental results validate the effectiveness and simplicity of the proposed method.

A Distributed MPC to Exploit Reactive Power V2G for Real-Time Voltage Regulation in Distribution Networks

Abstract: It has been demonstrated theoretically and experimentally that the Vehicle-to-Grid (V2G) enabled electric vehicle (EV) charger is of a reactive power compensation ability with a battery or capacitor connected. To exploit the aggregated reactive power V2G abilities of massively dispersed EV chargers, a distributed model predictive control (DMPC) strategy applying to both balanced and unbalanced distribution networks (DNs) is proposed to integrate them into real-time DN voltage regulation. Firstly, based on the instantaneous power theory and voltage sensitivity matrices, a voltage regulation model considering the reactive response of EV chargers is established without violating the normal EV active charging demands. Then, a completely distributed framework is achieved by DMPC, in which prediction information and calculation results are shared in a Peer-to-Peer (P2P) way to realize the asynchronous broadcast. The proposed model and techniques are validated by numerical results obtained from the IEEE European low voltage test feeder system. The case studies indicate that the proposed DMPC is robust to communication latency (CML) and works effectively in both balanced and unbalanced DNs without any control center, which is a significant advantage for the promotion of real-time reactive power V2G in DNs with irregular user integration and relatively poor communication infrastructure.

Near-Optimal PI Controllers of STATCOM for Efficient Hybrid Renewable Power System

Abstract: Connecting different renewable energy sources (RESs) to the electrical grids is presently being urged to fulfill the enormous need for electric power and to decrease traditional sources’ ecological related issues, the so-called hybrid systems. Unfortunately, these hybrid systems suffer from the possible negative environmental impacts of the wind gusts in wind energy conversion systems (WECSs) that may degrade the overall system performance. Additionally, various severe faults may disconnect some RESs from the hybrid system, like three-phase faults. In this paper, the static synchronous compensator (STATCOM) is considered for both improving the performance of a hybrid system, contains WECS and photovoltaics (PVs) against wind gusts and maintaining the continuous operations of RESs during three-phase fault occur at the point of common coupling (PCC) between the RESs and the grid. The STATCOM is stimulated by two PI controllers regulating the reactive power flow between the STATCOM and the hybrid system at PCC and, consequently, regulating the voltage at PCC. A metaheuristic optimizer optimally schedules these two PI controllers based on whale optimization algorithm (WOA). The impartial comparison between the WOA dynamic performance and the particle swarm optimization as another optimization algorithm verifies the efficiency of the WOA for the near-optimal gain scheduling of the PI controller gains.