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At least 1,315 records · Page 73

Data-driven Modeling for Grid Edge IBRs: A Digital Twin Perspective of User-Defined Models

Recent events in Odessa have brought attention to the challenges associated with the interaction between Inverter- Based Resources (IBRs) and the transmission and distribution system. The NERC event diagnosis report has highlighted sev- eral issues, emphasizing the need for continuous performance monitoring of these IBRs by system operators. Key areas of concern include the mismatch of control and protection perfor- mance of IBRs between the original equipment manufacturer (OEM)-provided models and field measurements. The inability to replicate the realistic response can result in incorrect reliability and resilience studies. In this paper, we developed an approach on how to emulate the behavior of an IBR using measurement data obtained for system operators to utilize in real-time and long- term planning. Two experiments are conducted in the phasor domain and electromagnetic transients (EMT) domain to emulate the behavior for grid forming and grid following inverters under various operating conditions and the effectiveness of the proposed model is demonstrated in terms of accuracy and ease of utilizing user-defined models (UDMs)

Mahapatra, Kaveri [BATTELLE (PACIFIC NW LAB)]↗

Grid Parameters and Voltage Estimation Approach Integrating Data-Driven Converter Model

With Measurements of grid voltage and current are essential for the optimal operation of the grid protection and control (P&C) systems. Grid parameters vary through time during the faults and especially in the converter interfaced resources (CIRs) rich power grid, and thus accurate estimation is critical to avoid the mis-operation of the P&C systems. In this paper, a moving horizon estimation (MHE) as an observer is devised and applied to estimate the grid line parameters and grid voltages for protection enhancement. Due to the proprietary and confidentiality of CIRs, the proposed approach uses the black-box model to represent their dynamics. Leveraging the easily accessible measurements of output current from the black-box model of CIR and voltage at the point of common coupling, the proposed method estimates the grid impedance and grid voltage during normal and faulty operating conditions. The performance shows that the optimization-based observer was able to closely observe the accurate states and parameters, which can be utilized by the P&C systems.

Subedi, Sunil↗

Thermal Analysis of Wireless Power Transfer Coils for Dynamic Wireless Electric Vehicle Charging

In this paper, safe operating conditions of a wireless power transfer coil were identified and road infrastructure for a dynamic wireless electric vehicle charging system was studied. Magneto-thermal simulations were used to map the power loss directly into the computed fluid dynamics solver. This method allowed the authors to analyze the heating pattern of the enclosed wireless power transfer coil in the road structure, as well as for the vehicle coil. Thermal heating patterns for three types of rectangular coil structures were analyzed. Heating patterns were analyzed for 200 kW coils and different magnetic field densities in the magnetic core.

Wojda, Rafal↗

Comparison of Dead-Time Effects in a WPT System Inverter for Different Fixed-Frequency Modulation Techniques

In this paper, a comparative study of the dead-time effects in a wireless power transfer (WPT) system inverter is performed for different fixed-frequency control techniques. The dead-time is provided between the complementary switching instances of the inverter phase-legs to ensure safe operation of the input power source. Under certain operating conditions, the dead-time results in waveform distortions or voltage-polarity reversal (VPR) at the inverter output. The VPR affects the switching characteristics, harmonic spectrum, switching losses, and output voltage/power of the system. A detailed analysis of the dead-time effect on the WPT system parameters such as output voltage and output power is conducted for the different fixed-frequency control strategies (i.e., traditional phase-shift control, asymmetrical clamped-mode, and asymmetrical duty-cycle control). Furthermore, the impact of dead-time on the inverter switching losses is compared for the different control strategies.

Kavimandan, Utkarsh↗

Design of a 100 kW Surface Permanent Magnet Machine with Wide Constant Power Speed Ratio for Traction Applications

Surface permanent magnet (SPM) machines are considered to be strong candidates for traction applications due to their high power density and high efficiency. By adopting fractional-slot concentrated windings, SPM machines can achieve a wide constant power speed range. A carbon fiber sleeve is applied to ensure the retainment of the magnets at high speed operating conditions. The purpose of this paper is to present the design of a high speed SPM machine for traction applications with 25 kW/Liter active power density and a wide constant-power speed range that is consistent with guidelines and targets presented in the Electrical and Electronics Technical Team Roadmap published by the US Department of Energy. The predicted electromagnetic performance and structural characteristics are presented based on both analytical and FEA results.

42 ENGINEERING↗

Modeling of RMS Current in CSI Filter Capacitor and Minimum Conduction Loss Operation of CSI-Fed PMSM Drives for Traction Applications

This paper presents a new minimum conduction loss (MCL) torque control algorithm for current source inverter- (CSI-) fed permanent-magnet synchronous machine drives that improves the overall machine drive efficiency by minimizing the combined conduction losses in the inverter and machine at each operating point. First, analytical models of conduction losses in CSI-fed motor drives are presented, and a closed-form expression for optimal d-axis stator current to achieve MCL operation is derived. An expression for the rms current in both wye- and delta-connected CSI output capacitors is derived. A detailed simulation model that emulates the operation of a 100 kW SiC CSI-fed integrated machine drive (IMD) has been developed based on experimental results and finite element analysis. This simulation model is used to evaluate the proposed MCL control algorithm applied to a CSI-fed IMD system for a battery-electric vehicle traction drive, and the predicted total drive system loss with MCL control is compared to predicted losses with maximum-torque-per-ampere (MTPA) and minimum dc-link current (MDCC) control. Results show that MCL control can achieve loss reductions compared to the other two control algorithms over a wide range of operating conditions, with significant loss reductions >20% in the medium-speed regime.

42 ENGINEERING↗

Crack Propagation Modeling of a High-Speed Outer Rotor Motor

This study aims to investigate the propagation of initial cracks in electric motors and their rate of spread through the rotor structure under various operating conditions. Traction motors are subjected to high centrifugal load owing to their speed and rapid acceleration and deceleration. In the manufacturing process, some initial imperfections or cracks in the rotor components are likely to occur. Under the influence of loading, these cracks will grow, and factors such as loading frequency, material strength, and location of material voids will affect this threshold speed. In the current study, a fracture mechanics–based approach has been used to investigate the crack growth rate for a 100 kW outer rotor motor with a rated speed of 6,000 rpm and a peak speed of 20,000 rpm for an integrated drive application.

Barua, Himel↗

Autoencoder-Based Sensor Drift Detection and Mitigation for Resilient Charging Systems

This work presents an autoencoder-based approach for sensor signal reconstruction and drift detection for charging systems. The proposed strategy is implemented within a Simulink-based system framework and evaluated under multiple operating conditions. An autoencoder with 8 neurons in the bottleneck layer is adopted, achieving accurate reconstruction across 10 variables and strong agreement with the physical sensor readings under normal conditions. In the case of a sensor fault, the autoencoder reconstruction remains closer to the expected true value compared to the corrupted measurement. Furthermore, feeding the autoencoder-reconstructed signal value back into the control framework in place of the faulty sensor signal leads to improved power monitoring. These results highlight the potential of autoencoder-based virtual sensing to extend the concept of resiliency to all components of the charging system, including sensors.

Rezende Da Costa Reis Kimpara, Renata [ORNL] (ORCI↗

Grid-Forming Inverters: Project Demonstrations and Pilots

Power system operators around the world are pushing the limits of integrating inverter-based resources (IBRs) to very high levels, approaching 100% instantaneous penetration under certain operating conditions. This often applies to smaller power systems with very little or no ac interconnections to other neighboring regions or sometimes to fringes of large balancing areas, such as Denmark or Portugal, within the mainland European power system. These jurisdictions have identified the potential of grid-forming (GFM) technology as a key enabler to support the energy transition with very few or no synchronous generators online. Until recently, practical applications of GFM inverters were limited to microgrids and isolated grids and in smaller grid applications on the order of a few tens of megawatts (MW).

Australia↗

Cycle-by-cycle Delay Estimation at Signalized Intersections by using Machine Learning and Simulated Video Detection Data

Accurate estimation of delay is crucial for efficient traffic signal operations. Estimation of delay in the real-time manner using traditional loop detectors requires advanced detectors (in addition to stop-bar detection). In cases when this detection layout is not in place, delay estimates are approximated with a lower accuracy. Video detection is one of the most frequently deployed detection systems at signalized intersections in recent years. In most cases video detection operates in the same way as traditional inductive loops. However, when coupled with computer vision algorithms, video detection systems could be used to retrieve additional information (e.g., vehicular arrivals and departures) that cannot be taken out from the conventional systems (e.g., long stop-bar loop detectors). Although present for several decades, video detection data were not frequently examined for delay estimation purposes. In this study, we proposed a novel delay estimation model which can be developed with only data from stop-bar video detectors. Relevant data were collected from a simulation model of 11 signalized intersections at downtown Chattanooga, TN and processed to create needed inputs for model development. With the use of multigene genetic programming the authors developed a delay model that outperforms accuracy of multi regression model. Furthermore, authors evaluated the developed model by comparison with the other benchmark delay models, such as HCM and approach delay model. It was found that the developed MGGP delay model outperforms benchmark models for a wide range of traffic and signal operation conditions.

Erdagi, Ismet Goksad↗

A General State Estimation Formulation for Three-Phase Unbalanced Power Systems

Almost all of the three-phase state estimation algorithms assume existence of a reference bus whose phase angles are perfectly balanced. This assumption is quite realistic for transmission systems, and also for most distribution systems that are connected to a strong transmission system where transmission side can modeled by a balanced reference bus. However, for distribution systems having high penetration of renewable sources or for microgrids operating in islanded mode, the assumption of a balanced reference bus will not be realistic. While there are recent publications focusing on this problem, formulation of the three-phase unbalanced state estimation problem with proper treatment of the reference bus remains unaddressed. In this paper, a new formulation will be described where an accurate state estimation solution can be obtained for any unbalanced threephase system irrespective of its operating conditions (balanced or highly unbalanced), configuration (isolated microgrid, connected to transmission system, etc.) and whether or not it contains any synchronous generators. Validation of the proposed formulation will be carried out via simulations.

State Estimation, Distribution System, Unbalanced ↗

Generalized Power Flow Model of an Extra High-Power Multi-Terminal HVdc Transmission Grid with Parallel-Connected and Voltage-Stacked Converters

To increase power transfer capacity of high-voltage direct current (HVdc) transmission, a new extra high-power HVdc architecture with multiple standard modular multilevel converters (MMCs) per substation has recently been introduced. This paper proposes a power flow model for a multi-terminal HVdc (MTdc) grid with this innovative substation architecture. The proposed MTdc model can be integrated seamlessly with existing ac-dc power flow algorithms with minimal modifications. The model is applicable to various MTdc grid types and topologies, different numbers of dc buses, dc lines, and MMCs per substation, along with diverse control parameters. In addition, it accurately captures both balanced and unbalanced operations of the MTdc grid. The proposed model is verified using a 5-terminal bipole MTdc grid that spans 4 areas in the Eastern Interconnection system of the USA. The numerical solutions obtained from unified and sequential ac-dc power flow algorithms under different operating conditions closely match the time-domain simulation results in PSCAD, validating the accuracy and versatility of the proposed MTdc power flow model.

Nguyen, Quan H.↗

Assessing the Accuracy of Balanced Power System Models in the Presence of Voltage Unbalance

Traditional models of electric power systems represent distribution systems with unbalanced three-phase network models and transmission systems with balanced single-phase-equivalent network models. This distinction poses a challenge for coupled models of transmission and distribution systems, which are becoming more prevalent due to the growth of distributed energy resources connected to distribution systems. In order to maintain a balanced network representation, transmission system models typically assume that the voltage phasors at the interface to the distribution system are balanced. Inaccuracies resulting from this assumption during unbalanced operation can lead to erroneous values for line currents in the transmission system model. This paper empirically quantifies the accuracy of this balanced operating assumption during unbalanced operating conditions for both a simple two-bus system along with a more complex transmission and distribution co-simulation. This paper also characterizes the performance of different methods for translating the unbalanced voltage phasors into a balanced representation in order to give recommendations for modeling coupled transmission and distribution systems.

power distribution↗

Safe Reinforcement Learning for Emergency Load Shedding of Power Systems

The paradigm shift in the electric power grid necessitates a revisit of existing control methods to ensure the grid’s security and resilience. In particular, the increased uncertainties and rapidly changing operational conditions in power systems have revealed outstanding issues in terms of either speed, adaptiveness, or scalability of the existing control methods for power systems. On the other hand, the availability of massive real-time data can provide a clearer picture of what is happening in the grid. Recently, deep reinforcement learning (RL) has been regarded and adopted as a promising approach leveraging massive data for fast and adaptive grid control. However, like most existing machine learning (ML)- based control techniques, RL control usually cannot guarantee the safety of the power systems. In this paper, we introduce a novel method for safe RL-based load shedding of power systems that can enhance the safe voltage recovery of the electric power grid after experiencing faults. Numerical simulation on the IEEE 39-bus testcase is performed to demonstrate the effectiveness of the proposed safe RL emergency control, as well as its adaptive capability to faults not seen in the training.

reinforcement learning, emergency control, power g↗

Reinforcement Learning for Volt- Var Control: A Novel Two-stage Progressive Training Strategy

This paper develops a reinforcement learning (RL) approach to solve a cooperative, multi-agent Volt-Var Control (VVC) problem for high solar penetration distribution systems. The ingenuity of our RL method lies in a novel two-stage progressive training strategy that can effectively improve training speed and convergence of the machine learning algorithm. In Stage 1 (individual training), while holding all the other agents inactive, we separately train each agent to obtain its own optimal VVC actions in the action space: fconsume, generate, do-nothingg. In Stage 2 (cooperative training), all agents are trained again coordinatively to share VVC responsibility. Rewards and costs in our RL scheme include (i) a system-level reward (for taking an action), (ii) an agent-level reward (for doing-nothing), and (iii) an agent-level action cost function. This new framework allows rewards to be dynamically allocated to each agent based on their contribution while accounting for the trade-off between control effectiveness and action cost. The proposed methodology is tested and validated in a modified IEEE 123-bus system using realistic PV and load profiles. Simulation results confirm that the proposed approach is robust and computationally efficient; and it achieves desirable volt-var control performance under a wide range of operation conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Quantified Fast Frequency Response of Inverter-Based Resources for Bulk-Power System Study

Quantifying fast frequency response (FFR) of inverter-based resources (IBRs) is crucial for robust frequency regulation, managing resources, and improving system reliability in the power grids with high penetration levels of IBRs. This paper proposes a concept of frequency response scheme that its response is quantifiable and applicable to the generic IBR models. To achieve this, a stepwise-energy function is derived as a control module by considering operational constraints of IBRs. Then the module is implemented along with generic IBR models in electromagnetic transient (EMT) and electromechanical-based software. To quantify the FFR, the implemented module calculates available incremental active power for a specific time duration. This energy profile is being updated depending on IBR’s operating conditions and is provided into a power grid upon detecting a frequency event. Thus, due to this characteristic, this scheme can quantify the FFR and enable applicable IBRs to provide their available headroom within frequency arrest period. Thereby, this scheme can help estimate IBRs’ frequency response and is more effective in improving the initial frequency response than frequency-dependent control schemes: rate-of-change-of-frequency based and droop-based control schemes. The performance of the proposed scheme was tested under different IBR penetration levels using PSLF and PSCAD simulators.

Kim, Jinho↗

Spatial-Temporal PV Hosting Capacity Estimation and Evaluation

Evaluating Photovoltaic Hosting Capacity (PVHC) is an essential step in the process of integrating solar energy into power grids, particularly when focusing on the distribution network (DN) as the primary integration target. PVHC needs to be investigated, especially in cases where the grids are unbalanced, and their operational conditions vary spatially and temporally. This motivation prompted us to propose a scalable model tailored to this application. In this paper, we applied linearization to the alternating current optimal power flow (AC-OPF) and solar inverters, transforming the original problem into a mixed-integer linear programming (MILP) problem. Additionally, we accounted for the battery energy storage system (BESS) as a time-coupling factor for calculating PVHC. We then compared the PVHC results between the IEEE-13 bus and SMART-DS San Francisco (SFO) cases and discussed the extent to which BESS can enhance the PVHC of a DN. Furthermore, we designed a web-based graphical visualization for the SFO case, enabling user interaction with raw data and simulation results on a map through a graphical user interface (GUI). In summary, our results and findings provide valuable insights for future three-phase unbalanced AC-OPF PVHC practices and their visualization.

AC-optimal power flow↗

Volt/VAR Optimization (VVO) Application on GridAPPS-D Platform

There is a large increment in the distributed energy resources (DERs) installation and deployments of smart sensing devices and communication infrastructure; hence, the power distribution network is swiftly evolving from a passive network to an active network. This motivates the development of advanced applications to operate power distribution systems for higher efficiency and reliability. These advanced applications are model-based and data-driven. This requires an advanced distribution management system (ADMS) to provide required data for the optimal operation of the distribution systems by coordinating various grid controllable devices. In this paper a Volt-VAR optimization (VVO) application to coordinate the grid’s legacy and new voltage control devices for conservation voltage reduction (CVR) is deployed on the GridAPPS-D platform (an open-source platform ) for ADMS application development. The VVO application is validated for various operating conditions on using modified IEEE 8500-node distribution test feeders. Further, the application is successfully deployed on the GridAPPS-D platform.

Jha, Rahul↗