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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Data and Multistage Optimization for the New Grid

Three essential capabilities for using exascale computing resources on next generation power grid applications are: generating large renewable energy datasets, modeling damage and operations during and after extreme events, and employing multi-stage optimization for infrastructure planning. Powerscenarios, developed as part of the ExaSGD project, addresses these capabilities by enabling users to build synthetic wind farms for large test systems using numerical weather prediction-based data sources. We share examples of using Powerscenarios to build out wind farms on the ACTIVSg2000 test system, to enable simulated operations and emergency asset allocation during a hurricane strike, and to compute multi-stage infrastructure buildouts.

economic dispatch↗
DOE OSTI2021

Influence of Business Models on PV-Battery Dispatch Decisions and Market Value

PV-battery hybrid projects dominate interconnection queues in some regions in the United States, but few projects have been operational long enough to assess how the hybrid capabilities may be used in practice. We interview plant operators and analyze empirical dispatch data for eleven large-scale PV-battery hybrids in three organized wholesale markets in the United States. We use the dispatch data and wholesale market prices to estimate the market value of our sample hybrids in 2020. The empirical increase in market value of a PV-battery hybrid relative to a standalone PV plant varies by project and ranges from $\$$1 to $\$$48/MWhsolar. The premium is driven by market, location, technical characteristics of the PV and battery asset, and battery dispatch strategies. In contrast to the widespread assumptions in the PV-battery hybrid modeling literature, only three of the eleven project operators optimize battery usage for wholesale market revenue as merchant plants. Instead, the majority of operators in the sample have alternate objectives. For example, load-serving entities target peak load reductions, incentive program participants focus on compliance with program requirements, and large energy consumers prioritize resiliency and utility bill minimization. Understanding prevalent dispatch signals and the degree of alignment with system-wide grid needs can increase the market value of PV-battery hybrids.

14 SOLAR ENERGY↗
DOE OSTI2022

Hierarchical Transactive Control of Flexible Building Loads Under Distribution LMP

With grid modernization efforts, future distribution networks, which consist of various distributed generators and flexible loads, will be more flexible and active. All new network components of distributed energy resources (DERs) drive and enable the transition towards a market-based distribution net-work that seeks the optimal allocation of all DERs. To address challenges associated with DERs, one promising solution is to utilize demand-side flexibility of building loads facilitated by demand response (DR) programs and provide ancillary grid services through distribution-level markets. Under this new paradigm, this paper proposes an efficient DR management strategy incorporating emerging price signals of distribution markets, i.e., distribution locational marginal price (DLMP), based on a hierarchical transactive control approach. The proposed approach establishes a two-layer decision-making framework; the upper layer formulates a bilevel model to obtain an optimal demand response (ODR) under DLMP, and the lower layer employs model-free control to dispatch the (aggregated) ODR to individual end users. Numerical case studies using a modified IEEE 33 test network are performed to verify the effectiveness of the proposed approach; load shifting and peak shaving for the distribution system operator and payments’ reduction for end users while maintaining their comfort.

Park, Byungkwon↗
DOE OSTI2019

VOLTTRON/econ-dispatch

Work space for in development Economic Dispatch Application. Multi-purpose open-source control algorithms that will ensure real-time optimal operation, increase electric grid reliability, and lead to the goal of clean, efficient, reliable and affordable next generation building-integrated combine cooling, heating and power (CHP) system.The CHP system could include conventional heating, ventilation, air conditioning (HVAC) systems, distributed generation (DG), local storage (both thermal and electric) and local solar photovoltaic (PV) systems.

Katipamula, Srinivas↗
DOE OSTI2025

Dispatch Manager for NEML2 Constitutive Model Calculations Embedded in MOOSE

This report describes the extended capabilities of the NEML2 constitutive modeling library, including a flexible and efficient work dispatching system designed to leverage both CPU and GPU resources. This enhancement addresses one of the primary computational challenges in large-scale simulations: the ability to distribute and execute batches of material model evaluations across heterogeneous computing devices. The new dispatch system introduces a modular set of dispatcher and scheduler classes that coordinate the flow of data and execution between devices. The dispatcher is responsible for efficiently packaging work, managing device-specific memory operations, and synchronizing results. This modularity allows for extensibility, making it straightforward to integrate additional computing backends in the future. From an implementation standpoint, the dispatcher system interfaces seamlessly with NEML2's existing models. They handle device-aware tensor operations, optimize memory transfers, and support asynchronous execution when applicable. This design ensures that batches of material points can be evaluated concurrently, substantially improving throughput compared to previous single-device or serial implementations. These improvements not only enhance the raw performance of NEML2 but also improve its usability in multiscale and high-fidelity simulations, where the simultaneous evaluation of large material point batches is critical. Benchmarks included in the report demonstrate the system’s scalability, highlighting its effectiveness when leveraging modern GPU architectures.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Market-Integrated Optimization of Wind-Battery-Hydrogen Hybrids for Peaking Capacity via Storage

As Integrated Energy Systems (IES) combine multiple energy and storage technologies to provide potentially more value and less risk via resource diversification, complementary overbuild, increased flexibility, and revenue-stacking, IES value is dependent on electricity market dispatch and grid interactions should play an important role in IES design and operation. This study hybridizes and retrofits wind and combustion turbine plants to study the impacts of replacing gas generation capacity with wind, battery, PEM electrolysis, hydrogen tanks and hydrogen turbines. The optimized design is co-simulated in a production cost model with different bidding strategies in order to compare performance and highlight the importance of grid-interactions. We analyze the revenue and dispatch changes as well as the price and cost implications of wind-battery-hydrogen IESs.

electrolysis↗
DOE OSTI2023

A Machine Learning Framework to Deconstruct the Primary Drivers for Electricity Market Price Events

As the electricity grid is moving towards a 100% Renewable Energy Source Bulk Power Grid, the overall operations of the power system operations and electricity markets are changing. The electricity markets are not only dispatching resources economically but also taking into account various controllable actions like renewable curtailment, transmission congestion mitigation, and energy storage optimization to make sure the grid is operating reliably. As a result, price formations in electricity markets have become quite complex. Traditional root cause analysis and statistical approaches are rendered inapplicable to analyze and infer the main drivers behind price formation in the modern grid and markets with variable renewable energy (VRE). In this paper, we propose a machine learning analysis framework to deconstruct some primary drivers for price formation in modern electricity markets with high renewable energy and the outcomes can be utilized for various critical aspects of market design, renewable dispatch and curtailment, operations, and cyber-security applications. The framework can be applied to any ISO or market data and in this paper it is applied to open-source publicly available datasets from California Independent System Operator (CAISO) and ISO New England.

machine learning (ML), electricity markets, Renewa↗
DOE OSTI2021

Modeling State Transition and Head-Dependent Efficiency Curve for Pumped Storage Hydro in Look-Ahead Dispatch

As one of the most widely installed utility-scale storage facilities, pumped storage hydro (PSH) plays an essential role in providing flexibility for power systems worldwide. Thus, to accurately quantify the flexibility of PSH units in operational optimization problems is important. The conventional PSH models in the literature rarely consider detailed state transitions due to their hourly-based settings. However, it becomes imperative for operational optimization on short-term intervals, especially with increasing shares of renewable energy in power systems. To this end, this paper presents a novel deterministic PSH model that considers the transition time and trajectory between three states of PSH units in look-ahead dispatch. Moreover, to better characterize the varying efficiency of PSH units with water head and flow rate, this paper proposes to model detailed headdependent efficiency curves (hereafter called input-output curves) in look-ahead dispatch, which encounters heavy computational burdens when short time intervals are applied. In this work, a zig-zag piece-wise linear approximation method is used for input-output curve modeling. This can enable an accurate quantification for variable efficiency and head dependence in a computationally effective manner. Here, numerical results are presented to show performances of the proposed PSH model in both flexibility quantification and computation time.

13 HYDRO ENERGY↗
DOE OSTI2021

Evaluating Utility-Scale PV-Battery Hybrids in an Operational Model for the Bulk Power System

Systems that combine solar photovoltaic and battery energy storage technologies (PV-BES) are increasingly being proposed and deployed on the bulk power system. The operations and value of PV-BES systems have been extensively studied from the project developer's perspective through analyses that maximize plant-level revenue. However, PV-BES hybrids' operational characteristics are seldom studied from the perspective of bulk power system operators, who seek to optimize the performance of a suite of generation and storage assets that are connected via the transmission network. This work presents modeling approaches for representing and evaluating PV-BES hybrids in a model that optimizes operations across the bulk power system. Its novel contributions include demonstrating a technique to modify a unit commitment and dispatch model to represent the operational synergies of PV-BES hybrids. In particular, we describe the challenges and an approach for representing so-called DC-coupled PV-BES - which utilize a single bi-directional inverter - as a dispatchable resource in a commercial, production cost model (PCM), PLEXOS. We demonstrate this technique in a PCM study of the Los Angeles Department of Water and Power (LADWP) test system, by replacing existing PV and battery generators on the test system with our PV-BES hybrids. We then pursue scenario analysis that is designed to isolate the various drivers of operational strategies for DC-coupled PV-BES hybrids, including the nature of coupling, PV penetration on the system, and varying inverter loading ratios (or degrees of over-sizing of the PV field). Results from the analysis include utilization profiles for the PV DC energy across available pathways, dispatch profiles for the battery component, and the hybrid technologies' impacts on system-wide production costs. The approach presented in this paper can be used in any PCM that is looking to study PV-BES hybrids as a resource in different power system configurations and services.

14 SOLAR ENERGY↗
DOE OSTI2022

Robust Scheduling of Networked Microgrids for Economics and Resilience Improvement

The benefits of networked microgrids in terms of economics and resilience are investigated and validated in this work. Considering the stochastic unintentional islanding conditions and conventional forecast errors of both renewable generation and loads, a two-stage adaptive robust optimization is proposed to minimize the total operating cost of networked microgrids in the worst scenario of the modeled uncertainties. By coordinating the dispatch of distributed energy resources (DERs) and responsive demand among networked microgrids, the total operating cost is minimized, which includes the start-up and shut-down cost of distributed generators (DGs), the operation and maintenance (O&M) cost of DGs, the cost of buying/selling power from/to the utility grid, the degradation cost of energy storage systems (ESSs), and the cost associated with load shedding. The proposed optimization is solved with the column and constraint generation (C&CG) algorithm. The results of case studies demonstrate the advantages of networked microgrids over independent microgrids in terms of reducing total operating cost and improving the resilience of power supply.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Real-Time Dispatch With Secondary Frequency Regulation: A Pathway to Consider Intra-Interval Fluctuations

Real-time dispatch balances the power demand with minimized operating costs. For the current dispatch model, the demand is assumed to be constant within a time interval, while the intra-interval power balance is left to frequency regulation. Based on practical experience and simulations, this behavior may lead to insufficient frequency regulation and uneconomic regulation costs considering the increase in intra-interval fluctuations caused by renewables. Here, a real-time dispatch method with secondary frequency regulation behaviors is proposed. Without changing the interval of the real-time dispatch command, the system regulation mileage and intra-interval generation adjustment are explicitly formulated in a mixed-integer optimization model. To reduce the computational burden, an efficient two-stage calculation method is proposed. With practical utility data, this article finds that the proposed method can effectively improve the system frequency performance with the subminute net load forecasting curve obtained by an off-the-shelf forecasting approach. Time-domain simulations in IEEE and practical utility systems validate the effectiveness of the proposed method in terms of the frequency performance and total operating costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Robust hierarchical dispatch for residential distribution network management considering home thermal flexibility and model predictive control

In the transactive energy (TE) paradigm, the devices of participative consumers, or prosumers, may be aggregated and employed to drive operational objectives at the network level. Home heating, ventilation and air-conditioning (HVAC) systems in particular are well-suited to modulate their behaviours based on both home thermal flexibility and requests from the utility grid. This paper develops a robust, hierarchical power dispatch scheme in the context of a residential distribution network. The formulation couples a unique, multiphase linear distribution optimal power flow (OPF) at the upper level with model predictive control (MPC)-based HVAC fleet controllers at the lower level. The proposed approach is tested on nearly 2000 homes with a three-phase distribution network in an intraday market setting, where two major applications are explored and analysed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Multi-Energy Microgrid Planning Considering Heat Flow Dynamics

In this paper, we present a multi-energy microgrid optimal planning method, considering the intra-hour dynamics of the heating system as constraints of the energy dispatch, and consequently of the sizing of the Combined Heat and Power units. The fixed-mass flow rate method and finite difference technique are applied to linearize the dynamic constraints. Moreover, to determine the values of the mass flow rates, a critical scenario representing the slowest heat dynamic process is put forward. Finally, a realistic microgrid case study is presented to illustrate the effect of considering the heat flow dynamics in the overall solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

An Improved Genetic Algorithm approach to the Unit Commitment/Economic Dispatch problem

The deployment of new technologies, the importance of accurately modeling the dynamics of the generating units and the introduction of new policies are making the solution of the Unit Commitment/Economic Dispatch problem more and more complicated.In the present scenario, traditionally followed scheduling criteria might not lead to the optimal fleet configuration any more. In addition, most of the widely used techniques have limited capabilities at modeling the nonlinear dynamics of committed power plants. When realistic power systems comprising of several tens of generating units are modeled, the resulting optimization problem turns to be computationally intensive for the current computing capabilities. In this paper, an improved version of a GA-based optimization algorithm is presented. A detailed methodology aimed at obtaining a more efficient version of the GA, and a more detailed and accurate description of the flexible operation flexibility of the power plants is described.

genetic algorithm↗
DOE OSTI2020

Repair and Resource Scheduling in Unbalanced Distribution Systems Using Neighborhood Search

—This paper proposes an optimization strategy to assist utility operators to recover power distribution systems after large outages. Specifically, a mixed-integer linear programming (MILP) model is developed for co-optimizing crews, resources, and network operations. The MILP model coordinates damage isolation, network reconfiguration, distributed generator re-dispatch, and crew/resource logistics. In addition, a framework for integrating different types of photovoltaic (PV) systems in the restoration process is developed. We consider two different types of crews, namely, line crews for damage repair and tree crews for obstacle removal. We also model the repair resource logistic constraints. Furthermore, a new algorithm is developed for solving the distribution system repair and restoration problem (DSRRP). The algorithm starts by solving DSRRP using an assignmentbased method, then a neighborhood search method is designed to iteratively improve the solution. The proposed method is validated on modified IEEE 123- and 8500-bus distribution test systems.

Outage management↗
DOE OSTI2021

Economic Dispatch Model of Nuclear High-Temperature Reactor with Hydrogen Cogeneration in Electricity Market

Hydrogen produced without carbon emissions could be a useful fuel as nations look to decarbonize their electricity, transport, and industry sectors. Using the iodine–sulfur (IS) cycle coupled with a nuclear heat source is one method for producing hydrogen without the use of fossil fuels. An economic dispatch model was developed for a nuclear-driven IS system to determine hydrogen sale prices that would make such a system profitable. The system studied is the HTTR-GT/H2, a design for power and hydrogen cogeneration at the Japan Atomic Energy Agency’s High Temperature Engineering Test Reactor. This study focuses on the development of the economic model and the role that input data plays in the final calculated values. Using a historical price duration curve shows that the levelized cost of hydrogen (LCOH) or breakeven sale price of hydrogen would need to be 98.1 JPY/m3 or greater. Synthetic time histories were also used and found the LCOH to be 67.5 JPY/m3. The price duration input was found to have a significant effect on the LCOH. As such, great care should be used in these economic dispatch analyses to select reasonable input assumptions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Coordinated Modeling of Electric Grid and Natural Gas Network Operations

Presentation based upon full report of a Colorado case study and coordination framework, which is available at https://www.nrel.gov/docs/fy20osti/77096.pdf. JISEA analysts Brian Sergi, Omar Guerra, and Bri-Mathias Hodge will present on recent JISEA work on coordination between the natural gas and electricity sectors. Power and gas are becoming increasingly interdependent but weren't designed to function together. How does greater coordination impact system operations with different levels of solar and wind penetrations? This free JISEA presentation will take place in a Webinar on Tuesday, May 11, 2021 at 12 p.m.: Learn how greater coordination between the natural gas and electricity sectors impacts system operations with different levels of solar and wind penetrations. Presentation information includes: Historical and projected data for natural gas consumption and power generation in the United States as demonstrated by 2014 East Coast Polar Vortex, 2021 Texas Winter Storm Uri. Showing coupling points, FERC identified need for better coordination, different levels of coordination (decision making and optimization control), coordination framework. Case study on Colorado Front Range, ramping requirements and gas nominations, real-time dispatch (June and December scenarios), results of analysis of impacts of coordination on unserved load. Total real-time gas offtakes by node, impacts on unserved gas, effect on CO2 emissions. Discussions on clusions drawn from Colorado Case study expanded co-simulation via HELICS, objectives of the HELICS+ natural gas use case, modeling of hydrogen blending, techno economic assessment of blending, and blending impacts on energy content and pressure.

analysis↗
DOE OSTI2023

Evolution of Scenario Generation Capabilities in the ExaSGD Project

High-fidelity renewable energy scenarios and rare-event high-impact contingencies are essential for modeling operations and infrastructure expansion of the next generation power grids using exascale computing resources. As the ExaSGD project progressed, our capabilities for generating scenarios for modeling wind power output at multiple wind farms significantly improved, evolving from the use of independent random perturbations to importance sampling-based techniques capturing representative spatial-temporal relations. Contingency generation also improved, evolving from standard N-1 techniques to probabilistic models of infrastructure damage resulting from extreme weather events. We review the developments in the realistic intermittent-energy scenario forecasting and extreme-event contingency creation as the ExaSGD project progressed and discuss the future work in these areas.

economic dispatch↗