Criticality of Inverter Controller Order in Power System Dynamic Studies – Case Study: Maui Island
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Kenyon, Rick Wallace↗
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Results for “Power distribution systems”
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Power System Wildfire Risks and Potential Solutions: A Literature Review & Proposed Metric
Several fire risk evaluation, fire tracking, and fire response resources are available. The risk metrics and fire response programs are sometimes modified to include a power system context. The risk metrics often evaluate the risk of fires causing power system faults or outages, especially on transmission systems. The response programs are modified to ensure the safety of power system equipment and first responders as well as to coordinate power system outages to both ensure safety during an active fire and prevent fire ignition during high risk periods. Although some aspects of wildfire responses have been adapted to include power system concerns, adaptations to power system operations and maintenance to include wildfire risks and responses are still nascent. In particular, a risk metric that evaluates the potential for power system components to ignite wildfires is needed to help guide power system upgrade efforts and power system fire safety measures. This document serves as a brief literature review of wildfire risk metrics and response programs and how they relate to power systems. It also includes a proposed risk metric and structure for describing the risk of a power system component igniting a fire.
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A Transactive Approach for Service Restoration Utilizing Customer Load Flexibility and Grid-Edge Resources: Preprint
This paper develops a transactive energy system model to restore electricity to customers in an isolated distribution system after an outage. The model engages a variety of customer types -- prosumers, flexible loads, critical/noncritical customers, and distributed generators -- as active participants in the restoration process. Unlike many existing transactive approaches, the proposed model is developed for service restoration and accounts for various customer types and their \textit{autonomy} and \textit{privacy} through an iterative approach to determine the optimal market price, while maintaining system-level power flow and voltage constraints. The advantages of the proposed approach are numerically validated on a modified IEEE 123-bus test system.
distributed energy resources↗
Adopting Dynamic VAR Compensators to Mitigate PV Impacts on Unbalanced Distribution Systems
Not Available
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Decentralized Distribution System Restoration with Grid-Forming/Following Inverter-Based Resources
The high penetration of distributed energy resources (DERs) in active distribution systems has posed challenges to the centralized distribution system restoration (DSR) strategies in current practice. On the other hand, the advancement in smart inverter technologies enables the bottom-up restoration capability. This paper is motivated to develop a 3-layered hierarchical framework for decentralized DSR, based on the grid-forming (GFM) and grid-following (GFL) grid-edge inverters. The first layer presents the tertiary control, which determines the load pickup schedule and generation dispatch of DERs, using the alternating direction method of the multipliers algorithm. The second layer consists of two control functions: GFM control, which regulates voltage and frequency, establishing a stable grid for GFL inverters to follow; and GFL control, which regulates the real and reactive power. In the third layer, the primary control is proposed to regulate the inverter voltage and current, which is developed based on the virtual oscillator control (VOC). Furthermore, the developed framework is tested in the modified IEEE 13-node test feeder. Two scenarios of grid-connected and islanded operating modes are designed, and simulation results demonstrate the effectiveness of decentralized DSR strategies for controlling grid-edge inverters to enhance the distribution system resilience.
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Chapter 8 - Testing and Evaluation Methods for Protection Systems
In this chapter, we aim to present different approaches used formally and informally for the evaluation of protection devices and schemes. This chapter starts with presenting background on generalization of protection device components, followed by the resources necessary to evaluate the protection system. Further, this chapter presents the different approaches used in protection evaluation with their advantages and disadvantages. Finally, this chapter closes by presenting background on technology readiness level metrics. Technology readiness level metric is borrowed from the space industry for the purpose of comparing the maturity of the different protection technologies and using the appropriate evaluation methods from the list presented here.
power systems↗
Advanced testbed to assess disturbances in electrical grids with DERs using relays/meters with varying sampling frequencies
Not Available
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Toward Statistical Real-Time Power Fault Detection
We propose statistical fault detection methodology based on high-frequency data streams that are becoming available in modern power grids. Our approach can be treated as an online (sequential) change point monitoring methodology. However, due to the mostly unexplored and very nonstandard structure of high-frequency power grid streaming data, substantial new statistical development is required to make this methodology practically applicable. The paper includes development of scalar detectors based on multichannel data streams, determination of data-driven alarm thresholds and investigation of the performance and robustness of the new tools. Due to a reasonably large database of faults, we can calculate frequencies of false and correct fault signals, and recommend implementations that optimize these empirical success rates.
bolted faults↗
Identification of Voltage Stability Critical Locations for Future Large Grids With High Renewable Mix
Not Available
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Grid Optimization Competition on Synthetic and Industrial Power Systems
This paper summarizes a grid optimization (GO) competition effort in the United States to find the best solution strategies for up to interconnect-scale power system networks with around 32,000 buses. The optimization problem is a mixedinteger, non-convex non-linear problem, (MINLP) and includes discrete variables such as unit commitment and line switching, control settings (transformer taps and phase shifters with impedance correction tables), and bus shunts. The case study includes six actual industry grids as well as 16 realistic synthetic grids created by three different dataset teams. The winners are selected and ranked based on scoring criteria, which consider the solution quality (such as objective functions) within time limits. Nine winner teams are selected from 26 competitor teams. The results achieved by different teams are described and the performance of different algorithms on synthetic grids and actual industry grids are compared and analyzed.
mixed-integer non-linear programming↗
A Framework to Evaluate the Grid Impacts of EV Fleet Charging Solutions
Growing Electric vehicle (EV) adoption in residential and commercial applications is driving the need for the charging infrastructures required to fulfill the charging needs. The resulting increase in demand for electric power will add a significant load to the electric grid, which could negatively impact the grid operation. EVs are power electronic loads and draw harmonic currents which can lead to a host of power quality issues. Therefore, it is crucial to assess the grid impacts and management of EV charging loads to ensure the reliable operation of the electric grid. In this paper, we develop a framework to help determine power-quality impacts given an EV charging schedule on the system. We compare the performance of unmanaged and managed charging solutions on factors like voltage drop, flicker, harmonic distortion and the peak site load - based on the EV depot in Hazelwood school district. The results allow insights into operation and site design of EV depots.
ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗
Metal Oxide Varistor (MOV) Lifetime Estimation with Impulse-Based Testing in PV Inverter Systems
Surges caused by lightning strikes could damage electrical components in photovoltaic (PV) systems. Metal oxide varistors (MOVs) are commonly used to protect PV systems from lightning strikes. This paper proposes a holistic impulse-based MOV lifetime estimation framework. The impacts of peak current and fault duration induced by lightning events are considered in the MOV lifetime estimation framework. Moreover, the impact of different parameter combinations on MOV lifetime estimation is analyzed. The effectiveness of the proposed work is validated in a PV inverter test system developed in MATLAB/Simulink.
lifetime estimation↗
On the Computational Viability of Quantum Optimization for PMU Placement
Using optimal phasor measurement unit placement as a prototypical problem, we assess the computational viability of the current generation D-Wave Systems 2000Q quantum annealer for power systems design problems. We reformulate minimum dominating set for the annealer hardware, solve the reformulation for a standard set of IEEE test systems, and benchmark solution quality and time to solution against the CPLEX optimizer and simulated annealing. For some problem instances the 2000Q outpaces CPLEX. For instances where the 2000Q underperforms with respect to CPLEX and simulated annealing, we suggest hardware improvements for the next generation of quantum annealers.
hardware↗
A Modified Maximum Entropy Inverse Reinforcement Learning Approach for Microgrid Energy Scheduling
Increasing popularity of integrating distributed energy resources (DERs) into the power system brings a challenge to optimize the microgrid dispatch policy. The reinforcement learning methods suffer from a long-time problem with the theoretical assumption of the objective/reward function for the microgrid system. Although the traditional inverse reinforcement learning (IRL) approaches can solve this problem to some extent, they encounter a limitation of complex computations for state visitation frequency in the large and continuous state space. To alleviate this limitation, we propose a modified maximum entropy IRL (MMIRL) method to extract the reward function from the expert demonstrations for solving the microgrid energy scheduling problem. The proposed MMIRL algorithm is promising in recovering the reward function and learning the dispatch policy compared to conventional approaches. Case studies are performed in an energy arbitrage problem and a microgrid system with DERs. Results substantiate that the proposed MMIRL approach can learn the dispatch policy with more than 99% efficiency and outperforms other comparative methods.
artificial intelligence, reinforcement learning, m↗
DQ Admittance Extraction for Inverter-Based Resources
The power grid industry is pushing for electromagnetic transient (EMT)-based studies for generation interconnection and planning process due to high penetrations of inverter-based resource (IBRs). Vendor-specific and site-specific black-box IBR models are preferred in those simulation studies. For small-signal analysis, measurement-based admittance models are necessary. In this paper, we demonstrate the extraction of frequency-domain dq frame IBR models. These linear models are specific to operating conditions. We demonstrate two extraction methods: frequency scan and a step response-based method. The latter relies on converting time-domain responses to Laplace-domain expressions via eigensystem realization analysis (ERA). Both can lead to dq admittance representation and the latter is time saving.
admittance model↗
Quantifying Solar PV Variability at Multiple Timescales for Power Systems Studies: Preprint
Increasing penetration of solar photovoltaics (PV) has concerned power system operators about their ability to balance load and generation over multiple timescales and maintain acceptable frequency profile because of the variability and uncertainty associated with solar PV. This paper focuses on developing metrics to quantify solar PV variability at multiple temporal scales ranging from seconds to an hour to help power system operators and planners better understand and account for solar PV variability under high solar PV penetration. Fourier coefficients of solar irradiation spectrum and average size of solar irradiation ramps over a day are the two metrics that are used to quantity the variability. It is shown that by using the two metrics the days with highest and lowest solar irradiation variability can be identified, which is useful information for operations planning or long-term power system planning studies. The key findings of the paper are (i) single sensor-based variability quantification can significantly exaggerate the variability of a solar PV plant, particularly at seconds to 1-min temporal resolution, (ii) at 1-minute or lower temporal resolutions, single sensor-based variability quantification of an entire plant can be fairly accurate, with the accuracy increasing as the temporal resolution reduces from 1-minute to 1-hour, (iii) at each 1-minute and lower temporal resolutions, maximum solar irradiation ramps appear to be independent of the geographical location of the sensor, and (iv) significant reduction in solar PV plant variability over a region with multiple plants is possible at all temporal scales, but more high quality, high temporal resolution data is needed to quantify the reduction with high confidence.
photovoltaics↗
An Advanced Synchronized Time Digital Grid Twin Testbed for Relay Misoperation Analysis of Electrical Fault Type Detection Algorithms
Distributed energy resources and the number of relays are expected to rise in modern electrical grids; consequently, relay misoperations are also expected to grow. Relays can detect electrical fault types using an internal algorithm and can display the result using light indicators on the front of the relay. However, some relays’ internal algorithms for predicting types of electrical faults could be improved. This study assesses a relay’s external and internal algorithms with an Advanced Synchronized Time Digital Grid Twin (ASTDGT) testbed with paired relays. A misoperation relay analysis focused on measuring the accuracy of using the boundary admittance (the external algorithm) versus the set-default (the internal algorithm) relay method to determine the electrical fault types was performed. In this study, the internal and external relay algorithms were assessed with a synchronized time digital grid twin testbed using a real-time simulator. This testbed evaluated two sets of logic at the same time with the digital grid twin and paired relays in the loop. Different types of electrical faults were simulated, and the relays’ recorded events and electrical fault light indicator states were collected from the human–machine interfaces. This ASTDGT testbed with paired relays successfully evaluated the relay algorithm misoperations. The boundary admittance method had an accuracy of 100% for line-to-line, line-to-ground, and line-to-line ground faults.
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Cybersecurity for Fast Charging EV Infrastructure
The integration of electric vehicles (EVs) into electric grid operations can potentially leave the grid vulnerable to cyberattacks from both legacy and new equipment and protocols, including extreme fast-charging infrastructure. This paper introduces a co-simulation platform to perform cyber vulnerability analysis of EV charging infrastructure and its dependencies on communications and control systems. Grid impact scenarios through linkages to power system simulation tools such as OpenDSS and vehicle infrastructure-specific attack paths are discussed. An adaptive platform that assists with predicting and solving evolving cybersecurity challenges is demonstrated with a cyber-energy emulation that accelerates the analysis of cyberattacks and system behavior.
ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗