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At least 91 records · Page 5

Rapid QSTS Simulations for High-Resolution Comprehensive Assessment of Distributed PV

The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modeling and impact analysis. Unlike conventional scenario-based studies, quasi-static time-series (QSTS) simulations can realistically model time-dependent voltage controllers and the diversity of potential impacts that can occur at different times of year. However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1-second resolution is often required, which could take conventional computers a computational time of 10 to 120 hours when an actual unbalanced distribution feeder is modeled. This computational burden is a clear limitation to the adoption of QSTS simulations in interconnection studies and for determining optimal control solutions for utility operations. The solutions we developed include accurate and computationally efficient QSTS methods that could be implemented in existing open-source and commercial software used by utilities and the development of methods to create high-resolution proxy data sets. This project demonstrated multiple pathways for speeding up the QSTS computation using new and innovative methods for advanced time-series analysis, faster power flow solvers, parallel processing of power flow solutions and circuit reduction. The target performance level for this project was achieved with year-long high-resolution time series solutions run in less than 5 minutes within an acceptable error.

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Resilient Inverter-Driven Black Start with Collective Parallel Grid-Forming Operation: Preprint

As the modern power systems are experiencing exceptional changes with increasing penetration of inverter-based resources (IBRs), system restoration using IBRs has received attention. Using local grid-forming (GFM) assets near consumers, engineered to establish grid voltages in the absence of a stiff grid, i.e., bottom-up restoration, a distribution system would obtain high system resilience, by not relying on the bulk power system restoration requiring significant human intervention and procedure to restore. This paper studies the technical feasibility of the novel approach with detailed electromagnetic transient (EMT) simulations. To thoroughly evaluate the potential of GFM inverters and technical challenges in IBR-driven black start, a detailed three-phase inverter model is developed, including negative-sequence control for voltage balance and a phase-by-phase current limiter to sustain momentary overloading during the black start. To examine dynamic aspects of the black start process, the EMT simulation also models transformer and motor dynamics to emulate their inrush and start-up behaviors as well as network dynamics. In addition, active involvement of grid-following distributed energy resources (DER) is also studied to facilitate the black start process. It is shown that, by allowing multiple GFM inverters to collectively black start without master-slave coordination, a system can achieve high resilience even with a fraction of assets lost. Two test cases of inverter-driven black start using two and one GFM inverters, respectively, for a heavily unbalanced 2-MVA distribution feeder are demonstrated. Takeaways for further study and field deployment are provided.

grid-forming inverter↗

Resilient Inverter-Driven Black Start with Collective Parallel Grid-Forming Operation

As modern power systems are experiencing exceptional changes with increasing penetrations of inverter-based resources (IBRs), system restoration using IBRs has received attention. Using local grid-forming (GFM) assets near consumers, engineered to establish grid voltages in the absence of a stiff grid, i.e., bottom-up restoration, a distribution system could obtain high system resilience by not relying on the bulk power system restoration, which requires significant human intervention and procedure. This paper studies the technical feasibility of the novel approach with detailed electromagnetic transient (EMT) simulations. To thoroughly evaluate the potential of GFM inverters and the technical challenges in IBR-driven black start, a detailed three-phase inverter model is developed, including negative-sequence control for voltage balance and a phase-by- phase current limiter to sustain momentary overloading during the black start. To examine dynamic aspects of the black-start process, the EMT simulation also models transformer and motor dynamics to emulate their inrush and startup behaviors as well as network dynamics. In addition, active involvement of grid- following distributed energy resources is also studied to facilitate the black-start process. By allowing multiple GFM inverters to collectively black start without leader-follower coordination, we demonstrate that a system can achieve high resilience even with a fraction of assets lost. Two test cases of inverter-driven black start, using two and one GFM inverters, respectively, for a heavily unbalanced 2-MVA distribution feeder are demonstrated. Takeaways for further study and field deployment are provided.

grid-forming inverter↗

Performance Evaluation of a Novel Sequence-Based Directional Detection Strategy for Protection of Active Distribution Networks

Directional elements are relied on to achieve selectivity in fault detection in power systems. Although such elements have been deployed successfully for many years, there is an increased need for novel methods to deal with the unique challenges of directional protection in modern distribution networks. This article analyzes the impact of inverter-based resources (IBRs) on existing directional protection methods in distribution systems. It identifies parts of such elements that pose a risk of misoperation when IBRs are used in distribution networks. The authors have developed a new directional detection method for unbalanced faults in such networks using superimposed symmetrical sequence quantities. The phase angle of the superimposed negative sequence admittance is used to determine fault direction. The paper also presents a real-time co-simulation platform between a simulated distribution system and physical protection relay, using OPAL-RT. An SEL-411L relay is used to program the detection algorithm. This hardware-in-the-loop (HIL) setup is used to verify the performance of the method and the results are compared with existing directional methods

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Exactness of OPF Relaxation on Three-phase Radial Networks with Delta Connections

Simulations have shown that while semi-definite relaxations of AC optimal power flow (AC-OPF) on three-phase radial networks with only wye connections tend to be exact, the presence of delta connections seem to render them inexact. This paper shows that such inexactness originates from the non-uniqueness of relaxation solutions and numerical errors amplified by the non-uniqueness. This finding motivates two algorithms to recover the exact solution of AC-OPF in unbalanced distribution networks featuring both wye and delta connections. In simulations using IEEE 13, 37 and 123-bus systems, the proposed algorithms provide exact optimal solutions up to numerical precision.

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Retracted Article: Distributed energy management for networked microgrids in a three-phase unbalanced distribution network

Owing to increased penetration of three-phase and single-phase microgrids, distributed energy resources (DERs), and responsive loads, the maintenance of a three-phase balance by distribution networks is a significant challenge. Existing literature on distributed energy management for networked microgrids generally neglects the distribution network or employs a simplified phase balanced distribution network; thus, these evaluations are not applicable. Further, the underlying mutual coupling between the different phases of distribution feeders results in a more challenging situation. Here, to solve this issue, this study sought to propose distributed energy management based on a three-phase unbalanced distribution network. Various three-phase or single-phase microgrids, utility-owned DERs, and responsive loads were coordinated through iteratively adjusted price signals. Based on the price signals received, the microgrid controllers (MCs) and distribution management system (DMS) updated the schedules of the DERs and responsive loads under their jurisdiction separately. The price signals were then updated according to the generation-load mismatch at each node and distributed to the corresponding MCs and DMS for the next iteration. The iteration continued until a sufficiently small generation-load mismatch was achieved at all nodes, that is, a balanced generation and load at all nodes under the agreed price signals. Considering a three-phase unbalanced distribution network, the price signals were determined per phase per node. Overall, the proposed distributed energy management coordinates microgrids, utility-owned DERs, responsive loads with guaranteed network constraints, and preserves the privacy of microgrid customers. This distributed energy management method was further demonstrated through various case studies on a three-phase networked microgrid test system.

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Stochastic multi-period optimal dispatch of energy storage in unbalanced distribution feeders

This report presents a convex, multi-period, AC-feasible Optimal Power Flow (OPF) framework that robustly dispatches flexible demand-side resources in unbalanced distribution feeders against uncertainty in very-short timescale solar Photo-Voltaic (PV) forecasts. This is valuable for power systems with significant behind-the-meter solar PV generation as their operation is affected by uncertainty from forecasts of demand and solar PV generation. The aim of this work is then to ensure the feasibility and reliability of distribution system operation under high solar PV penetration. We develop and present a novel, robust OPF formulation that accounts for both the nonlinear power flow constraints and the uncertainty in forecasts. This is achieved by linearizing an optimal trajectory and using first-order methods to systematically tighten voltage bounds. Case studies on a realistic distribution feeder shows the effectiveness of a receding-horizon implementation.

25 ENERGY STORAGE↗

CP‐SyNet: A tool for generating customised cyber‐power synthetic network for distribution systems with distributed energy resources

Abstract The integration of distributed energy resources and advancement in information technology has enabled the transition of traditional power distribution systems to active cyber‐physical distribution systems. A growing amount of research has been done on the modelling, analysis, and optimisation of power distribution system behaviour. However, existing publicly available distribution test feeders are limited in numbers and have minimal features. Furthermore, these test feeders do not include cyber models and are not customisable. To bridge this gap, we propose and develop Cyber‐physical synthetic distribution system network (CP‐SyNet), a tool for generating customisable cyber‐physical synthetic distribution test feeders. CP‐SyNet generates three‐phase unbalanced test feeders according to users' requirements, while simultaneously considering both the cyber side and the physical side of the network for cyber‐physical analysis. The physical test network is developed using a graph‐theoretical approach that employs information from existing test feeders. The cyber side considers an equivalent communication network by transforming the physical topology into possible and feasible simulated network. Two examples are presented to demonstrate the feasibility of the proposed framework to generate cyber‐physical test feeders.

Wang, Lusha↗

2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

Recent proliferation of distributed energy sources in distribution or sub-transmission systems necessitates close monitoring of these three-phase power grids which typically operate under unbalanced loading conditions. Unlike the transmission systems where the network equations are commonly based on the positive sequence component models, a detailed three phase model will have to be used in implementing network applications for these systems. In the specific case of the state estimator, where measurement and parameter errors may bias the solution, bad data and parameter error detection algorithms should also be incorporated. Implementing the state estimator and error detection algorithms for three-phase systems impose additional computational burden and modifications to the state estimation code. This paper proposes a practical solution to avoid these issues by using synchronized phasor measurements and modal decoupling. The previously developed parameter error detection algorithm based on the normalized Lagrange multipliers (NLM) test is applied to the measurements independently in each mode in parallel, not only saving CPU time but also avoiding new code development for a three-phase estimator. Different parameter error scenarios are created and tested to verify the effectiveness of the proposed error detection approach.

Khalili, Ramtin↗

Evaluation of an Interferometric Sensor for In-Space Detection of Gas Leaks

Space mission planning often involves long-term storage of volatile liquids or high-pressure gases. These may include cryogenic fuels and oxidizers, high-pressure gases, and life-support-critical consumables. The risk associated with the storage of fluids and gases in space systems has long been an issue and the ability to retain these fluids is often tied to mission success. A leak in the storage or distribution system can cause many different problems, including a simple, but mission endangering, loss of inventory or, in severe cases, unbalanced thrust loads on a flight vehicle. Cryogenic propellants are especially difficult to store, especially over a long duration. The propellant can boil off and be lost through the insulating walls of the tank or simple thermal cycling of the fittings, valves, and propellant feed lines may unseat seals allowing the fluid to escape. Current NASA missions call for long-duration in-space storage of propellants, oxidizers, and life support supplies. Leaks of a scale detectable through a pressure drop in the storage tank are often catastrophic and have long been the focus of ground-based mitigation efforts where redundant systems are often employed. However, there is presently no technology available for detecting and monitoring low-level, but still mission-endangering, gas leaks in space. Standard in-space gas detection methods either have a very limited pressure range over which they operate effectively or are limited to certain gases. Mass spectrometer systems are able to perform the detection tasks, but their size, mass and use of high voltage, which could potentially lead to an arc that ignites a combustible propellent, severely limit their usefulness in a space system. In this paper, we present results from testing of the light-based interferometric gas monitoring and leak detection sensor shown in Fig. 1. The output of the sensor is an interference fringe pattern that is a function of the gas density, and commensurate index of refraction, in the sample region. Changes in the density of gas cause the interference fringes to move across a photodiode detector, providing a temporal history of the leak. The sensor is fiber coupled and constructed from solid optics, allowing for placement almost anywhere on the spacecraft. It is also advantageous in that it consumes very little power and does not introduce an ignition source. Data are presented demonstrating the capability of the sensor to measure density variations in different gas species. In addition, the transient response of the sensor in vacuum is demonstrated. These data extend and improve upon the results previously presented by the authors in Ref. [1].

Polzin, Kurt A.↗

Model-Free Voltage Control of Active Distribution System with PVs Using Surrogate Model-Based Deep Reinforcement Learning

Accurate knowledge of the distribution system topology and parameters is required to achieve good voltage control performance, but this is difficult to obtain in practice. This paper proposes a physical-model-free voltage control method based on a surrogate-model-enabled deep reinforcement learning approach. Specifically, a surrogate model is trained in a supervised manner using the recorded limited number of historical data to learn the relationship between the power injections and voltage fluctuations of each node. Then, the deep reinforcement learning algorithm is applied to learn an optimal control strategy from the experiences obtained by continuous interactions with the surrogate model. The proposed method can achieve physical-model-free control of unbalanced distribution network and inform real-time decisions to deal with fast voltage fluctuations caused by the rapid variation of PV generation. Simulation results on an unbalance IEEE 123-bus system show that the proposed method can achieve similar performance as that of perfect physical-model-based approaches while being advantageous over other traditional methods.

active distribution network↗

Parallel Grid-Forming Inverter-Driven Black Start: Power-Hardware-in-the-Loop Validation: Preprint

With power systems encountering increasing deployment levels of inverter-based resources (IBRs), system restoration using grid-forming (GFM) IBRs has gained attention. Engineered to establish grid voltages in the absence of a stiff grid, black-start-capable GFM IBRs are expected to enhance power system resilience by playing a critical role in bottom-up system restoration. This paper experimentally studies the feasibility of the novel approach through power-hardware-in-the-loop (PHIL) testing and validation with a commercial GFM inverter. The PHIL test setup demonstrates an inverter-driven black start of a 5-MW unbalanced distribution feeder where two GFM inverters collectively black start the feeder: one is a commercial hardware GFM inverter interacting through the PHIL interface, and the other is a software GFM emulated by a real-time simulation with full electromagnetic transient (EMT) models. Both GFM inverters are equipped with negative-sequence voltage control to suppress the voltage imbalance resulting from the unbalanced loading, allowing us to study the dynamic interactions between the GFMs with their control parameters unknown. To evaluate the dynamic behavior of the GFM inverters under the entire black-start process, the EMT model of the distribution system details the transformer and motor dynamics to emulate their inrush and startup behaviors. It abstracts conventional grid-connected inverter dynamics, i.e., grid-following inverters. Oscilloscope measurements of the hardware GFM inverter are also presented for critical steps. Takeaways for further study and field deployment are provided.

grid-forming inverter↗

Integrating Transactive Energy into Reliability Evaluation for a Self-healing Distribution System with Microgrid

Non-utility owned distributed energy resources (DERs) are mostly untapped currently, but they can provide many grid services such as voltage regulation and service restoration, if properly controlled, and can improve the distribution systems reliability when coordinated with utility-owned assets such as self-healing control and microgrids. This paper integrates transactive energy control into the distribution system reliability evaluation to quantitatively assess the impact of non-utility owned DERs on reliability improvement. Here, a transactive reactive power control strategy is designed to incentivize the DERs to provide reactive power support for improving voltage profiles thus enabling additional customer load restoration during an outage. Also, an operational sequence to coordinate the non-utility owned DERs with the utility owned self-healing control and utility owned microgrids is designed and integrated into the service restoration process with the operational constraints guaranteed by checking the three-phase unbalanced power flow for post-fault network reconfiguration. The reliability indices are then calculated through a Monte Carlo simulation. The transactive reactive power control strategy is tested on a four-feeder distribution system operated by Duke Energy in the U.S. Results demonstrate that the non-utility owned DERs with the transactive control improve the reliability of both the system and critical loads by more than 30%.

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Insulated Engine, 100-Pound Thrust

The design and test results of an insulated, 100-pound thrust engine capable of delivering high performance, providing long, steady state and pulse mode endurance, and maintaining a low outside surface temperature of 4000 F, are presented. Included are descriptions of the injector designs and insulation materials investigated, plus a discussion of the thermal analysis and test results. Continuous operation in excess of 29 minutes, and start capability in excess of 4900 pulses, have been demonstrated. To allow the use of available chamber materials and coating systems under insulated conditions, the major challenge to the designer was to define an injector design that would provide gas temperatures and performance of a predetermined value. The solution was the development of an unbalanced, 8-element triplet injector having an unequal fuel distribution within each element, capable of providing a specific impulse in excess of 290 pounds at reduced wall temperatures. The design consists of a columbium chamber and nozzle utilizing a silicide coating, a columbium injector, a composite insulation system of aluminum oxide

Roth, N. R.↗

Controlled Islanding Strategy Considering Uncertainty of Renewable Energy Sources Based on Chance-constrained Model

Controlled islanding plays an essential role in preventing the blackout of power systems. Although there are several studies on this topic in the past, not enough attention is paid to the uncertainty brought by renewable energy sources (RESs) that may cause unpredictable unbalanced power and the observability of power systems after islanding that is essential for back-up black-start measures. Therefore, a novel controlled islanding model based on mixed-integer second-order cone and chance-constrained programming (MISOCCP) is proposed to address these issues. First, the uncertainty of RESs is characterized by their possibility distribution models with chance constraints, and the requirements, e. g., system observ-ability, for rapid back-up black-start measures are also considered. Then, a law of large numbers (LLN) based method is employed for converting the chance constraints into deterministic ones and reformulating the non-convex model into convex one. Finally, case studies on the revised IEEE 39-bus and 118-bus power systems as well as the comparisons among different models are given to demonstrate the effectiveness of the proposed model. The results show that the proposed model can result in less unbalanced power and better observability after islanding compared with other models.

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Dynamic State Estimation for Radial Microgrid Protection

Dynamic state estimation (DSE) is a generalization of differential protection that offers a reduced likelihood of misoperation, particularly in the case of devices with nonlinear characteristics such as transformers which are being energized. It is also useful in cases where distance protection performs poorly, such as transmission lines with series compensation or mutually coupled transmission lines. DSE has been previously applied to microgrid branch protection. This study investigates the use of DSE for protection of radial portions of a microgrid or distribution system. This can be a challenge in microgrids or distribution systems with distributed generation on account of lack of fault current from inverter-interfaced generation, varying fault current between grid- connected and islanded modes, the potential for normally-meshed operation and unbalanced operation due to single-phase loads. Admittance relaying has been investigated as a solution for protection of microgrids, though it has been observed to have issues with grounded-wye connected loads, and additional relaying is necessary to prevent misoperation.

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Coordinated Optimization and Control of Residential Solid State Power Substations in Electrical Distribution Network

This paper proposes a computationally efficient mixed integer linear programming (MILP) model for the coordinated optimization of solid-state power substations (SSPSs) in a feeder considering the full unbalanced three-phase structure of the distribution grid and its characteristics. The proposed model determines the optimal real and reactive power of each SSPS at the point of common coupling (PCC) that minimizes the operating cost and maximizes the system performance, e.g., voltage regulation and phase balancing. To improve the computational efficiency, an inscribed octagon is introduced to approximate the quadratic capacity constraints of components. Numerical simulation results show the effectiveness of the proposed model and significant improvements in voltage profiles and power imbalance between phases.

Liu, Guodong↗

Ensuring Solution Uniqueness in Three-Phase Power System State Estimation

This paper is concerned with the issue of potential non-unique solutions in three-phase state estimation. Theory of observability analysis for positive sequence power system state estimation is based on certain assumptions that avoid possibility of multiple solutions. Also, it is shown that observability of a positive sequence network remains independent of the network parameters or the operating state. When extending single-phase observability analysis directly to the three-phase case, this paper considers the possibility of converging to multiple solutions, i.e. solution non-uniqueness, even for cases where state estimator successfully converges. The study illustrates via numerical examples the likelihood of converging to entirely different solutions for certain network parameters. It also examines how the operating state, particularly under unbalanced loading, leads to solution non-uniqueness. The paper then describes an alternative approach to ensure a unique solution in three-phase state estimation. This method aims to accurately and uniquely estimate the state of any unbalanced three-phase system, irrespective of load imbalance, network configuration, existence of synchronous generators or transformers.

Power System State Estimation, Three-Phase, Distri↗