IEEE Open Access Journal of Power and Energy - Volume 8

Listed below are the papers that were published in volume 8 of the IEEE Open Access Journal of Power and Energy. Click on the titles to access the papers in the PES Resource Center.

Regular Papers

  • "Characterization Procedure for Unsymmetrical Single-Phase Capacitor-Start Induction Machines"
    J. Cale, C. Lute, G. Ross, and A. Othee

    This paper describes an experimental and numerical optimization procedure for off-line extraction of parameters for unsymmetrical, single-phase induction machines with capacitor-start operation. In addition to permitting asymmetry between phase winding parameters, the approach requires only average and rms measurements as inputs; electrical phase angle measurements are not required. The method is validated on an experimental motor with transient and steady-state simulations, using fitted parameters obtained using the proposed approach.

  • "Demand-Side Participation via Economic Bidding of Responsive Loads and Local Energy Resources"
    M. Ostadijafari, R. R. Jha, and A. Dubey

    The active participation of demand response (DR) resources into the wholesale market price formation and load dispatch process has the potential to stimulate demand-side flexibility. However, it is challenging for a market entity to utilize the DR resources for practical use. This is because day-ahead wholesale market-clearing prices are uncertain, and DR resources are heterogeneous. Furthermore, DR participation may lead to violations of the distribution system's operational constraints. In this article, we propose an approach for an aggregator/load-serving entity (LSE) to profitably bid aggregated DR resources into the day-ahead wholesale market. The LSE requires an optimal bidding strategy that reflects the price elasticity of the aggregated retail loads to participate in the wholesale market operations. In the proposed approach, the LSE executes load curtailment and load shifting contracts with DR resources, where DR resources are remunerated for their participation at pre-contracted incentive prices. Then, the LSE aggregates the DR flexibility and optimally bids it in the day-ahead wholesale market. The proposed approach is validated using the IEEE-123-bus test system. It is demonstrated that the LSE can successfully generate economic bids for its participation in the day-ahead market by optimal management of DR resources and without violating the network's operating constraints.

  • "100% Sustainable Electricity in the Faroe Islands: Expansion Planning Through Economic Optimization"
    H. M. Tróndheim, B. A. Niclasen, T. Nielsen, F. Faria da Silva, and C. L. Bak

    SEV, the Faroese Power Company, has a vision to reach a 100% renewable power system by 2030. SEV is committed to achieve this, starting from a 41% share of renewables in 2019. A detailed expansion plan for the generation, storage and transmission is needed to reach this goal. This is the focus of this study. Practical constrains e.g. resource potential and available space must be considered. Balmorel, an optimisation tool, has been used to optimise investments and dispatch. A method to translate optimal results to a realistic RoadMap was developed and applied. The impact of different technologies and costs has been investigated through multiple scenarios. In ratios of average consumption in 2030, installed power will be 224% wind, 105% solar with 8-9 days of pumped hydro storage according to the proposed RoadMap. The plan is economically favorable up to 87% of renewables, but in order to reach a 100% renewable production in an average weather year, the renewable generation capacity has to be increased by 80%. The study also shows that if biofuels or tidal technologies become viable, these will be game changers needing a significantly lower total sum of installed renewable power.

  • "Bulk Electric Power System Risks From Coordinated Edge Devices"
    R. Kenyon, J. Maguire, E. Present, D. Christensen, and B.-M. Hodge

    As smart load adoption grows on the electric power system, potential for losing load diversity increases, possibly in ways that impact system stability. Cloud computing resources are able to coordinate large amounts of behind-the-meter loads and resources. Inadvertent or malicious actions could potentially result in gigawatts of load, distributed across large regions, acting nearly simultaneously. We study the resulting impacts of such a perturbation, which were previously recognized, with improved fidelity and granularity using a physically-based power system and demand model. The ResStock tool was used to calculate residential air conditioning load at more than 3,000 locations across the Western Interconnection, corresponding in time to heavy summer and light spring loading. Under an assumption that one cloud platform managed smart thermostats controlling 10%, 15%, or 20% of residential air-conditioning, calculated load steps could be injected into Positive Sequence Load Flow dynamic simulations. These load-driven effects were coupled with two classes of distributed generation ride-through to evaluate the potential for cascading outages.We found frequency deviations in the spring case far exceed the credible contingency event, leading to widespread distributed generation loss, while voltage depressions during the summer loading lead to widespread distributed generation loss and system separation.

  • "Distributed Mixed Voltage Angle and Frequency Droop Control of Microgrid Interconnections With Loss of Distribution-PMU Measurements"
    S. Sivaranjani, E. Agarwal, V. Gupta, P. Antsaklis, and L. Xie

    Recent advances in distribution-level phasor measurement unit (D-PMU) technology have enabled the use of voltage phase angle measurements for direct load sharing control in distribution-level microgrid interconnections with high penetration of renewable distributed energy resources (DERs). In particular, D-PMU enabled voltage angle droop control has the potential to enhance stability and transient performance in such microgrid interconnections. However, these angle droop control designs are vulnerable to D-PMU angle measurement losses that frequently occur due to the unavailability of a global positioning system (GPS) signal for synchronization. In the event of such measurement losses, angle droop controlled microgrid interconnections may suffer from poor performance and potentially lose stability. In this paper, we propose a novel distributed mixed voltage angle and frequency droop control (D-MAFD) framework to improve the reliability of angle droop controlled microgrid interconnections. In this framework, when the D-PMU phase angle measurement is lost at a microgrid, conventional frequency droop control is temporarily used for primary control in place of angle droop control to guarantee stability. We model the microgrid interconnection with this primary control architecture as a nonlinear switched system and design distributed secondary controllers to guarantee stability of the network. Further, we incorporate performance specifications such as robustness to generation-load mismatch and network topology changes in the distributed control design. We demonstrate the performance of this control framework by simulation on a test 123-feeder distribution network.

  • "Distributed Secondary Control of a Microgrid With a Generalized PI Finite-Time Controller"
    Y. Zhang, A. Mohammadpour Shotorbani, L. Wang, and B. Mohammadi-Ivatloo

    This paper proposes a novel distributed secondary controller for droop-controlled microgrids to regulate the frequency and voltage, and autonomously share the power mismatch. The proposed scheme is entitled generalized proportional-integral finite-time controller (GPI-FTC). The proposed GPI-FTC is synthesized based on the control Lyapunov function method and modifying the conventional PI controller by adding a consensus term to the integrand dynamic. The proposed distributed GPI-FTC provides plug-n-play capability, scalability, and fast finite-time convergence of the system states. Moreover, a reactive power sharing (Q-sharing) method is designed to improve the sharing pattern of reactive power under exact voltage regulation. Also, a distributed voltage observer is developed for average voltage regulation. Performance of the proposed GPI-FTC is validated through numerical simulations of the detailed model of the microgrid, including small signal analysis, load change, DG outage, Q-sharing, and performance comparison.

  • "Generative Adversarial Networks-Based Synthetic PMU Data Creation for Improved Event Classification"
    X. Zheng, B. Wang, D. Kalathil, and L. Xie

    A two-stage machine learning-based approach for creating synthetic phasor measurement unit (PMU) data is proposed in this article. This approach leverages generative adversarial networks (GAN) in data generation and incorporates neural ordinary differential equation (Neural ODE) to guarantee underlying physical meaning. We utilize this approach to synthetically create massive eventful PMU data, which would otherwise be difficult to obtain from the real world due to the critical energy infrastructure information (CEII) protection. To illustrate the utility of such synthetic data for subsequent data-driven methods, we specifically demonstrate the application of using synthetic PMU data for event classification by scaling up the real data set. The addition of the synthetic PMU data to a small set of real PMU data is shown to have improved the event classification accuracy by 2 to 5 percent.

  • "Development and Electric Grid Applications of a Magnetometer Network"
    K. S. Shetye, R. R. Kumar, C. Klauber, Z. Mao, T. J. Overbye, J. Gannon, and M. Henderson

    Monitoring the elements associated with geomagnetic disturbances (GMDs), such as the earth's magnetic field, can help mitigate their negative impacts on the power grid. While there are existing magnetometers monitoring this in certain locations, they are currently sparse and have several gaps in coverage such as the southern US region. This paper describes the recently developed network of six magnetometers in the US state of Texas. Aspects such as the site selection, physical description of a magnetometer station, and data communication are described. Data quality is tested using correlation analysis among these magnetometers and pre-existing magnetic observatories. A real-time magnetic field data streaming and visualization setup is developed, with provisions to make the data available to researchers and industry.

  • "Safe Reinforcement Learning-Based Resilient Proactive Scheduling for a Commercial Building Considering Correlated Demand Response"
    Z. Liang, C. Huang, W. Su, N. Duan, V. Donde, B. Wang, and X. Zhao

    It is a crucial yet challenging task to ensure commercial load resilience during high-impact, low-frequency extreme events. In this paper, a novel safe reinforcement learning (SRL)-based resilient proactive scheduling strategy is proposed for commercial buildings (CBs) subject to extreme weather events. It deploys the correlation between different CB components with demand response capabilities to maximize the customer comfort levels while minimizing the energy reserve cost. It also develops an SRL-based algorithm by combining deep-Q-network and conditional-value-at-risk methods to handle the uncertainties in the extreme weather events such that the impact from extreme epochs in the learning process is greatly mitigated. As a result, an optimum control decision can be derived that targets proactive scheduling goals, where exploration and exploitation are considered simultaneously. Extensive simulation results show that the proposed SRL-based proactive scheduling decisions can ensure the resilience of a commercial building while maintaining comprehensive comfort levels for the occupants.

  • "Quasi-Static Time-Series Power Flow Solution for Islanded and Unbalanced Three-Phase Microgrids"
    V. C. Cunha, T. Kim, P. Siratarnsophon, N. Barry, S. Santoso, and W. Freitas

    Recent advances in inverter-based distributed energy resources (DERs) allow microgrids to operate in grid-connected and islanded modes with ease. However, determining a steady-state load flow solution of a real-world unbalanced and islanded three-phase microgrid remains a challenge. Existing methods are either unsuitable, labor-intensive or computationally demanding for a long-term analysis of islanded microgrids. To address these issues, we propose a practical solution framework that employs externally-updated system frequency, power quantities, and droop characteristics governing the voltage and phase angle of DERs in every iteration as inputs to an off-the-shelf open-source multi-phase, multi-wire, unbalanced power flow software tool to solve an islanded-microgrid power flow. Using our framework, users only need to implement a set of droop equations and update system variables. The power flow solution is accomplished entirely by an off-the-shelf power flow tool, e.g., OpenDSS. Our proposed framework can model a microgrid of any arbitrary configuration and operating condition. We demonstrate and validate the proposed method's efficacy by comparing its results with those modeled using a time-domain simulation with PSCAD/EMTDC. Finally, an example of a quasi-static time-series study is presented to better illustrate the application of such a tool.

  • "An Algorithmic Approach for Identifying Critical Distance Relays for Transient Stability Studies"
    R. Vakili, M. Khorsand, V. Vittal, B. Robertson, and P. Augustin

    After major disturbances, power system behavior is governed by the dynamic characteristics of its assets and protection schemes. Therefore, modeling protection devices is essential for performing accurate stability studies. Modeling all the protection devices in a bulk power system is an intractable task due to the limitations of current stability software, and the difficulty in updating the setting data for thousands of protection devices. One of the critical protection schemes that is not adequately modeled in stability studies is distance relaying. Therefore, this paper proposes an iterative algorithm that uses two methods to identify the critical distance relays to be modeled in stability studies: (i) apparent impedance monitoring, and (ii) the minimum voltage evaluation (MVE). The algorithm is implemented in Python 3.6 and uses the GE positive sequence load flow analysis (PSLF) software for performing stability studies. The performance of the algorithm is evaluated on the Western Electricity Coordinating Council (WECC) system data representing the 2018 summer-peak load. The results of the case studies representing various types of contingencies show that to have an accurate assessment of system behavior, modeling the critical distance relays identified by the algorithm suffices, and there is no need for modeling all the distance relays.

  • "Dynamic Programming Method to Optimally Select Power Distribution System Reliability Upgrades"
    S. Raja, B. Arguello, and B. J. Pierre

    This paper presents a novel dynamic programming (DP) technique for the determination of optimal investment decisions to improve power distribution system reliability metrics. This model is designed to select the optimal small-scale investments to protect an electrical distribution system from disruptions. The objective is to minimize distribution system reliability metrics: System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI). The primary input to this optimization model is years of recent utility historical outage data. The DP optimization technique is compared and validated against an equivalent mixed integer linear program (MILP). Through testing on synthetic and real datasets, both approaches are verified to yield equally optimal solutions. Efficiency profiles of each approach indicate that the DP algorithm is more efficient when considering wide budget ranges or a larger outage history, while the MILP model more efficiently handles larger distribution systems. The model is tested with utility data from a distribution system operator in the U.S. Results demonstrate a significant improvement in SAIDI and SAIFI metrics with the optimal small-scale investments.

  • "Assessment of Measurement-Based Phase Identification Methods"
    F. Therrien, L. Blakely, and M. J. Reno

    The task of determining the phase connection of customers, known as phase identification, is crucial to obtain accurate distribution system models. This paper starts with a thorough literature review of the existing phase identification methods, which are broadly divided into three categories: hardware-based, real power-based, and voltage-based methods. This is followed by multiple case studies assessing the accuracy of six real power- and voltage-based phase identification algorithms on four realistic distribution test systems. Synthetic load profiles along with network models are used to quantify accuracy of each method for different scenarios: varying advanced metering infrastructure (AMI) coverage, number of initially mislabeled customer phases, number of available samples, and measurement noise. A case study using a real AMI data set, including field verification, is also provided. Finally, several aspects key to accurate phase identification are discussed in detail.

  • "Optimised Time for Travelling Wave Fault Locators in the Presence of Different Disturbances Based on Real-World Fault Data"
    M. Parsi and P. A. Crossley

    The real-world travelling wave fault data investigated in this paper indicate disturbances generate unpredictable, non-stationary and random waveforms which may cause maloperation of protection and control elements in a power system including travelling wave fault locators (TWFL). This type of fault locator is directly dependent on the detection of an accurate time of arrival (ToA) of travelling waves (TW) generated by a fault. This detection becomes complicated in the presence of disturbances when their ToAs are detected earlier than the fault TWs. Since travelling waves occur in the high-frequency bands (e.g. >50 kHz), in this paper a capacitor voltage transformer is employed to measure the TW voltage signals; this involves acquiring the current flowing to the ground and removing the low-frequency components (50/60 Hz). Disturbances create high magnitude pulses in the pre-fault section of a TW fault signal that last for a short time. Therefore, the time when a TWFL starts its computations requires to be optimised so that the effect of the disturbances is eliminated. The analysis techniques mentioned in this paper are based on real-world travelling wave fault data, and the solution uses statistical tools, such as cost function, mean and standard deviation, alongside Digital Signal Processing algorithms.

  • "Examination of Composite Load and Variable Frequency Drive Air Conditioning Modeling on FIDVR"
    A. Cisco Sullberg, M. Wu, V. Vittal, B. Gong, and P. Augustin

    Fault induced delayed voltage recovery (FIDVR) is a credible concern in power systems with high penetration of single-phase air conditioner loads. Power system planning studies use dynamic load models, such as the Western Electricity Coordinating Council (WECC) composite load model CMPLDW to examine FIDVR in power systems. The behavior of modern variable frequency drive (VFD) air conditioners to voltage drops is not the same as traditional one- or two-speed air conditioning systems. This paper investigates the impact of increasing VFD air conditioner penetration within a power system on FIDVR events, by first modeling VFD air conditioners as a separate load and then as a power electronic component within the CMPLDW model. Simulation results show that increasing the penetration of VFD driven air conditioners decreases the post-fault voltage sag, recovery time, and number of customers interrupted by undervoltage load shedding.

  • "Improving Numerical Accuracy in Time-Domain Simulation for Power Electronics Circuits"
    W. Nzale, J. Mahseredjian, X. Fu, I. Kocar, and C. Dufour

    In time-domain simulations of power system transients, trapezoidal integration with fixed step-size is the most common method due to its accuracy and ease of implementation. Discontinuities occurring within fixed time-step when simulating power electronics circuits, may cause numerical oscillations and errors. Several methods are available in the literature for interpolation and handling of discontinuities. This paper intends to analyze how accuracy is affected by existing techniques for handling discontinuities in time-domain simulations based on the trapezoidal integration method. New algorithms are proposed to improve accuracy.

  • "Automated Tool to Create Chronological AC Power Flow Cases for Large Interconnected Systems"
    B. Vyakaranam, Q. H. Nguyen, T. B. Nguyen, N. A. Samaan, and R. Huang

    Power system planning engineers currently perform planning studies based on a few snapshots representing typical system operating points, also known as base power flow cases. However, that is not enough to fully understand and evaluate operational impacts of the current and future grid, especially in high uncertainty and extreme events. Time-series analysis must be considered. We developed a procedure for using production cost model (PCM) simulation data for wind, photovoltaic, and load levels to generate chronological, hourly power flow cases. Because the PCM uses a lossless, linear, DC power-flow solution for simulations, AC power flow must be converged to enable reliability planning studies. This paper describes a procedure to handle losses and reactive power planning for large, interconnected systems. The procedure is illustrated with an example using the Western Electricity Coordinating Council (WECC) 2028 Anchor Data Set (ADS) as a PCM and the WECC 2028 High Summer Power Flow case (22,000 bus system) as references. This procedure can be applied to systems with multiple AC and DC grids of any grid topology.

  • "Fully Decentralized Reinforcement Learning-Based Control of Photovoltaics in Distribution Grids for Joint Provision of Real and Reactive Power"
    R. El Helou, D. Kalathil, and L. Xie

    In this paper, we introduce a new framework to address the problem of voltage regulation in unbalanced distribution grids with deep photovoltaic penetration. In this framework, both real and reactive power setpoints are explicitly controlled at each solar panel smart inverter, and the objective is to simultaneously minimize system-wide voltage deviation and maximize solar power output. We formulate the problem as a Markov decision process with continuous action spaces and use proximal policy optimization, a reinforcement learning-based approach, to solve it, without the need for any forecast or explicit knowledge of network topology or line parameters. By representing the system in a quasi-steady state manner, and by carefully formulating the Markov decision process, we reduce the complexity of the problem and allow for fully decentralized (communication-free) policies, all of which make the trained policies much more practical and interpretable. Numerical simulations on a 240-node unbalanced distribution grid, based on a real network in Midwest U.S., are used to validate the proposed framework and reinforcement learning approach.

  • "Model-Based and Data-Driven HVAC Control Strategies for Residential Demand Response"
    X. Kou, Y. Du, F. Li, H. Pulgar-Painemal, H. Zandi, J. Dong, and M. M. Olama

    The implementations of residential demand response (DR) based on heating, ventilation, and air conditioning (HVAC) are inseparable from effective control algorithms for coordinating the operating schedules of multiple HVAC devices. In this work, both model-based and data-driven HVAC control strategies are developed to determine the optimal control actions for HVAC systems. The control objectives are to minimize customers' electricity costs, customers' discomfort, and the utility-level load violation. In the model-based approach, a thermal resistance-capacitance (RC) HVAC model is formulated to capture buildings' thermodynamic behaviors, and a distributed solution algorithm (i.e., alternating direction method of multipliers) is applied to determine the day-ahead HVAC operation schedules. In the data-driven approach, the neural networks continuously interact with the environment during the training process to learn what control actions to take under certain circumstances and then are used for online decision-making. The case study is performed on a utility system with one hundred houses. Simulation results demonstrate that the model-based approach can save 22% of the total cost compared to the data-driven approach, while the data-driven approach does not require outdoor temperature forecast information and its computational speed is 46 times faster than that of the model-based approach.

  • "Synthesis of Load and Feeder Models Using Point on Wave Measurement Data"
    S. Nekkalapu, V. Vittal, J. Undrill, B. Keel, B. Gong, and K. Brown

    This paper describes a novel method to synthesize load and feeder models, by estimating the load composition and the load parameters, using instantaneous voltage and current measurements, obtained at the distribution level, from disturbance events. A novel feeder model structure has been proposed in this work comprising of single-phase loads, three-phase loads, impedance loads, distribution transformers and distribution line segments. The load composition of the proposed feeder models and the motor load parameters are determined using a non-linear least squares algorithm integrated with an electromagnetic transient (EMT) analysis tool PSCAD. The efficacy of the proposed algorithm is examined for feeders at different physical locations and with distinctly varied load characteristics. Using this approach, parameters of the motor loads have been obtained within a fixed set of bounded values for each corresponding parameter. The ability of the proposed feeder and load models to capture severe fault induced delayed voltage recovery events (FIDVR) has also been discussed here.

  • "A Fast Penalty-Based Gauss-Seidel Method for Stochastic Unit Commitment With Uncertain Load and Wind Generation"
    A. M. Palani, H. Wu, and M. M. Morcos

    Stochastic network-constrained unit commitment (S-NCUC) can be used to manage the uncertainty of an increasing penetration level of renewable energy effectively. However, the drawbacks of the progressive hedging algorithm (PHA) based solutions are that they are not provably convergent due to the non-convexity of S-NCUC. Additionally, the solution obtained is usually fractional-valued (non-binary) and therefore not readily implementable. In this paper, we apply a novel Penalty-Based Gauss-Seidel (PBGS) algorithm in solving S-NCUC using an exact augmented Lagrangian representation with proven convergence. To improve the computational efficiency of the PBGS, we further propose an accelerating technique with rigorous proof to skip solving scenarios when certain conditions are met during iterations. We numerically validate the proposed algorithms on the IEEE 118-bus system and a practically-sized ERCOT-like system, both with variable wind generation. Numerical results demonstrate the efficacy of the proposed algorithms in yielding high-quality S-NCUC solutions. The merits of the proposed algorithms are also revealed in comparison with PHA and extensive-form (EF) based mixed-integer programming solutions.

  • "Power Distribution System Synchrophasor Measurements With Non-Gaussian Noises: Real-World Data Testing and Analysis"
    C. Huang, C. Thimmisetty, X. Chen, E. Stewart, P. Top, M. Korkali, V. Donde, C. Tong, and L. Min

    This short paper investigates distribution-level synchrophasor measurement errors with online and offline tests, and mathematically and systematically identifies the actual distribution of the measurement errors through graphical and numerical analysis. It is observed that the measurement errors in both online and offline case studies follow a non-Gaussian distribution, instead of the traditionally assumed Gaussian distribution. It suggests the use of non-Gaussian models, such as Gaussian mixture models, for representing the measurement errors more accurately and realistically. The presented tests and analysis are helpful for the understanding of distribution-level measurement characteristics, and for the modeling and simulation of distribution system applications, such as state estimation.

  • "Quantifying Power System Operational and Infrastructural Resilience Under Extreme Conditions Within a Water-Energy Nexus Framework"
    S. Zuloaga and V. Vittal

    This work presents definitions and metrics developed for quantifying the resilience of the electric power system (EPS) while considering its interdependent operation with the water distribution system (WDS). These metrics are used within a novel formulation in order to determine EPS resilience during the coordinated real-time operation of the two systems where both the operational state and infrastructural configuration of the EPS is taken into account. Coordinated operation of the two systems involves simulations that account for the main dependencies of each system on the other (cooling water for thermoelectric generation and electric power for WDS pumps). The results for several test cases are used within this work to demonstrate how system resilience in the EPS is captured for simulations that emulate the critical conditions of long-term power outages (in the EPS) and severe drought (in the WDS).

  • "Time-Stepped Finite-Element Modeling of Three-Phase Transformer for Electromagnetic Transient Emulation on FPGA"
    Q. Xu, P. Liu, and V. Dinavahi

    The finite-element analysis is a powerful method to obtain detailed insight into the operation of any electromagnetic equipment. However, the required computational power to solve a finite-element modeled power equipment is so heavy that most Newton-Raphson-method-based algorithms can barely achieve real-time simulation. The low latency and hardware parallelism of the field-programmable gate array (FPGA) provides a path forward. In this paper, a parallel and deeply pipelined adaptive transmission-line modeling method with preconditioned conjugate gradient solver is designed in hardware and implemented on two Xilinx® XCVU37P FPGAs for the finite-element modeling of a three-phase transformer. The accuracy of the transformer solver under both current-excited and voltage-excited conditions of the transformer was validated against the commercial FE simulation tool.

  • "Reliability Assessment of Converter-Dominated Power Systems Using Variance-Based Global Sensitivity Analysis"
    B. Zhang, M. Wang, and W. Su

    With the proliferation of renewable energy and power electronic converters in power systems, the reliability issue has raised more research attention than ever before. This paper proposes a comprehensive framework to assess the reliability of a power system considering the effect from various power converter uncertainties. For the converter stage, we formulate a reliability model for each power converter based on several semiconductor devices, for which ambient uncertainties and converter topologies are considered. For the system stage, we estimate system reliability indicators through a non-sequential Monte Carlo simulation and calculate their variances. Afterward, we leverage machine learning regression algorithms between two stages to establish a nonlinear reliability relation. Moreover, a variance-based sensitivity analysis (SA) is conducted to rank and identify the most influential converter uncertainties with respect to the variance of system EENS. Based on the SA conclusions, system operators can take proactive actions to mitigate the potential risk of the system.

  • "Synthetic Harmonic Distance Relaying for Inverter-Based Islanded Microgrids"
    K. A. Saleh and M. A. Allam

    Faults in inverter-based islanded microgrids can be a formidable protection challenge due to (i) low fault current magnitudes, (ii) compromised fault current phase angles, and (iii) bidirectional flow of fault currents. This paper proposes a protection scheme that disregards the fault signals altogether. Instead, it relies on decoupled synthesized signals introduced only during fault conditions. This scheme is achieved by exploiting the existing inverter-based distributed generation (IBDG) controllers to inject synthetic harmonic voltages and currents. These synthetic signals are measured locally by digital relays in the microgrid to develop a novel synthetic harmonic distance relay (SHDR). Apart from the utilization of high-order harmonic signals that enhance SHDR reactance reach, further reach improvement is achieved via the introduction of line reactance magnifiers (LRMs). Transient studies in PSCAD/EMTDC verify the performance of the proposed scheme under various faults, contingencies, and different microgrid configurations.

  • "Economic Analysis of Power Grid Interconnections Among Europe, North-East Asia, and North America With 100% Renewable Energy Generation"
    C. Wu, X.-P. Zhang, and M. J. H. Sterling

    In this paper, we investigate whether the interconnection of power grids with 100% renewable energy generation can bring greater economic benefits now that the technology exists for high power, long distance Ultra High Voltage Direct Current transmission. Based on multi-year historical weather data and demand series, this study compares eight interconnection schemes for three regional grids in Europe, North-East Asia, and North America where there is around 8-hour time difference between any of the two regions. Sensitivity analyses are presented with respect to infrastructure capital cost and different weather year which show that interconnection yields a reduction of approximately 18% in the total annual system cost. The results in this paper also indicate that the regional levelized cost of electricity (LCOE) drops by 31%, 10%, and 10% for Europe, North-East Asia and North America, respectively. It is concluded that there is a strong incentive through both annual cost saving and regional LCOE drop in favour of full long-distance interconnections between the three regions in the context of the international drive towards a net-zero strategy.

  • "Novel Data-Driven Distributed Learning Framework for Solving AC Power Flow for Large Interconnected Systems"
    B. Vyakaranam, K. Mahapatra, X. Li, H. Wang, P. Etingov, Z. Hou, Q. Nguyen, T. Nguyen, N. Samaan, M. Elizondo, and T. Hay

    Recent advancement in power systems induces complexity in large-scale interconnected systems and poses challenges in performing security assessment studies at various operating conditions. Traditional model-based methods are computationally intensive and may not meet the requirements for real-time applications. This paper presents a novel data-driven framework for accelerating the process of obtaining multiple AC power flow (ACPF) solutions for large systems using deep convolutional neural networks (DCNN). DCNN models are designed and trained using various representative power flow cases from a system, whose outputs can be used to perform steady-state security assessment studies. Distributed training with multiple Graphical processing units (GPU)s is implemented using TensorFlow to reduce computation time. The proposed framework is implemented to identify critical buses and recognize the ACPF cases expected to cause steady-state bus voltage violations. The efficacy and feasibility of the proposed framework are evaluated on the Western Electricity Coordinating Council (WECC) 2028 system. Results demonstrate that the proposed framework is highly accurate and possess good interpretability in performing various transmission planning and operation assessment studies for large scale power networks.

  • "Smart Sampling for Reduced and Representative Power System Scenario Selection"
    X. Sun, X. Li, S. Datta, X. Ke, Q. Huang, R. Huang, and Z. J. Hou

    With increasing penetration of renewable energy and active market participation, power system operation scenarios and patterns have increased exponentially. This has led to challenges in identifying a good subset of scenarios for routine planning, operation, and emerging machine learning applications. To address these challenges, we develop an approach integrating comprehensive exploratory data analyses and smart sampling techniques to identify and select a small subset of representative power system scenarios that maintain the coverage of system scenarios and operation envelope, therefore, leading to very efficient, yet representative studies and analysis. We propose a hierarchical Latin Hypercube Sampling (LHS) technique for smart sampling, which allows free-form distributions of system load and considers generator commitment status along with generation levels. A set of performance metrics are also defined for systematic evaluation of the adequacy and efficiency of the sampled cases. The developed approach and metrics are demonstrated using the Texas 2000 bus system in this paper and will be extended to the more complex real world systems such as Western Interconnect System.

  • "Ensemble Learning, Prediction and Li-Ion Cell Charging Cycle Divergence"
    J. Obert, R. D. Trevizan, L. Torres-Castro, and Y. Preger

    In recent years, the pervasive use of lithium ion (Li-ion) batteries in applications such as cell phones, laptop computers, electric vehicles, and grid energy storage systems has prompted the development of specialized battery management systems (BMS). The primary goal of a BMS is to maintain a reliable and safe battery power source while maximizing the calendar life and performance of the cells. To maintain safe operation, a BMS should be programmed to minimize degradation and prevent damage to a Li-ion cell, which can lead to thermal runaway. Cell damage can occur over time if a BMS is not properly configured to avoid overcharging and discharging. To prevent cell damage, efficient and accurate cell charging cycle characteristics algorithms must be employed. In this paper, computationally efficient and accurate ensemble learning algorithms capable of detecting Li-ion cell charging irregularities are described. Additionally, it is shown using machine and deep learning that it is possible to accurately and efficiently detect when a cell has experienced thermal and electrical stress due to cell overcharging by measuring charging cycle divergence.

  • "Coordinated Damping Control Design for Power System With Multiple Virtual Synchronous Generators Based on Prony Method"
    M. Zhao, H. Yin, Y. Xue, X.-P. Zhang, and Y. Lan

    With more renewables integrated into power grids, the systems are being transformed into low inertia power electronic dominated systems. In this situation, the virtual synchronous generator (VSG) control strategy was proposed to deal with insufficient inertia challenge caused by the reduction of synchronous generation. However, as the VSG control method emulates the dynamic behavior of traditional synchronous machines, the interaction between multiple VSG controllers and synchronous generators (SGs) may cause low-frequency oscillation similar to that caused by the interaction between multiple SGs. This paper reveals that the system low-frequency oscillatory modes are affected by multiple VSGs. Then Prony analysis is utilized to extract the system mode information which will be subsequently used for VSG controller design, and a decentralized sequential coordinated method is proposed to design the supplementary damping controller (SDC) for multiple VSGs. The system low-frequency oscillation is first analyzed based on a modified two-area system with a linearized state-space model, and a further case study based on a revised New England 10-machine 39-bus system is used to demonstrate the effectiveness of the proposed coordinated method for multiple VSGs.

  • "Developing Robust Bidding Strategy for Virtual Bidders in Day-Ahead Electricity Markets"
    H. Mehdipourpicha, S. Wang, and R. Bo

    Purely financial players without any physical assets can participate in day-ahead electricity markets as virtual bidders. They can arbitrage the price difference between day-ahead (DA) and real-time (RT) markets to maximize profits. Virtual bidders encounter various monetary risks and uncertainties in their decision-making due to the high volatility of the price difference. Therefore, this paper proposes a max-min two-level optimization model to derive the optimal bidding strategy of virtual bidders. In this model, the risks of uncertainties associated with the rivals' strategies and RT market prices are managed by robust optimization. The proposed max-min two-level model is turned into a single-level mixed integer linear programming model through duality theory (DT), strong duality theory (SDT), and Karush-Kuhn-Tucker (KKT) conditions. An illustrative case is designed to demonstrate the advantages of the proposed model over the deterministic model. Moreover, case studies on the IEEE 24-bus test system validate the applicability of the proposed model.

  • "Probabilistic Assessment on Area-Level Frequency Nadir/Vertex for Operational Planning"
    J. Wen, S. Bu, and H. Xin

    Local heterogeneity of the frequency response of modern grids becomes more severe than ever before due to 1) weaker grid connection strength brought by the favorable grid interconnection, and 2) more uncertainties and less system inertia brought by the increasing renewable integration. This dominant characteristic is difficult to be accurately characterized and evaluated by the classic aggregated system frequency response (SFR) model. Therefore, this paper proposes a framework for assessing the risk of area-level frequency nadir/vertex (FN/FV) for operational planning in a practical and effective manner. Firstly, a multi-point sensitivity (MPS) is proposed based on the classical SFR model to evaluate the system FN/FV, where the impact of different Renewable Energy Sources (RESs) on system FN/FV are considered. The method can be extended for regional frequency evaluation, but the influence of generator frequency oscillation cannot be effectively considered, which might impact assessment accuracy. To address this issue, a multi-interval sensitivity (MIS) method is further proposed to calculate the probabilistic distribution of the area-level FN/FV. The probabilistic results are evaluated by the FN/FV RAM, i.e., Risk Assessment Matrix, to provide a two-dimensional analysis for system operational planners. The accuracy and efficiency of the proposed MPS and MIS methods are critically validated via scenario-based simulation (SBS) in a modified IEEE 16-machine 68-bus benchmark system.

  • "Generalized Formulation of Steady-State Equivalent Circuit Models of Grid-Forming Inverters"
    V. C. Cunha, T. Kim, N. Barry, P. Siratarnsophon, S. Santoso, W. Freitas, D. Ramasubramanian, and R. C. Dugan

    This work proposes positive- and negative-sequence equivalent circuits of grid-forming inverters for steady-state analysis. The proposed models are especially attractive for performing long-duration voltage regulation analysis and short-circuit studies involving grid-forming inverters. Our proposed equivalent circuit models are based on the inverter's voltage and current control loops in the αβ and dq frames. For this reason, they operate according to prescribed control functions and specified impedances (i.e., filter impedance, current limiter block, virtual admittance block, and PI/PR controller block). The equivalent circuit model accuracy is validated by comparing system steady-state voltage and current responses obtained by detailed time-domain models in PSCAD/EMTDC to those by the equivalent circuit models implemented in steady-state load flow program (e.g., OpenDSS). Two distinct control structures implemented in the αβ and dq frames are used for the validation. Single line-to-ground and line-to-line-to-ground faults are simulated in a small islanded microgrid as well as the IEEE 34-node test feeder. Fault impedances varying from 0 to 5 ohms are simulated. We show that the equivalent models precisely replicate the steady-state response of the detailed time-domain models.

  • "Evaluating Distributed PV Curtailment Using Quasi-Static Time-Series Simulations"
    J. A. Azzolini, M. J. Reno, N. S. Gurule, and K. A. W. Horowitz

    By strategically curtailing active power and providing reactive power support, photovoltaic (PV) systems with advanced inverters can mitigate voltage and thermal violations in distribution networks. Quasi-static time-series (QSTS) simulations are increasingly being utilized to study the implementation of these inverter functions as alternatives to traditional circuit upgrades. However, QSTS analyses can yield significantly different results based on the availability and resolution of input data and other modeling considerations. In this paper, we quantified the uncertainty of QSTS-based curtailment evaluations for two different grid-support functions (autonomous Volt-Var and centralized PV curtailment for preventing reverse power conditions) through extensive sensitivity analyses and hardware testing. We found that Volt-Var curtailment evaluations were most sensitive to poor inverter convergence (-56.4%), PV time-series data (-18.4% to +16.5%), QSTS resolution (-15.7%), and inverter modeling uncertainty (+14.7%), while the centralized control case was most sensitive to load modeling (-26.5% to +21.4%) and PV time-series data (-6.0% to +12.4%). These findings provide valuable insights for improving the reliability and accuracy of QSTS analyses for evaluating curtailment and other PV impact studies.

  • "Thévenin Equivalent Circuits for Modeling Coupled Common/Differential-Mode Behavior in Power Electronic Systems"
    T. J. Donnelly, S. D. Pekarek, D. R. Fudge, and N. Zarate

    Modeling the unintended common- and differential-mode (CM and DM) behavior of multi-converter power electronic-based systems can be a challenge. Chief among the issues is the need for detailed knowledge of the converter hardware to determine model parameters. In this paper, a focus is on the derivation of Thévenin-based models that only require characterization at the converter terminals. Periodic linear time varying system analysis is first used to derive and consider the applicability such models. Subsequently, methods to experimentally characterize Thévenin parameters are established. The modeling approach is then used to establish worst-case predictions of CM/DM behavior of a microgrid which is validated using both time-domain simulation and hardware experiment.

  • "Planned Islanding Algorithm Design Based on Multiple Sub-Microgrids With Dynamic Boundary"
    H. Yin, L. Zhu, Y. Ma, C. Zhang, Y. Su, D. Li, I. Ray, Y. Liu, F. Wang, and L. M. Tolbert

    Planned islanding is one of the fundamental functions of microgrid (MG) controllers. However, existing planned islanding functions cannot be directly utilized in MGs that have the capability to have both dynamic boundary and multiple sub-MGs. To optimize the smart switch operation and distributed energy resource (DER) output power, a planned islanding algorithm is designed to minimize the battery energy storage systems' power difference before and after a planned islanding. To verify the performance of the proposed algorithm, a hardware-in-the-loop (HIL) test has been conducted by implementing the algorithm in a general purpose MG controller system. The results demonstrate that the difference in active power before and after the planned islanding decreases significantly with the proposed algorithm.

  • "Active Power Curtailment in Power System Planning"
    R. Bolgaryn, Z. Wang, A. Scheidler, and M. Braun

    In regions with high penetration of Distributed Energy Resources (DER), grid congestion is mostly caused by power feed-in of generators. In this context, conventional approaches for solving the grid congestion problems are Active Power Curtailment (APC) of DER and grid reinforcement. In the wake of increased DER generation, it is not only of interest how to obtain the grid reinforcement, but also how to consider APC during grid planning. The challenge of such grid planning is to determine the best combination of reinforcement and APC. We present a new grid planning method and use it to find the trade-off between APC and grid reinforcement in a case study of a High-Voltage (HV) grid with a future renewable energy scenario. We compare the proposed reinforcement method to two existing methods. With the combination of APC and grid reinforcement, the proposed method shows a decrease regarding the total expenditures.

  • "Test Distribution Systems: Network Parameters and Diagrams of Electrical Structural"
    M. Mahdavi, H. H. Alhelou, and P. Cuffe

    Nowadays, specialized literature uses different test systems to verify their proposed models and methodologies regarding reconfiguration and operation of distribution networks. However, none of these research works include various test systems with enough information in order to endorse studies that approach distribution system reconfiguration and operation issues. This paper contains several test systems including the load data, network configuration, line characteristics, maximum current of branches, and nominal powers and voltages. The main objective is to provide all the details and information required to evaluate models and methods developed for reconfiguration and operation of radial distribution systems. Verification of all presented data and information has been performed by solving the network reconfiguration problem using established techniques. Moreover, in order to check the radiality of test systems and correctness of their given data, a data visualization technique is employed to online depict network topologies based on the electrical distance between buses.

Special Section: Invited Papers in 2021 on Emerging Topics in the Power and Energy Society

  • "Editorial: Special Section on Invited Papers in 2021 on Emerging Topics in the Power and Energy Society"
    F. Li and J. P. S. Catalão
  • "Modeling and Performance Evaluation of Grid-Interactive Efficient Buildings (GEB) in a Microgrid Environment"
    S. Rahman, A. Haque, and Z. Jing

    A detailed analysis of how Grid-interactive Efficient Buildings (GEB) can participate as active elements in a microgrid through on-site PV electricity generation and energy efficiency applications is presented. A case study using three US Department of Energy (DoE)-developed prototype commercial building models are used. These represent a secondary school, a hospital and a large office building. Simulation results show that when schools, hospitals and office buildings are operated as GEBs, there are always electricity savings, but savings amounts vary depending on levels of HVAC and lighting controls within the limits of customer comfort levels. These comfort level ranges are determined through interactions with building occupants which resulted in ΔT of 2-5°F and dimming level range of 20% to 50%. Savings in the school building are so much higher for two reasons. One, because without GEB application these buildings are operated in a business-as-usual fashion throughout the year, even when the school is not in session. The second reason is — being a two-story building the roof area is comparatively much higher than the hospital or the multi-storied office buildings.

  • "Load Factor Assessment of the Electric Grid by the Optimal Scheduling of Electrical Equipment- A MIQCP Model"
    F. V. Cerna, M. Pourakbari-Kasmaei, E. Naderi, M. Lehtonen, and J. Contreras

    In recent years, demand-side management (DSM) strategies have become an indispensable tool in the operation and planning of modern electricity grids (EGs). One effective way of ensuring the economical and reliable operation of an EG is through assessing its load factor (LF), while considering different types of electrical equipment (e.g., residential, commercial, and industrial). Toward this end, this paper proposes a mixed-integer quadratically constrained programming (MIQCP) model to deal with the LF assessment problems in a modified power distribution system through optimal scheduling of electrical equipment. This MIQCP model aims to minimize the total costs of purchasing energy by the electric utility via an iterative process, in which the difference between the energy consumption in each period and the average consumption is reduced. In the proposed model, the uncertainties in the consumption habits of different consumers, information related to each electrical equipment, energy prices, and the grid's technical constraints are considered. A modified 34-node EG, differentiated by consumer type, is implemented to evaluate the proposed model. Results show that the LF value is related to the optimal scheme of the electrical equipment that meets the operational and economic requirements of the power grid.

  • "A Shape-Based Clustering Framework for Time Aggregation in the Presence of Variable Generation and Energy Storage"
    N. Sarajpoor, L. Rakai, J. Arteaga, and H. Zareipour

    A common solution to mitigate the complexity of power system studies is time aggregation. This is to replace the actual data set for all time intervals with representative time periods. Previous research confirms that when energy storage systems are involved in the study, preserving the overall shape of the original data is crucial. This paper proposes a new time aggregation framework to incorporate a shape-based distance to jointly extract representative periods of wind and demand data. The duration curve of the net demand is used as a data-based validation index to compare the performance of the proposed method against other techniques. Also, a 3-bus case study that includes a wind resource, an energy storage system, and two conventional generators is designed. Four model-based validation indices are defined and applied for performance measurement, including the annual operation cost of the system, the annual wind curtailment in the system, the energy throughput of the storage facility, and the daily average of the state of the charge of the energy storage for each 365 days of the year.

  • "A Multi-Site Networked Hardware-in-the-Loop Platform for Evaluation of Interoperability and Distributed Intelligence at Grid-Edge"
    S. Essakiappan, P. R. Chowdhury, K. P. Schneider, S. Laval, K. Prabakar, M. D. Manjrekar, Y. N. Velaga, N. Shepard, J. Hambrick, and B. Ollis

    Electric power systems have experienced large increases in the number of intelligent, connected and controllable devices being deployed, leading to a high degree of distributed intelligence at the grid-edge. These devices, both utility-owned and consumer-owned, include renewable generation, energy storage, remote switches, voltage regulators, and smart controllable loads. These new devices provide significant potential for increased operational flexibility that can be leveraged to achieve system reconfiguration, resiliency improvements, power quality improvements, and distribution system automation. However, two significant challenges must be addressed before these assets can be leveraged for operations: interoperability and system level validation prior to deployment. Because of the complexity of distributed control systems, and their interactions with legacy centralized controls, a purely simulations-based approach for pre-deployment validation is not sufficient. It requires hardware-in-the-loop (HIL) testing to emulate hardware devices and evaluate their performance. Additionally, securely integrating multiple test facilities at utility operators and vendors can enable the rapid scale-up of evaluation platforms and remove the need for multiple expensive standalone installations. Presented in this paper, is the development of a multi-site evaluation platform that employs Advanced Distribution Management Systems (ADMS), distributed control devices, real-time HIL assets, secure communication links, and protocol adapters. The testbed has been developed at three sites, with one site hosting the ADMS and the other two hosting HIL capabilities. This platform uses standards-based approaches and open-source tools, and hence can serve as a template for other researchers and institutions to implement their multi-site evaluation frameworks for pre-deployment testing.

  • "A Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints"
    Y. Chen, S. M. Mazhari, C. Y. Chung, and S. O. Faried

    This paper proposes a probabilistic transient stability-constrained preventive dispatching method for power systems under a high inclusion of wind power. First, a set of instability mode (IM)-categorized probabilistic transient stability constraints (PTSCs) are constructed, which facilitate the development of a dispatching plan against various fault scenarios. Next, to avoid massive transient stability simulations in each dispatching operation, a machine learning-based model is trained to predict the critical clearing time (CCT) and IM for all preconceived fault scenarios. Based on the predictions, the system operation plan is assessed with respect to the PTSCs. Then, the sensitivity of the probabilistic level of the CCT is calculated to the active power generated from the critical generators for each IM category. Accordingly, the implicit PTSCs are converted into explicit dispatching constraints, and the dispatch is rescheduled to ensure the probabilistic stability requirements of the system are met at an economical operating cost. The proposed approach is validated on two modified IEEE test systems, reporting high computational efficiency and high-quality solutions.

  • "Real-Time Self-Dispatch of a Remote Wind-Storage Integrated Power Plant Without Predictions: Explicit Policy and Performance Guarantee"
    Z. Guo, W. Wei, L. Chen, Y. Chen, and S. Mei

    This paper investigates real-time self-dispatch of a remote wind-storage integrated power plant connecting to the main grid via a transmission line with a limited capacity. Because prediction is a complicated task and inevitably incurs errors, it is a better choice to make real-time decisions based on the information observed in the current time slot without predictions on the uncertain electricity price and wind generation in the future. To this end, the operation problem is formulated under the Lyapunov optimization framework to maximize the long-term time-average revenue of the wind-storage plant. Inter-temporal storage dynamics are represented by a virtual queue which is mean rate stable. An online method for real-time dispatch is proposed based on Lyapunov drift algorithm via a drift-minus-revenue function. The upper bound of such a function, which does not depend on future uncertainty, is minimized in each time slot. Explicit dispatch policies are obtained through multi-parametric programming technique so that no optimization problem is solved online. It is proved that the online algorithm can maintain all the constraints across the entire horizon and the expected optimality gap compared to the deterministic offline optimum with perfect uncertainty information is inversely proportional to the weight coefficient in the drift-minus-revenue function. Numerical tests using real wind and electricity price data validate the effectiveness and performance of the proposed method.

  • "A Dynamic Equivalent of Active Distribution Network: Derivation, Update, Validation and Use Cases"
    G. Chaspierre, G. Denis, P. Panciatici, and T. Van Cutsem

    This paper deals with the derivation of dynamic equivalents of active distribution networks, hosting inverter-based generators as well as static and motor loads. Equivalents are reduced-order models for use in dynamic simulations of the transmission system. They are of the grey-box types and their parameters are identified from large-disturbance Monte-Carlo simulations accounting for model uncertainty. After presenting an overview of the identification method at a single operating point, the paper deals with the update the equivalent when the operating conditions of the distribution network change. A procedure identifies the parameters to update, hence avoiding a complete new identification. Besides illustrative examples, two sets of simulation results are reported. First, the accuracy of the equivalent is validated in a long-term voltage instability scenario. Second, a larger-scale application is presented, with numerous instances of the equivalent attached to the model of the IEEE Nordic transmission test system. This combined model is used to assess the impact on short- and long-term voltage stability of the inverter-based generators with fast and slow controls.

  • "A New Approach to the Fault Location Problem: Using the Fault's Transient Intermediate Frequency Response"
    N. Cifuentes and B. C. Pal

    The fault location problem has been tackled mainly through impedance-based techniques, the travelling wave principle and more recently machine learning algorithms. These techniques require both current and voltage measurement. In the case of impedance-based methods they can provide multiples solutions. In the case of the travelling wave approach it usually requires high sampling frequency measurements together with sophisticated identification algorithms. Machine learning techniques require training data and re-tuning for different grid topologies. This paper proposes a new fault location method based on the fault's transient intermediate frequency response of the system immediately after a fault occurs. The transient response is characterized by the travelling wave phenomenon together with intermediate frequencies of oscillation, which are dependent on the faulted section and the fault location. In the proposed fault location solution, an offline methodology identifies these intermediate frequencies and their dependency on the fault location is fitted using a polynomial regression. The online fault location is performed using those polynomial regressions together with voltage measurements from the system and simple signal processing techniques. The full method is tested with an EMT simulation in PSCAD, using the exact frequency dependent model for underground cables.

  • "Assessment of the Effects of the Electromagnetic Pulse on the Response of Overhead Distribution Lines to Direct Lightning Strikes"
    A. Borghetti, K. Ishimoto, F. Napolitano, C. A. Nucci, and F. Tossani

    In the usual practice, the evaluation of overvoltages due to direct lightning strikes to overhead power lines is focused on the representation of the effects of the lightning current injection, whilst the effects of the coupling between the conductors and the lightning electromagnetic pulse (LEMP) is disregarded. Motivated by recent results obtained for the case of a medium voltage line configuration with a shield wire, this paper extends the analysis to assess the contribution of the LEMP on the lightning performance of an overhead distribution line with and without periodically grounded wires and surge arresters. Moreover, the paper deals with the LEMP effect on the occurrence probability of flashovers on different phases, which is an important information on the service continuity of networks with isolated or compensated neutral earthing. A validation of the results is obtained by comparing the overvoltages calculated by the electromagnetic transient program including the model of the line illuminated by the LEMP and those obtained by a three-dimensional finite difference time-domain approach.

  • "Review of Low-Rank Data-Driven Methods Applied to Synchrophasor Measurement"
    M. Wang, J. H. Chow, D. Osipov, S. Konstantinopoulos, S. Zhang, E. Farantatos, and M. Patel

    There is a growing acceptance of using synchrophasor data collected over large power systems in control centers to enhance the reliability of power system operations. The spatial and temporal nature of power system ambient and disturbance response allows the analysis of large amount of synchrophasor data by low-rank methods. This paper provides an overview of several applications of synchrophasor data utilizing the low-rank property. The tools to capitalize on the low-rank property include matrix completion methods, tensor analysis, adaptive filtering, and machine learning. The applications include missing data recovery, bad data correction, and disturbance recognition.

  • "Frequency Response in the Presence of Renewable Generation: Challenges and Opportunities"
    N. Nguyen, D. Pandit, R. Quigley, and J. Mitra

    Due to their many advantages, renewable energy resources (RERs) are proliferating rapidly to satisfy a significant portion of the global energy demand. It is predicted that the importance of RER generation will continue to increase in the future of the energy industry. In spite of all their known benefits, the integration of RERs poses several challenges to system stability and reliability. Low inertia characteristics and the intermittent output of RERs introduces additional variation into an already variable grid frequency. System regulation capability and reliability are reduced as RERs gradually replace conventional generators. This paper reviews the challenges associated with RER integration on system frequency response and how these challenges affect system reliability. Advanced methods for mitigating challenges associated with increasing RER integration, while ensuring system security, are discussed, and the necessary mathematical background is provided in concise form. A model is developed for determining the maximum level of RER penetration based on stability constraints. Emerging methods to advance the integration of RERs are discussed.

  • "Interdisciplinary Vision of the Digitalized Future Energy Systems"
    Z. Y. Dong and Y. Zhang

    Global energy systems are transforming from fossil fuels to renewables, but the conventional electricity systems are so fragile that could lead to negative consequences such as soaring prices, rolling blackouts, security issues and delays to emission reductions. Confronting to these issues, electricity systems of the future will be vastly changed, dominated by new technologies and business models, increasingly digital and highly complex. Such transformation will be enabled by means to efficiently, stably and affordably distribute electrical power from many sources and storage points. Market design, policy, regulations, legislations, cyber security and politics are barely keeping up with advances in technologies, and energy technology choices have multi-generational implications for people and economies. These issues are global and to find a solution requires true systems thinking, informed by cutting-edge research. This paper envisages interdisciplinary digitalized future energy systems for emission reductions and proposes a 6-theme template to shape the future energy system. The six research themes have been designed such that the "whole is greater than the sum of the parts''. Each theme is informed by the others and the inter-linking of the six themes' inputs and outputs will drive the outcomes and impacts of future energy systems.

  • "Space Microgrids for Future Manned Lunar Bases: A Review"
    D. Saha, N. Bazmohammadi, J. M. Raya-Armenta, A. D. Bintoudi, A. Lashab, J. C. Vasquez, and J. M. Guerrero

    Several space organizations have been planning to establish a permanent, manned base on the Moon in recent years. Such an installation demands a highly reliable electrical power system (EPS) to supply life support systems and scientific equipment and operate autonomously in a fully self-sufficient manner. This paper explores various technologies available for power generation, storage, and distribution for space microgrids on the Moon. Several factors affecting the cost and mass of the space missions are introduced and analysed to provide a comprehensive comparison among the available solutions. Besides, given the effect of base location on the design of a lunar electrical power system and the mission cost, various lunar sites are introduced and discussed. Finally, the control system requirements for the reliable and autonomous operation of space microgrids on the Moon are presented. The study is complemented by discussing promising future technological solutions that could be applied upon a lunar microgrid.

Regular Paper

  • "Voltage-Sensitivity-Based Volt-VAR-Watt Settings of Smart Inverters for Mitigating Voltage Rise in Distribution Systems"
    S. Yoshizawa, Y. Yanagiya, H. Ishii, Y. Hayashi, T. Matsuura, H. Hamada, and K. Mori

    Active and reactive power control using smart inverters (SI) is highly effective in mitigating voltage rise in distribution systems, which is caused by the high penetration of photovoltaic (PV) power generation. However, the voltage control performance depends on the SI settings. We propose a new approach that uniquely determines the parameter settings for volt-VAR-watt control based on the active and reactive power-voltage sensitivity matrix of SIs. Because the voltage sensitivity matrix is calculated based solely on the impedance of the distribution system and it does not vary with time or the number of SIs, the proposed method can determine the individual SI parameter settings theoretically and efficiently without the need for optimization problem formulation, power flow calculation, or communication between the SIs. To evaluate the proposed method, the voltage control performance in a real distribution system model with a large number of PV installations is compared with that of volt-VAR-watt control using default parameters and optimized parameters in case that the load demand and PV generation are given in advance. The results show that the proposed method achieves better control performance than other conventional methods in terms of all the evaluation indices; in particular, it realizes effective control in the case of voltage rise. Furthermore, the proposed method can also achieve the same level of voltage control performance as the optimization results, even though it uses only the voltage sensitivity matrix and SI rating capacities for parameters determination, and the accuracy of the proposed voltage control can be ensured.

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