Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Power distribution”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

LuSEE-night power distribution system design

The Lunar Surface Electromagnetic Experiment at Night (LuSEE-Night) is a low-frequency, 0.5 to 50 MHz, radio experiment on the radio-quiet far side of the Moon. The instrument will be launched by NASA Commercial Lunar Payload Services in 2026. The LuSEE-Night instrument core is composed of a radio frequency spectrometer (SPT) processing signals from four antennas, the Data Controller Board (DCB), low electromagnetic interference (EMI) Picket Fence Power Supply (PFPS), and Power Distribution Unit (PDU). The battery powers the instrument during the lunar night and stores energy harvested by the solar panel array during the lunar day. The battery charging is controlled by the Power Conditioning and Distribution Unit (PCDU). The unregulated power is supplied either by the SpaceCraft (S/C) or the battery and gets distributed to the PFPS, communication radio, heaters, and deployables through the PDU. The PFPS generates all regulated low-voltage rails using switching regulation synchronized to the LuSEE-Night clock, which ensures self-generated EMI will be confined to well-defined frequency bins. Here, we discussed the unregulated power distribution system architecture and functionality. The PDU engineering and flight modules are developed and characterized to confirm compliance with LuSEE-Night requirements. At the time of writing, all power subsystem components have been integrated into the payload.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Systems and methods for distributed power system model calibration

A computing device for distributed power system model calibration is provided. The computing device is programmed to receive event data and model response data associated with a model to simulate, wherein the model includes a plurality of parameters, divide the event data into a plurality of sets, wherein each set includes associated parameters, and transmit the plurality of sets of event data to a plurality of client nodes. Each client node of the plurality of client nodes is programmed to analyze a corresponding set of event data to determine updated parameters for the model. The computing device is further programmed to receive a plurality of updated parameters for the model from the plurality of client nodes and analyze the received plurality of updated parameters to determine at least one adjusted parameter.

Wang, Honggang↗
DOE OSTI2021

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration: Preprint

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

High performance protonic ceramic fuel cell systems for distributed power generation

The technology landscape around distributed generation continues to evolve in response to increasing demand for high-efficiency, low-emission, low-cost power generation. While emerging distributed power technologies, such as solid oxide fuel cells (SOFCs), continue to advance, they still face challenges due to their high capital costs, and shorter lifetimes that typically arise from electrochemical stack performance degradation at high operating temperatures (>750 °C). Recent advancements in protonic ceramic fuel cells (PCFCs) offer the potential to mitigate drawbacks of their higher temperature SOFC counterparts by enabling lower operating temperatures (550 °C–600 °C) with acceptable power densities. Here the present work leverages the recent progress in protonic ceramic cell and stack technology development to generate viable system configurations and evaluate the energetic performance potential of PCFC-based systems for stationary power generation. Process system engineering of two water-neutral system concepts, which provide 25 kW of electric power and process hot water, are presented and evaluated through sensitivity studies. Stack design parameters are altered and used to gauge the effect on system performance characteristics, including fuel cell stack and balance-of-plant sizing requirements, and electric and cogeneration efficiencies. The study finds that the potentially high per-pass fuel utilization capability of PCFC stacks could enable unprecedented electric efficiencies approaching 70% without hybridization with other prime movers.

25 ENERGY STORAGE↗
DOE OSTI2026

Laboratory Evaluation of Federated, Hierarchical Controls for Distribution Power System Management: Preprint

The connection of more loads and distributed energy resources (DERs) to the distribution power system brings both challenges and opportunities to system operators. There are opportunities to aggregate flexible loads and DERs to provide transmission grid services, but the coordinated actions of DERs being managed by independent, third-party DER aggregators to support transmission system operations can present challenges. We developed a federated DER management architecture and control framework that aims to manage heterogeneous DERs to deliver reliable transmission grid services while respecting distribution system constraints. The controls include stochastic day-ahead optimization, model predictive control, and a simple real-time management scheme. We present simulation results obtained from a realistic laboratory test bed of federated controls managing DERs within a substation service area to make the substation net power follow the optimal net power determined by the day-ahead optimization based on cost and limiting reverse power flow.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Co-Simulation of Electric Power Distribution Systems and Buildings including Ultra-Fast HVAC Models and Optimal DER Control

Smart homes and virtual power plant (VPP) controls are growing fields of research with potential for improved electric power grid operation. A novel testbed for the co-simulation of electric power distribution systems and distributed energy resources (DERs) is employed to evaluate VPP scenarios and propose an optimization procedure. DERs of specific interest include behind-the-meter (BTM) solar photovoltaic (PV) systems as well as heating, ventilation, and air-conditioning (HVAC) systems. The simulation of HVAC systems is enabled by a machine learning procedure that produces ultra-fast models for electric power and indoor temperature of associated buildings that are up to 133 times faster than typical white-box implementations. Hundreds of these models, each with different properties, are randomly populated into a modified IEEE 123-bus test system to represent a typical U.S. community. Advanced VPP controls are developed based on the Consumer Technology Association (CTA) 2045 standard to leverage HVAC systems as generalized energy storage (GES) such that BTM solar PV is better utilized locally and occurrences of distribution system power peaks are reduced, while also maintaining occupant thermal comfort. An optimization is performed to determine the best control settings for targeted peak power and total daily energy increase minimization with example peak load reductions of 25+%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Outage Cause Classification of Power Distribution Systems with Machine Learning and Real-World Data

Power distribution systems are geographically dispersed by nature. It may be affected by various factors, such as vegetation, weather, animal and human behaviors. Present response procedures to an outage event massively rely on expert experience and thus tend to be time-consuming. Automatic outage event detection and classification will help to reduce the responding and restoration time. However, this issue is less addressed with existing research done in this area. In this applied research, a set of waveform pre-processing techniques are first proposed to prepare the waveform data for being used as inputs to the classification algorithm. Further, a machine learning-based algorithm is proposed to classify the outage events according to their root causes, e.g. tree contact, animal contact, lightning, etc. Available data include three phase current & voltage waveforms and contextual information during the distribution system outages. The proposed machine learning algorithm takes the current and voltage waveforms as direct inputs in search of features that humans are unable to capture. Real data provided by a distribution company in the East Tennessee region is used to test the proposed pre-processing techniques and the classification algorithm.

Sun, Haoyuan↗
DOE OSTI2022

Feedback Power Cost Optimization in Power Distribution Networks with Prosumers

Here, we propose a feedback control approach for solving optimal power flow (OPF) problems in power distribution networks (DNs) based on a projected gradient scheme, where the cost is given by the sum of functions of local power injections. This approach does not require detailed knowledge of the grid model and enables real-time tracking of the optimal generation configuration. Moreover, the communication burden is minimal: only a broadcast from a central entity, called the Network Supervisor (NS), to the agents in the network is needed. Hence, agents do not have to share local information that can be sensitive, e.g., their power injections or the value of the local costs. Our approach is then used to solve a particular OPF problem targeting DNs with high penetration of distributed energy resources (DERs) in which the energy cost is given by the remuneration that the DERs owners receive for the service they provide.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

DINGO: Digital assistant to grid operators for resilience management of power distribution system

With increasing adverse weather events and disasters, enabling resiliency of the power distribution system (PDS) is becoming increasingly important. Here in this work, resiliency is defined as the systems ability to keep supplying critical loads even with multiple contingencies. Resiliency may depend on: (a) advanced tools to assist operators in situational awareness and decision making with the increasing volume of data generated by the PDS, (b) visualization and ease of interaction with system resources and information, especially during extreme events and resulting human operator stress, and (c) flexible resources and autonomous control. Operators and support engineers need to interact with the system for key information and take action under stress, given the requirement for decisions in a short time. Integrated technological solutions are prevailing steps to support the most appropriate decision during critical times to serve essential loads. In order to meet the required goals, a Real-time Resiliency Monitoring and Operational Decision Support (RT-RMOD) tool have been developed. It supports various functionalities, including real-time monitoring, resilience assessment, and proactive decision support. However, this work makes advanced feature additions to the tool by developing data-enabled resilience management algorithms for (i) outage detection and localization, (ii) Resiliency-metric driven restoration and reconfiguration, and (iii) NLP based digital assistant for operators called DINGO (DIgital assistaNt to Grid Operators) to interact with Advanced Distribution Management System (ADMS) and RT-RMOD. The developed algorithm was validated for multiple cases of weather events using a real-world, off-grid microgrid system modeled in a real-time simulator, sensor data, and software tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A Risk-Driven Probabilistic Approach to Quantify Resilience in Power Distribution Systems

It is of growing concern to ensure resilience in power distribution systems to extreme weather events. However, there are no clear methodologies or metrics available for resilience assessment that allows system planners to assess the impact of appropriate planning measures and new operational procedures for resilience enhancement. In this paper, we propose a resilience metric using parameters that define system attributes and performance. To represent extreme events (tail probability), the conditional value-at-risk of each of the parameters are combined using Choquet Integral to evaluate the overall resilience. The effectiveness of the proposed resilience metric is studied within the simulation-based framework under extreme weather scenarios with the help of a modified IEEE 123-bus system. With the proposed framework, system operators will have additional flexibility to prioritize one investment over the others to enhance the resilience of the grid.

Poudyal, Abodh↗
DOE OSTI2024

The Position Index of Overhead LED Sources Under Different Spectral Power Distributions and Background Luminances

The position index was developed by Luckiesh and Guth in 1949 and is widely used in discomfort glare models to account for the position of the glare source when predicting the presence and magnitude of visual discomfort. The applicability of this index to modern LED sources has not been evaluated; however, it is of concern due to potentially higher luminance levels of LEDs compared to the sources used by Luckiesh and Guth. Furthermore, the position index of overhead sources beyond 60° above the line of sight has not been quantified. An experiment was conducted using a hemispherical apparatus with LED sources. The position of the light source, background luminance, the spectral power distribution, and anchor (starting luminance level before adjustment) were varied and two procedures were used to determine the position index of these sources. Data from 29 participants indicate that overhead sources located 60° or 80° above the line of sight were detectable and their position index can be quantified. The position index values were found to be higher than those reported in previous studies, suggesting that anchor bias and the small luminance range in previous studies likely influenced their position index values. No differences were found in position index values by spectral power distribution, background luminance, participant age group, or eyeglass wearing. In conclusion, the position index values reported in this study account for range and anchor bias, providing a better estimate that should be incorporated into discomfort glare models.

Discomfort glare↗
DOE OSTI2021

Decentralized Low-Rank State Estimation for Power Distribution Systems

This article considers the low-observability state estimation problem in power distribution networks and develops a decentralized state estimation algorithm leveraging the matrix completion methodology. Matrix completion has been shown to be an effective technique in state estimation that exploits the low dimensionality of the power system measurements to recover missing information. This technique can utilize an approximate (linear) load flow model, or it can be used with no physical models in a network where no information about the topology or line admittance is available. The direct application of matrix completion algorithms requires solving a semi-definite programming (SDP) problem, which becomes computationally challenging for large networks. We therefore develop a decentralized algorithm that capitalizes on the popular proximal alternating direction method of multipliers (proximal ADMM). The method allows us to distribute the computation among different areas of the network, leading to a scalable algorithm. By doing all computations at individual control areas and only communicating with neighboring areas, the algorithm eliminates the need for data to be sent to a central processing unit and thus increases efficiency and contributes to the goal of autonomous control of distribution networks. We illustrate the advantages of the proposed algorithm numerically using standard IEEE test cases.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2022

Adoption Pathways for DC Power Distribution in Buildings

Driven by the proliferation of DC energy sources and DC end-use devices (e.g., photovoltaics, battery storage, solid-state lighting, and consumer electronics), DC power distribution in buildings has recently emerged as a path to improved efficiency, resilience, and cost savings in the transitioning building sector. Despite these important benefits, there are several technological and market barriers impeding the development of DC distribution, which have kept this technology at the demonstration phase. This paper identifies specific end-use cases for which DC distribution in buildings is viable today. We evaluate their technology and market readiness, as well as their efficiency, cost, and resiliency benefits while addressing implementation barriers. The paper starts with a technology review, followed by a comprehensive market assessment, in which we analyze DC distribution field deployments and their end-use characteristics. We also conduct a survey of DC power and building professionals through on-site visits and phone interviews and summarize lessons learned and recommendations. In addition, the paper includes a novel efficiency analysis, in which we quantify energy savings from DC distribution for different end-use categories. Based on our findings, we present specific adoption pathways for DC in buildings that can be implemented today, and for each pathway we identify challenges and offer recommendations for the research and building community.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Multi-Source Data Aggregation and Real-Time Anomaly Classification and Localization in Power Distribution Systems

This paper proposes a real-time anomaly location and classification framework for power distribution systems to simultaneously determine the type of anomaly (i.e., short-circuit fault, cyber attack, DER switching) and its location. The proposed framework employs the data aggregation module to collect the measurement data from multiple field devices operating at different sampling rates, such as protection relays and D-PMUs. The output of the data aggregation is then fed into a multi-task learning-based long-based short-term memory (MTL-LSTM) to classify the type of anomaly and the location in two separate tasks. The proposed MTL-LSTM approach can be utilized in real-time operation in order to distinguish between normal and several anomalous operations and locate the anomaly. The proposed framework is tested on a modified IEEE 33-bus test feeder benchmark that integrates solar generation and energy storage. Furthermore, the results show that the proposed framework can locate and classify anomalies for several operation conditions with more than 96% accuracy. Further experiments highlight the impact of aggregating multiple sources of data on the performance of the proposed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Benefits of high-voltage SiC-based power electronics in medium-voltage power-distribution grids

Medium-voltage (MV) power electronics equipment has been increasingly applied in distribution grids, and high-voltage (HV) silicon carbide (SiC) power semiconductors have attracted considerable attention in recent years. This paper first overviews the development and status of HV SiC power semiconductors. Then, MV power-converter applications in distribution grids are summarized and the benefits of HV SiC in these applications are presented. Microgrids, including conventional and asynchronous microgrids, that can fully demonstrate the benefits of HV SiC power semiconductors are selected to investigate the benefits of HV SiC in detail, including converter-level benefits and system-level benefits. Finally, an asynchronous microgrid power-conditioning system (PCS) prototype using a 10 kV SiC MOSFET is presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗