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At least 685 records · Page 38

Stochastic pre-event preparation for enhancing resilience of distribution systems

Extreme weather events are the common causes for power supply interruptions and power outages in electrical distribution systems. Improving the distribution system and enhancing its resilience is becoming crucial due to the increased frequency of extreme weather events. Preparation and allocation of multiple flexible resources, such as mobile resources, fuel resources, and labor resources before extreme weather events can mitigate the effects of extreme weather events and enhance the resilience of power distribution systems. Here, in this paper, a two-stage stochastic mixed-integer linear programming (SMILP) is proposed to optimize the preparation and resource allocation process for upcoming extreme weather events, which leads to faster and more efficient post-event restoration. The objective of the proposed two-stage SMILP is to maximize the served load and minimize the operating cost of flexible resources. The first stage in the optimization problem selects the amounts and locations of different resources. The second stage considers the operational constraints of the distribution system and repair crew scheduling constraints. The proposed stochastic pre-event preparation model is solved by a scenario decomposition method, Progressive Hedging (PH), to ease the computational complexity introduced by a large number of scenarios. Furthermore, to show the impact of solar photovoltaic (PV) generation on system resilience, three types of PV systems are considered during a power outage and the resilience improvements with different PV penetration levels are compared. Numerical results from simulations on a large-scale (more than 10,000 nodes) distribution feeder have been used to validate the effectiveness and scalability of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Simulation and Postmortem Analysis of Angeles Forest Disturbance Event

Multiple unexpected solar photovoltaic (PV) plant responses in the California region following contingencies in recent years warrant postmortem analysis leveraging digital fault recorder (DFR) data for a better understanding of such events and preventing similar events in the future. Most utilities in US, in general, possess transient stability (TS) phasor-domain models of the power grid. Since traditional phasor-based transient stability planning models cannot perform such analysis, this paper presents an approach to extract a region of such models and convert it to Electromagnetic transient (EMT) models. The approach is based on the determination of the minimum impedance-weighted spanning tree between the fault location and affected PV plants in a Western Electricity Coordinating Council (WECC) planning model followed by conversion of this region into an EMT model. The accuracy of the proposed approach is validated against DFR records obtained from the 2018 Angeles Forest disturbance event.

Samanta, Sayan↗

Advancing Energy Equity Considerations in Distribution Systems Planning

Current distribution system planning (DSP) processes do not explicitly account for energy equity considerations, such as who is most affected by power system burdens, where those burdens are concentrated, and what investments can be made to improve baseline conditions. This paper proposes an iterative framework for advancing energy equity as an objective of the DSP process, showing how measurement strategies, or metrics (informed by conceptual foundations of energy justice), can be applied to benchmark equity performance at various stages. This methodology is applied for equity-aware distributed energy resource (DER) hosting capacity analysis and outage analysis to provide critical insights on infrastructure upgrade decisions compared to a business-as-usual (BAU) case. The analysis is performed on a taxonomy feeder representing the West Coast urban/semi-urban system with augmentation of electric vehicles (EVs) and rooftop solar photovoltaic (PV) generators. The study considers disadvantaged community (DAC) and non-disadvantaged community (NDAC) load regions to enable equity-aware simulations. The results demonstrate how equity-aware planning could reveal the limitations of the traditional DSP process as DAC regions are found to have lower DER hosting capacity and higher outage vulnerability. Overall, this work provides insights on the need to incorporate energy equity as an integral part of the DSP process.

Energy Equity, Distribution System Planning, DER a↗

Fault Current Control and Protection in a Standalone DC Microgrid Using Adaptive Droop and Current Derivative

This report presents a novel fault detection, characterization, and fault current control algorithm for a standalone solar-photovoltaic (PV) based dc microgrids. The protection scheme is based on the current derivative algorithm. The overcurrent and current directional/differential comparison based protection schemes are incorporated for the dc microgrid fault characterization. For a low impedance fault, the fault current is controlled based on the current/voltage thresholds and current direction. Generally, the droop method is used to control the power-sharing between the converters by controlling the reference voltage. In this article, an adaptive droop scheme is also proposed to control the fault current by calculating a virtual resistance R droop , and to control the converter output reference voltage. For a high impedance fault, differential comparison method is used to characterize the fault. These algorithms effectively control the converter pulsewidth and reduce the flow of source current from a particular converter, which helps to increase the fault clearing time. Additionally, a trip signal is sent to the corresponding dc circuit breaker (DCCB), to isolate the faulted converter, feeder or a dc bus. The dc microgrid protection design procedure is detailed, and the performance of the proposed method is verified by simulation analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Two-Stage Deep Reinforcement Learning for Distribution System Voltage Regulation and Peak Load Management

The growing integration of distributed solar photovoltaic (PV) in distribution systems could result in adverse effects during grid operation. This paper develops a two-agent soft actor critic-based deep reinforcement learning (SAC-DRL) solution to simultaneously control PV inverters and battery energy storage systems for voltage regulation and peak demand reduction. The novel two-stage framework, featured with two different control agents, is applied for daytime and nighttime operations to enhance control performance. Comparison results with other control methods on a real feeder in Western Colorado demonstrate that the proposed method can provide advanced voltage regulation with modest active power curtailment and reduce peak load demand from feeder's head.

deep reinforcement learning↗

Control of Behind-the-Meter Resources for Enhancing the Resilience of Residential Buildings

There is increased concern about the impacts of frequent power outages, caused primarily by extreme weather conditions. With increasing behind-the-meter resources such as solar photovoltaics (PV), battery energy storage, and controllable loads, these resources - if properly coordinated - can meet critical loads even during an outage. Resilience building controls can coordinate and operate these resources to enhance the resiliency of buildings supporting critical loads for longer duration. In this paper, we present two resilience building controls: rule-based control and model predictive control (MPC). We simulated various scenarios considering different locations, seasons, outage types, and times of outages to evaluate the performance of resilience controls. The results show that MPC-based control can enhance resilience up to 65% compared to rule-based control. Similarly, PV self-consumption and occupant thermal comfort both increase during outages with MPC-based control.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

Understanding Improvements in Coalesced Epilayers Grown over Nanopatterned Substrates

Nanopatterned substrates provide opportunities for reducing costs of high-efficiency III-V devices through methods such as substrate reuse and growth on cheaper substrates. In this work, we aim to better understand some of the fundamental challenges of growing high quality III-V material on nanopatterned substrates. Through specific pattern orientations and control of overgrowth morphology, we report that smooth and defect-free coalesced III-V epilayers are attainable over nanopatterned GaAs substrates.

coalescense↗

Platform for Accurate Efficiency Quantification of > 35% Efficient Thermophotovoltaic Cells

Thermophotovoltaic (TPV) devices convert thermal radiation directly into electricity using semiconductor diodes and have a variety of uses from waste heat recovery to energy storage to primary power conversion. Recent results have demonstrated promising cells nearing and surpassing 30% conversion efficiency. As TPV cells continue to increase in efficiency, they become attractive for a wider range of applications. Their efficiencies must be quantified in a standardized fashion to compare results accurately across research groups. Here, we outline and quantify the most important characteristics of an accurate and precise TPV efficiency measurement. Using a custom-built measurement apparatus that takes these characteristics into account, we report 19 cells with greater than 30% conversion efficiency and 2 cells with greater than 35% conversion efficiency. This confirms that our reported cell efficiencies are not simply those of hero cells but rather of a distribution of cells that can be produced in a consistent, high-quality process.

III-V↗

Planarization of Rough (100) GaAs Substrates via Growth by Hydride Vapor Phase Epitaxy

Wafer reuse techniques help offset the cost of III-V growth substrates by using a single wafer for multiple growths, but costly re-polishing after device removal limits the end benefit. In this work, we present planarization growth by hydride vapor-phase epitaxy (HVPE), a potentially low-cost growth technique, as a method of smoothing rough substrates for subsequent high-quality device growth without the need for polishing. First, we show there is a threshold for allowable substrate roughness without device degradation by comparing devices grown by organometallic vapor-phase epitaxy (OMVPE) on epi-ready polished and pre-polished substrates that did not have the final epi-ready polish. We then demonstrate successful smoothing with HVPE growth on substrates with different surface morphologies, with features ranging from general roughness to large facets. Initial devices grown by HVPE on a pre-polished substate showed no degradation compared to a control wafer, indicating that planarizing rough substrates through HVPE growth is a promising path toward being able to use rough substrates directly for growth, without costly polishing steps.

GaAs↗

Spectral Rear Irradiance Testing and Modeling for Degradation and Performance of Solar Fields

This work investigates how the spectrum of irradiance incident on the rear of solar modules impacts the degradation and performance of backsheets. We model the spectral irradiance incident on the rear of modules through raytrace simulations and validate with measured field data collected from a 75kW single axis-tracked bifacial test site. A generic equation to estimate relative degradation is proposed, and we show that current acceleration factors for UV damage in chambers can be sub-estimate up to 4.5% absolute from the usually assumed 10% dosage on the rear surfaces.

bifacial performance↗

Resilience Metrics for Building-Level Electrical Distribution Systems with Energy Storage

The energy system infrastructure that delivers power to a building's loads needs to be resilient to withstand and recover from extreme outages (e.g., grid faults that leave millions of people without power during severe weather events). Building-level electrical distribution systems (BEDSs) distribute power from a building's energy sources - including the grid, solar photovoltaic (PV) panels, and batteries - to its loads, including lighting, HVAC, and plug loads. BEDS with storage can provide resilience by distributing local electricity supply to critical loads during an outage. Quantitative metrics are needed to assess the resilience improvements associated with new BEDS and storage system technologies. In this paper, we apply an existing metric, the probability of outage survival curve (POSC), to BEDS with storage and propose novel metrics that improve upon POSC. Through a simulation-based case study, we demonstrate how these metrics are impacted by the BEDS design and how they can be used to design a resilient system.

buildings↗

Virtual Synchronous Generator Control of Multi-port Autonomous Reconfigurable Solar Plants (MARS)

Multi-port autonomous reconfigurable solar power plant (MARS) is an integrated concept for integration of solar photovoltaic (PV) and energy storage systems (ESS) to transmission alternating current (ac) grid and high-voltage direct current (HVdc) links. The integrated development incorporates advanced control methods to provide enhanced grid ancillary services such as fast frequency responses and dynamic voltage support. In this paper, the virtual synchronous generator (VSG) control algorithm of MARS is discussed. The proposed VSG-based control enables enhanced synthetic inertial response and flexible frequency response characteristics of hybrid PV and ESS power plants in accordance with grid ancillary service requirements. Multi-port power electronics interface allows controlled emergency power support from MARS to local transmission ac grid and remote grid through the HVdc link. The performance of VSG control is validated using a reduced-order model of MARS in Simulink. Methods for estimating grid ancillary service capabilities of MARS are also discussed.

Pan, Jiuping↗

Reliability Analysis of Power Grids Considering Component Failures of Variable Energy Resources

This paper proposes an improved model for the reliability assessment of power systems considering component failures of variable energy resources (VER). The inherent intermittency of VER such as solar photovoltaic (PV) and wind farms, along with their susceptibility to component failures, present significant challenges to reliable system operation. These issues, combined with power grid operation and network constraints, complicate the reliable operation of VER-integrated power systems. Here, to address these concerns, this paper introduces a reliability assessment framework that considers VER input variability, its impact on component availability, and their resulting impact on overall system reliability. Stochastic models based on discrete Markov processes are developed to incorporate variable irradiance, wind speeds, and their effects on PV and wind component failure rates. A next-event and state transition-based approach is then developed to integrate the stochastic models into a mixed-timing sequential Monte Carlo simulation framework for composite reliability assessment. Case studies on the RTS-GMLC system demonstrate the effectiveness of the proposed model in evaluating the reliability of VER-integrated systems.

Pandit, Dilip [Sandia National Laboratories (SNL-N↗

Community-Based Transactive Coordination Mechanism for Enabling Grid Edge Systems

The changing landscape of the electricity industry, characterized by a surge in distributed energy resources (DERs) and proactive customers, necessitates practical solutions for coordinated operations especially at the distribution-level. This paper introduces a community-based transactive coordination mechanism designed to incentivize customers for providing localized and system-level services reflected through real-time prices. The work presents a bidding approach for communities with DERs, such as solar photovoltaic (PV) and battery energy storage systems (BESS), to formulate their price-responsiveness for retail energy coordination, emphasizing a community-centric model. By sending bidding curves to a third-party, the mechanism enables customers with DER assets to actively participate in localized coordination with the load serving entity (LSE), thereby supplementing each other’s and even the utilities needs through a shared energy economy. The proposed transactive mechanism is implemented leveraging a co-simulation framework that integrates a distribution grid simulator and Python-based agents for performance evaluation. Collaboration with a local utility to access real distribution feeder models and consumption profiles yields simulation results demonstrating the potential to reduce costs by 12\% for communities with DERs like PV and BESS.

Community-based coordination, grid-edge systems, R↗

Grid Value Analysis of Medium-Voltage Back-to-Back Converter on DER Hosting Enhancement

This paper presents an analysis of the value that can be realized by medium-voltage back-to-back (MVB2B) converters in terms of the increased utilization rate of distributed energy resources (DERs) and the improvement in operational conditions. A systematic, transferrable, and scalable methodology has been designed to analyze and quantify the increased DER value from three perspectives: 1) curtailment reduction of the DER generation, 2) size reduction of the energy storage needed to otherwise realize DER hosting levels, and 3) hosting capacity improvement of the DERs compared to the base distribution circuit capability. In the case study, the proposed methodology is applied to two utility distribution systems for analysis and quantification of the grid value of the MVB2B converter, installed in the distribution circuit, and provided to the solar photovoltaic (PV) DERs. Here, the analysis results demonstrate that the MVB2B converter can deliver significant value to the PV hosting enhancement of two adjacent distribution systems when they are connected by the MVB2B converter. Based on this case study, this paper analyzes and summarizes the approximate realized grid value of the MVB2B converter for distribution systems dominated by different shares of customer classes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Voltage Estimation in Low-Voltage Distribution Grids with Distributed Energy Resources

Present distribution grids generally have limited sensing capabilities and are therefore characterized by low observability. Improved observability is a prerequisite for increasing the hosting capacity of distributed energy resources such as solar photovoltaics (PV) in distribution grids. In this context, this paper presents learning-aided low-voltage estimation using untapped but readily available and widely distributed sensors from cable television (CATV) networks. The cable broadband sensors offer timely local voltage magnitude sensing with 5-minute resolution and can provide an order of magnitude more data on the time-varying state of a secondary distribution system than currently deployed utility sensors. The proposed solution incorporates voltage readings from neighboring CATV sensors, taking into account spatio-temporal aspects of the observations, and estimates single-phase voltage magnitudes at all non-monitored low-voltage buses using random forests. The effectiveness of the proposed approach was demonstrated using a multi-phase 1572-bus feeder from the SMART-DS data set for two case studies passive distribution feeder (without PV) and active distribution feeder (with PV). The analysis was conducted on simulated data, and the results show voltage estimates with a high degree of accuracy, even at extremely low percentages of observable nodes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Operational Simulation of Multi-Functional Charging Station for Sustainable Transportation

As transportation systems move toward electrification and decarbonization, multifunctional charging stations (MFCS) are emerging as key infrastructure for electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs). This paper presents a simulation model of an MFCS that integrates solar photovoltaic (PV), wind power, battery storage, hydrogen (\mathrm{H}_{2}) production, dual-pressure \mathrm{H}_{2} storage, fuel cells, and dynamic grid interactions. The model simulates daily operations using 5 -minute resolution data to capture realtime variability in renewable energy (RE), demand, and electricity prices. A flexible dispatch algorithm dynamically allocates energy for EV charging, \mathrm{H}_{2} production, storage, and grid transactions while respecting system constraints. Results show that the MFCS effectively prioritizes RE usage, minimizes waste, meets diverse energy demands, and achieves net operational profit. The model serves as a valuable decision-support tool for designing and optimizing integrated clean energy hubs for zero-emission transportation.

Gbadegoye, Jeremiah [University of Tennessee, Knox↗