IEEE Open Access Journal of Power and Energy - Volume 8

Listed below are the papers that have been published to date in volume 8 of the IEEE Open Access Journal of Power and Energy. Papers will be added to the issue throughout the year as they are accepted and finalized. 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.

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