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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.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Post-Disturbance Dynamic Distribution System Restoration with DGs and Mobile Resources

Distributed generations (DGs) can act as emergency power supplies when distribution systems suffer from outages. However, the generation capabilities of DGs are generally limited by a number of factors including weather conditions, fuel limitations, etc. In this context, mobile resources that are able to reallocate resources to desired locations are regarded as important complements to conventional fixed DGs in assisting distribution system restoration. In this paper, a distribution system restoration model with DGs and mobile resources is proposed. Firstly, the dispatch and allocation of mobile resources are modeled with respect to the characteristics of the traffic network. Then the developed mobile resource models are integrated into the distribution system restoration model to co-optimize the scheduling of DGs and mobile resources. Uncertainty factors are managed by a model predictive control approach so that system operators can dynamically adjust the restoration strategy with the up-to-date information. The effectiveness of the proposed method is validated through an IEEE 13-bus test system.

distributed generations (DGs)↗
DOE OSTI2023

Developing Synthetic Distribution Models Using Open-Source Data Sets

The deployment of distributed generation resources at scale with the distribution side of the power system network over the last two decades has spurred a lot of research interest in distribution networks. Given, the sensitive nature of power system data sets, utilities are still reluctant to open-source distribution networks. Although some open-source data sets are available, they may not cover the region of interest. In this paper, we introduce the Synthetic dIstribution Network Generator (SING), new software that allows users to develop synthetic distribution models, using open-source data sets, in any region of interest within the continental US.

data set↗
DOE OSTI2021

Computational framework for behind-the-meter DER techno-economic modeling and optimization: REopt Lite

The energy system is undergoing a major transformation with the global emphasis on decarbonization. Distributed generation is projected to play a significant role in the new energy system, and energy models are informing how distributed generation can be integrated reliably and economically. In this work, we present an end-to-end computational framework for distributed energy resource (DER) modeling, REopt Lite™, which captures the interface of technology, economics, and policy in the energy modeling process. We describe the problem space, the building blocks of the model, the scaling capabilities of the design, the optimization formulation, and the extensibility of the model. We present a framework for accelerating the techno-economic analysis of behind-the-meter distributed energy resources to enable rapid planning and decision-making, thereby enabling greater renewable energy deployment. This computation framework is open-sourced to facilitate transparency, flexibility, and wider collaboration opportunities within the worldwide energy modeling community.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

DC electric field generation and distribution in magnetized plasmas

Very large DC and AC electric fields cannot be sustained between conducting electrodes because of volume gas breakdown and/or surface field emission. However, very large potential fields are now routinely generated in plasma structures, such as laser generated wake in unmagnetized plasmas. In magnetized plasmas, large DC fields can also be sustained and controlled perpendicular to the magnetic field, but the metallic end plates limiting the plasma, terminating the magnetic field lines, and usually providing the voltage drop feed between the field lines impose severe restrictions on the maximum field. However, it is shown that very large radial DC voltage drops can be sustained by injecting waves of predetermined frequencies and wave vectors, traveling along the azimuthal direction of an axially magnetized plasma cylinder, or by injecting fast neutral particles beams along this azimuthal direction. The large conductivity along the magnetic field lines and the small conductivity between the field lines then distribute this voltage drop. Furthermore, the global power balance and control parameters of wave and beam generated large DC electric fields in magnetized plasmas are identified, described, and analyzed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Distributed Online Voltage Control in Distribution Network: A Two-Stage Real-Time Implementation

The increasing integration of renewable-based distributed generation (DG) brings growing challenges to distribution network (DN) voltage control. To address this issue, a two-stage distributed online voltage control framework (TDO-VC) is proposed in this paper. In the proposed method, legacy voltage control devices are controlled in the upper stage on an hourly timescale, while DGs operate autonomously online in the lower stage to remove instantaneous voltage violations. The idea of receding horizon control is applied in the upper stage to comprehensively consider the current and future renewable generation, and the generalized fast dual ascent (Gf-DA) is employed in the lower stage to effectively manage DGs through near real-time optimization. The effectiveness of the proposed TDO-VC is demonstrated by rigorous theoretical analysis and case studies on IEEE-123 bus system.

Distributed generation↗
DOE OSTI2021

STOCHASTIC OPTIMAL POWER FLOW FOR REAL-TIME MANAGEMENT OF DISTRIBUTED RENEWABLE GENERATION AND DEMAND RESPONSE (Final Report)

To meet the grand challenge of a sustainable energy future, there has been a surge of interest in renewable energy. Today, the uncertainty associated with renewable resources is handled by using operating reserves. The high penetration of renewable resources, however, introduces difficult-to-control dynamics and challenges for power system operation. Decision support tools are necessary at the bulk system operational level to recognize and efficiently utilize renewable resources and distributed demand response products in concert with traditional grid resources. It is envisaged that responsive load can potentially have very significant cost advantages over either spinning or non-spinning ramping reserve. Critical decisions are made during hour(s)-ahead and real-time power system operation regarding the commitment and dispatch of generators to ensure power delivery is both reliable and economic. These decisions are typically made by a security constrained optimal flow, which determines future generator commitments, dispatches, and ensures adequate reserves are available in the event of a contingency (unexpected outage) or if future system conditions deviate from forecasts. However, security has been always based on a pre-specified subset of contingency constraints whose enforcement does not guarantee security under all possible future possibilities while also giving little or no weight to the likelihood of each contingent event or the severity of its consequences. Existing tools, which are based exclusively on deterministic optimization models, do not yield optimal operational decisions to address these new challenges, in terms of both reliability and cost-effectiveness. This project has focused on developing a stochastic optimal power flow (SOPF) framework, which integrates renewable resource uncertainty, load uncertainty, distributed storage (DS), demand response (DR) products, in a holistic manner to address the uncertainty associated with ever-increasing renewable resources, along with the inclusion of distributed demand response products in future power systems. A proof-of-concept problem was created using the Pennsylvania-Jersey-Maryland (PJM) power system network. Synthetic wind generation was added to the system to simulate 50% wind penetration. A 1-hour test of SOPF operation indicated more than 6% operational cost savings. The project continued by adding the Midwestern Independent System Operator (MISO) as a partner, with focus shifting from SOPF to Stochastic Look-Ahead Unit Commitment (SLAC). Unlike PJM, MISO is faced with significant renewable energy resources within its footprint and is challenged with substantial uncertainty in its operations. The SLAC distinguishes itself from existing tools that operators use. At best, today’s tools solve two to three cases independently, where one or two system parameters, such as forecasted load level (e.g., a low, base, and high forecast), are varied and the resulting scenarios are analyzed independently. The stochastic-based optimization of SLAC leverages statistical information from an ensemble of potential operational scenarios and their respective likelihood. The SLAC output can be translated into valuable information to the operator such as suggested commitments, optimal scheduling and dispatch of resources, reserve requirements at both locational and zonal resolutions, ramping availability and requirements, availability of demand response including operational guidance concerning the near-term and real-time coordination between distributed energy resources, and utilization of distributed storage resources. The developed SOPF/SLAC tool, a stand-alone tool compatible with existing EMSs, will provide system operators with unprecedented visibility, flexibility and predictability to these resources and operational guidance concerning the real-time coordination between DERs and DR/DS products. The game changing and practical impact of this disruptive technology will be dramatic and will usher in a new era in the electric power industry, wherein green energy concepts are fully embraced, and electric power costs are lowered throughout the nation.

42 ENGINEERING↗
DOE OSTI2021

Dynamic Building Load Control to Facilitate High Penetration of Solar Photovoltaic Generation (Final Technical Report)

Solar photovoltaic (PV) resources are the most common form of distributed generation in residential and commercial customer premises within electric distribution networks. A higher penetration of PV generation in distribution circuits will impose challenges on maintaining service voltages within the range of industry standards, power quality, and power flow. Buildings consume 74% of the electricity produced in the United States, and a significant portion of the building load is dispatchable, making them responsive to electrical grid needs. Oak Ridge National Laboratory—in collaboration with Southern Company; the University of Tennessee, Knoxville; and the Georgia Institute of Technology—is examining the PV integration issues in distribution-level electrical grids and developing integrated demand-side control and communication systems to enable responsive loads. The proposed responsive loads mechanism performs renewable generation following to increase the penetration of solar PV within each feeder. The specific objectives of this project are to (1) examine distribution-level PV integration scenarios to understand requirements, (2) undertake an end-to-end simulation-based design of a distributed control strategy of loads geographically near the PV generation asset to minimize the effect on the distribution feeder, (3) deploy and demonstrate the control technology developed in partnership with utilities, and (4) perform a scalability analysis at the utility scale. This 3-year integrated project aims to develop, demonstrate, and validate demand-side control technology to enable increased the penetration of renewables while mitigating challenges that arise due to their intermittency. Activities in Budget Period (BP) 1 focused on a literature review and the formal design of a control system for integrating local distribution with generation and loads. The team used modeling and simulation to evaluate the impact of varying buildings loads, variable PV generation, and power flow dynamics on the distribution circuit. The dynamic models developed in BP 1 were used in BP 2 to develop a model-based control design and a test bed. The test bed has enabled the simulation-based testing and comparison of different control designs and formulations applied to different configurations of the distribution grid, PVs, and building loads. The control approaches developed in BP 2 were implemented in BP 3 in the form of hardware deployed at the Central Baptist Church (CBC) in Knoxville, Tennessee, for testing and evaluation. The outcome of this project was the development and demonstration of open-source, low-cost, low-touch sensing and control retrofits to distributed PV generation and building loads that, in a coordinated fashion, provide the load-shaping response needed to integrate high levels of renewable penetration. This research addresses the target metrics by dynamically controlling a load with solar generation variability to minimize the extent of two-way power flow, enhance reliability, facilitate high PV penetration (>100% of peak load in a line segment), and generate scalable software and hardware solutions adaptable to any penetration levels. The research and development activities are focused and designed to be impactful within the relevant 2020 targets time frame.An accurate open-source integration simulation framework for end-to-end control design was developed and deployed at the CBC facility for testing and evaluation. This final report provides a detailed review of the technical results achieved during this 3-year integrated project. A novel spectral analysis of PV data is demonstrated to derive the requirements of the control design. A detailed simulation-based analysis of PV integration at increasing penetration levels is presented using 1 year of PV data to demonstrate the impact on the distribution circuits. Two different control strategies were developed and demonstrated via simulation to track variable PV generation with adaptive load dispatch. The report concludes with a summary of accomplishments and recommendations for a path forward.

14 SOLAR ENERGY↗
DOE OSTI2022

Integrated transient modeling of gas turbine and sCO2 power cycle for exhaust heat recovery application

For distributed generation installations, the transient response of the power generation system is critical to meet power quality (voltage and frequency) requirements. Transient models for gas turbine and supercritical carbon dioxide (sCO2) power cycle were integrated for an exhaust heat recovery bottoming cycle system for a distributed generation application. The transient model for the SGT-750 Siemens gas turbine was a ‘black-box’ functional mockup interface (FMI) model developed by Siemens Industrial Turbomachinery in $Finsp\mathring{a}ng$, Sweden. The SGT-750 is a twin-shaft gas turbine that produces 40 MW electricity with an efficiency of about 40% at ISO conditions. At 100% gas turbine throttle (load), the SGT-750 has average exhaust conditions of 114.6 kg/s and 469.8 °C.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100)

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phaseout of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040 as established in Puerto Rico Energy Public Policy Act (Act 17). To meet these goals and support widespread end-use electrification, Puerto Rico is exploring renewable energy and innovative technologies for energy storage, distributed generation, distribution control, electric vehicles, and energy efficient and responsive loads that can be deployed in each of Puerto Rico's cities and communities. Launched in February 2022, a two-year study entitled Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy (PR100) will perform a comprehensive analysis of stakeholder-driven pathways to Puerto Rico's clean energy future. This fact sheet describes the five activities this robust and objective energy analysis entails.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

The Distribution of U.S. Electric Utility Revenue Decoupling Rate Impacts from 2005 to 2017

Investments in energy efficiency and distributed generation reduce electric utility retail sales. Since electric utilities have historically collected a large portion of revenues from volumetric energy rates (¢/kWh), such reductions in sales can impact the utility’s ability to sufficiently recover non-production costs. Regulatory mechanisms that “decouple” utility revenues from sales were implemented to help make the utility indifferent to energy efficiency and distributed generation by ensuring the utility is able to collect an allowed level of revenue each year regardless of its sales. However, noticeable and consistent surcharges over time may create the perception of an incorrectly designed or implemented decoupling mechanism. To date, there are limited quantitative analyses of the rate adjustments due to decoupling mechanisms implemented among U.S. electric utilities (see Morgan, 2013). Given the recent rapid increase in distributed energy resource (DER) adoption in some states and utility service territories, consumers may be facing more prevalent and ongoing decoupling surcharges. This, in turn, may undermine stakeholder support for implementation of decoupling mechanisms and the associated utility support for energy efficiency and DERs. To determine the size of retail rate adjustments associated with decoupling mechanisms and whether they have a tendency towards bill surcharges or credits, we analyzed a large dataset of historical annual decoupling rate adjustments for 21 electric utilities in 11 states between 2005 and 2017. We found that decoupling mechanisms adjusted rates, both up and down, between rate cases, and the majority of those adjustments (54 percent) are small (within a range of -1 to 1 percent). However, we also found that 64 percent of the rate adjustment observations in our sample showed a positive rate adjustment. Importantly, once a surcharge is applied there is an 86 percent chance that there will be a surcharge in the next year as well. While our analysis did not seek to understand the root causes for such results, some possible factors include the accuracy of revenue requirement forecasts, emerging structural changes in customer use and production of energy, misaligned financial motivation, and other factors that influence sales (e.g., economic recession).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Generating Uncertainty Distributions for Seismic Signal Onset Times

Signal arrival-time estimation plays a critical role in a variety of downstream seismic analyses, including location estimation and source characterization. Any arrival-time errors propagate through subsequent data-processing results. In this article, we detail a general framework for refining estimated seismic signal arrival times along with full estimation of their associated uncertainty. Using the standard short-term average/long-term average threshold algorithm to identify a search window, we demonstrate how to refine the pick estimate through two different approaches. In both cases, new waveform realizations are generated through bootstrap algorithms to produce full a posteriori estimates of uncertainty of onset arrival time of the seismic signal. The onset arrival uncertainty estimates provide additional data-derived information from the signal and have the potential to influence seismic analysis along several fronts.

58 GEOSCIENCES↗
DOE OSTI2022

Neumann Series Based Voltage Sensitivity Analysis for Three Phase Distribution System

In this letter, a simplified voltage sensitivity analysis technique that can provide accurate estimates of voltage change across the network for a given change in bus power injections in a three-phase unbalanced distribution network is proposed. This technique is derived from the first-order approximation of the Neumann series, which allows maintaining the accuracy of the solution while the computational effort is reduced. Here, the proposed technique is tested on a 559-bus unbalanced distribution system with multiple distributed generation resources. The results show that the average error in the voltage estimates with the proposed method is not more than 0.3% with the execution time of similar order relative to the state-of-the-art sensitivity analysis methods.

42 ENGINEERING↗
DOE OSTI2023

Optimizing design and dispatch of a resilient renewable energy microgrid for a South African hospital

Lack of access to reliable energy is a major concern for countries in sub-Saharan Africa. The national grids are unable to consistently satisfy demand. Therefore, users turn to distributed generation systems in the form of back-up generators. However, such systems are usually designed based on a rule of thumb. We employ a mixed-integer linear programming model that considers several options such as renewable energy, combined heat and power, and storage technologies, in addition to those on-site, to provide optimal design and dispatch decisions that minimize total cost. We apply this model to a case study for a hospital in South Africa, considering its need for reliable electricity in light of multiple outages that might occur over the course of a year, as well as its high heating and cooling loads. Our results show that optimal design and dispatch decisions for the distributed generation system address reliability challenges, regardless of the time at which they occur. And, these solutions yield millions of dollars in savings, suggesting that technologies such as the absorption chiller may be overlooked in typical designs; its integration can reduce demand charges even in the absence of combined heat and power. We show that total cost is most sensitive to changes in site electrical demand, followed by capital cost, fuel cost, photovoltaic production, and monthly demand charges; changes in fuel cost primarily affect system sizes of combined heat and power and the absorption chiller, while photovoltaic system size is more sensitive to the changes in capital and fuel costs, photovoltaic resource availability, and hourly electrical demand. Finally, an outage simulator demonstrates the ability of our optimized system to sustain with no interruptions in power five-hour outages with probability 1.0 and ten-hour outages with probability 0.65, significant improvements over 0.5 and 0.0, respectively, under a business-as-usual case.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Techno-Economic Analysis of Distributed Energy Generation in Crow Creek, Alaska

Through the U.S. Department of Energy's Energy to Communities (E2C) program, NLR, other national laboratory experts, and select organizations provide Expert Match - free, short-term technical assistance to address near-term energy challenges and questions. Expert Match is for community stakeholders who have decision-making power or influence in their community but need access to additional energy expertise to inform key upcoming decisions. This Expert Match request supported Crow Creek in Girdwood, AK with a feasibility analysis for a microgrid to provide year-round power across the community.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Exploring the interplay between distributed wind generators and solar photovoltaic systems

This study investigates the spatial and temporal dynamics of wind and solar energy generation across the continental United States, focusing on energy availability, reliability, variability, and cooperation. Using data from the National Renewable Energy Laboratory, we analyze the performance of wind turbines and photovoltaic systems, revealing distinct patterns in energy production and reliability. The classification of wind and solar zones based on energy availability and reliability provides valuable insights for renewable energy planning and grid integration strategies. Overall, this methodology contributes to understanding wind and solar interactions, which will lead to informing effective renewable energy deployment and grid integration efforts.

14 SOLAR ENERGY↗
DOE OSTI2023

Energy I-Corps 2023: Distributed Wind Energy Toolkit

This presentation covers the purpose and scope of an Energy I-Corps project focused on refining a suite of analytical tools designed to support distributed wind deployment. These tools - the Distributed Generation Market Demand (dGen), Distributed Wind Tools Assessing Performance (TAP), and the Hybrid Optimization and Performance Platform (HOPP) - combine to provide users with the ability to simulate consumer purchasing behavior, accurately assess wind resource to better predict turbine performance, and effectively design and optimize hybrid systems that include distributed wind.

deployment↗