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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

VPP Participation Models: What is the Objective?

Virtual power plants (VPPs) can provide grid services by aggregating and controlling many distributed energy resources. However, their design, operation, level of participation, and outcomes depend on the regulatory and market environments they operate in, DER owner preferences, grid service value, and technical capabilities (e.g., communications, forecasting, controls, user interfaces). Although VPPs are inherently complex, they could enable high shares of behind-the-meter solar plus storage and reduce the cost of electrifying, e.g., personal vehicles and space heating.

demand response↗
DOE OSTI2022

Dynamic Economic Dispatch Considering Transmission–Distribution Coordination and Automatic Regulation Effect

With the rapid increase of renewable energy sources, the variability and uncertainty in power systems are significantly increased, and the power system operation is facing more and more challenges. In the traditional dynamic economic dispatch (DED) of transmission systems, the frequency and voltage regulation effects are not actively utilized. In addition, the transmission systems and distribution systems are optimized separately; the transmission–distribution coordination effect is not considered. In this article, a new DED is proposed. The optimal scheduling results are obtained by making a balance between operating cost and reliability cost. Both the automatic regulation effect and transmission–distribution coordination effect are explored and exploited in terms of the equivalent reserve, which can reduce the reserve provided by generating units, and can further enhance the security and economics of power system operation. The validity and effectiveness of the proposed model are illustrated by case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
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 OSTI2025

Workshop Report: Rural Electric Cooperative Distributed Energy Resource Business Model Development Workshops

The United States' energy future is being shaped by decades of technology innovation, rapidly changing consumer requirements, and governmental focus on securing reliable, low-cost energy sources. With expanded electrification and increased emphasis on grid reliability coupled with the heightened complexity and risks associated with transmission infrastructure, the use of distributed energy resources (DERs) is more commonly being considered a safe, efficient, and cost-effective way to maintain grid resilience and reliability. Amidst improvements in performance, decreasing costs, and unprecedented federal policy support for DERs, electric cooperatives are considering new opportunities to use these assets to ensure secure and reliable operations for millions of customers. In light of these developments, a series of workshops were held to collaborate on the development of business models for DERs in rural electric cooperative ecosystems. The first workshop was held July 11, 2024, at the Tri-State Generation and Transmission Association Inc. headquarters in Westminster, Colorado (hereafter referred to as the "Tri-State Workshop"). The second workshop was hosted by PNGC Power on Oct. 9, 2024, in Portland, Oregon (hereafter referred to as the "PNGC Power Workshop"). These workshops convened representatives from G&Ts, distribution cooperatives,2 the energy industry, the financial community, the U.S. government, national and regional organizations, and national laboratories to share perspectives on the unique needs, challenges, and opportunities that they face as DERs are further integrated into the grid. The workshops were designed to address the following objectives: (1) develop the enabling attributes of electric cooperative DER business models, (2) explore pathways for generating community benefits from these assets, and (3) identify technical challenges and market risks for DERs in rural electric cooperative service territories. This report outlines key findings and major themes identified by workshop participants that federal agencies, G&Ts, distribution cooperatives, and other entities can consider to advance electric cooperative DER business models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Enabling Evaluation of a Southern Company Distribution Feeder on NREL ADMS Test Bed: Cooperative Research and Development (Final Report)

The objective of this project is to enable evaluation of a Southern Company distribution feeder on the Advanced Distribution Management System (ADMS) test bed. The long-term goal is to evaluate a federated distributed energy resource (DER) management solution that aggregates DERs through either direct control, transactive control or an aggregator to provide bulk services while observing distribution system voltage and power constraints. The DER aggregation needs to be coordinated with an ADMS that is responsible for reliable power delivery across the distribution systems. This project takes the first step towards enabling such evaluation by deploying an ADMS from Oracle (Southern Company's ADMS supplier) with a Southern Company feeder at NREL.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2022

Case Study: Resilience Benefits of Distributed Wind Against Fuel and Weather Hazards in Alaska

In this case study of St. Mary’s Village, Alaska, we present a resilience evaluation exercise. A resilience framework is employed to identify system characteristics, relevant metrics, and resilience hazards and to assess the performance against the hazards with and without a distributed wind system installed. The results show the resilience benefits provided by the distributed wind installation against fuel shortage hazards and cold weather hazards. The resilience benefits can be assigned monetary values, which will be highly dependent on actual circumstances of the hazard, but provide insight into value streams of distributed wind that are not usually considered. For example, the single 900 kW turbine was found to prevent an average of 14,643 kWh of load from being dropped during a two-day diesel fuel shortage event, which saved the community $447,592 from the prevented outages. This case study serves as an example for novel power system resilience analysis and builds understanding of resilience hazards that are common across many power systems.

Culler, Megan J.↗
DOE OSTI2024

Power Sharing-Based Framework for Allocating Automatic Generation Control in Distributed Energy Resources: Preprint

The recent proliferation of distributed energy resources (DERs) in the power network along with the retirement of conventional generators has made it challenging to regulate system frequency. In this paper, we present a centralized control framework to leverage the potential of DERs in the distribution network in provisioning secondary frequency control services to the grid. The proposed framework is based on network volt-watt sensitivity analysis and takes into account DER operational and network-imposed constraints to allocate the automatic generation control (AGC) request among the aggregated units. The proposed framework was implemented on the IEEE 8500-node test feeder and results were validated against a standard linear programming-based scheme. Numerical results indicate that the proposed framework can successfully utilize the available power production headroom of the network to meet the AGC request while maintaining nodal voltages within acceptable limits.

distributed energy resources↗
DOE OSTI2023

Outage Forecast-Based Preventative Scheduling Model for Distribution System Resilience Enhancement

Distribution system resilience enhancement is an important topic to ensure customers have access to power supply during extreme events. In fact, certain weather-related extreme events can be predicted ahead of time. Therefore, it is important to investigate how to predict grid outages using extreme weather forecasts, and how outage predictions can be incorporated into distribution system resilience enhancement. In this paper, a preventative scheduling model for distribution systems is proposed. The model targets at allocating resources, especially mobile responsive resources such as mobile backup generators and mobile energy storage systems, to prepare for an extreme event in the day-ahead context. To achieve efficient resource allocation and scheduling, a machine learning-based outage prediction module is developed to predict vulnerable or risky segments of the distribution system based on historical operating records and extreme weather event forecast. By integrating the outage prediction results into the scheduling model, optimal resource allocation can be derived to help distribution systems prepare for an upcoming event and improve resilience performance. A real distribution feeder in North Carolina, U.S. is used in the case study to validate the proposed approach.

distributed energy resources↗
DOE OSTI2020

Optimal D-FACTS Placement in Moving Target Defense Against False Data Injection Attacks

Moving target defense (MTD) is a defense strategy to detect stealthy false data injection (FDI) attacks against the power system state estimation using distributed flexible AC transmission system (D-FACTS) devices. However, existing studies neglect to address a fundamental yet critical issue, i.e., the D-FACTS placement, by assuming that all lines are equipped with D-FACTS devices. Here, to tackle this problem, we first derive analytical necessary conditions and requirements on the D-FACTS placement for a complete MTD. Further, we propose sufficient conditions using a graph theory-based topology analysis to ensure that the MTD under the proposed D-FACTS placement has the maximum rank of its composite matrix, which is indicative of the MTD effectiveness. Based on the analytical conditions, we design D-FACTS placement algorithms by using the minimum number of D-FACTS devices to achieve the maximum MTD effectiveness. A novel MTD-based ACOPF model, in which the reactance of D-FACTS lines is introduced as decision variables, is proposed to find a trade-off between the system loss and the MTD effectiveness. Numerical results on 6-bus, IEEE 14-bus, and IEEE 118-bus systems show the efficacy of MTDs using the proposed D-FACTS placement algorithms in maximizing the composite matrix rank and detecting FDI attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Transmission-distribution long-term volt-var planning considering reactive power support capability of distributed PV

High penetration of grid-edge, inverter-based photovoltaic (PV) can cause significant voltage fluctuations not only at the distribution but also at the sub-transmission levels due to PV output intermittency. Traditional reactive power planning approaches do not consider intermittency, nor the possibility of coordinating the control of existing and future volt-ampere reactive resources. This paper proposes a reactive power planning tool for sub-transmission systems to mitigate voltage violations and fluctuations caused by high PV penetration and intermittency with a minimum investment cost. The planning tool coordinates with an optimization-based volt-var operational tool for: a) modeling the coordination of all existing var assets in both sub-transmission and distribution systems to reduce the need of new equipment, and b)selecting a set of scenarios with voltage violations, derived from PV intermittency c) testing the final investment decision. The tool obtains an investment need for each intermittency scenario with a proposed optimal power-flow framework with efficient techniques to handle a high number of discrete variables. Two options are provided for final planning decision: i) a conservative direct combination of investment need solutions and ii) a machine learning-based selection of representative investment needs at most time steps. The final investment decision options are verified using a realistic large-scale sub-transmission system and 5-minute PV and load data. The results show a significant voltage performance improvement with a lower investment cost for additional var equipment compared to conventional approaches.

14 SOLAR ENERGY↗