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DOE OSTI2022

Addressing Market Issues in Electrical Power Systems with Large Shares of Variable Renewable Energy

This paper reports recent findings from IEA Wind TCP Task 25, which compiles international experiences and research related to large-scale integration of wind and other renewable energy. In the paper, we address the main challenges for market integration of variable renewable energy, relating to price formation, cost recovery, balancing and other grid services. The paper gives an overview of recent scenario studies on electricity price impacts of (1) various generation, energy storage and demand types in different markets, and (2) different market designs and energy/climate policies. Studying markets with very high shares of variable renewable energy requires an improved set of analysis tools for forecasting market outcomes, estimating flexibility needs and sources, and assessing resource adequacy. Key market features need to be investigated within these improved analytical capabilities for systems transitioning to high shares of variable renewable energy, storage and flexible demand. System services that can be supported by markets will likely need to be revisited. Finally, this paper identifies open questions and suggested future market design work for supporting systems with very high shares of variable renewable energy, which are to be addressed in follow-up work of Task 25 collaborative research.

cost recovery↗

NASA NTRS1973

Technical consulting services for earth resources program

Evaluations of several sets of test data which show a normal amount of variability in gamma and Dmax on KODAK Aerial Duplicating Film (ESTAR Base) SO-467 are reported. Kodak is now furnishing to engineers at GSFC a full set of test data for each coating of SO-467 film. Glass-enclosed sensitometer step tablets which are being made for the Herrnfeld instrument at GSFC are discussed. These tablets include a gray scale and uniformity check areas as well as tribar resolution patterns imaged in a durable chromium layer. It is recommended that the Sioux Falls EDC procure four new enlarging printers and study the value and economics of a system for printer automation based on edge coding.

Source record↗

NASA NTRS2005

Analysis of Multiple Precipitation Products and Preliminary Assessment of Their Impact on Global Land Data Assimilation System (GLDAS) Land Surface States

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. NASA's Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type). Precipitation is arguably the most important input to LSMs. Many precipitation datasets have been produced using satellite and rain gauge observations and weather forecast models. In this study, seven different global precipitation datasets were evaluated over the United States, where dense rain gauge networks contribute to reliable precipitation maps. We then used the seven datasets as inputs to GLDAS simulations, so that we could diagnose their impacts on output stocks and fluxes of water. In terms of totals, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) had the closest agreement with the US rain gauge dataset for all seasons except winter. The CMAP precipitation was also the most closely correlated in time with the rain gauge data during spring, fall, and winter, while the satellitebased estimates performed best in summer. The GLDAS simulations revealed that modeled soil moisture is highly sensitive to precipitation, with differences in spring and summer as large as 45% depending on the choice of precipitation input.

Gottschalck, Jon↗

NASA NTRS2005

Evaluation of Ten Methods for Initializing a Land Surface Model

Rodell, M.↗

DOE OSTI2022

Cyber-Physical Dynamic System (CPDS) Modeling for Frequency Regulation and AGC Services of Distributed Energy Resources

The substantial integration of renewable energy brings significant challenges to balance the system in real time because of the variability and intermittency of renewable power. For the reliable system operation, the frequency regulation service is used to stabilize the system frequency through automatically balancing the system generation and load. On one hand, with the substantially increasing deployment of renewable energy in electricity system, the requirement of frequency regulation (FR) services increases significantly. On the other hand, the current main resource of FR services, the controllable conventional generation, is continuously decreasing in the system generation mix. This means that in the future high renewable penetration power system, additional and alternative reliable FR services providers such as distributed energy storage (DES) resources should be explored. Although the capability of utility-scale energy storage to provide FR services has been demonstrated, the integrated control and dynamic modeling of distributed energy resource (DER) providing frequency regulation grid services has been rarely explored. There are several challenges to adopt DERs to provide reliable grid services as illustrated in FERC 755. First, the distributed installation of DES requires a comprehensive cyber-physical dynamic system (CPDS) modeling to fully consider the impacts of the communication latency variability on its real time FR provision capability. Unlike the conventional generators, there are two-layer communication between DERs and system operators which increase the communication delay. Second, unlike the conventional generators whose dynamic models have been comprehensively studied, the difference among individual DER components' power-dynamic characteristic brings challenges in the accurate dynamic AGC modeling of its power-frequency relationship. Third, the temporal dependent state of charge uncertainty of DERs challenges DERs' power and frequency regulation capacities scheduling in the look-ahead generation scheduling. Therefore, the aggregator should optimize the frequency regulation provision from individual DER in real time. To overcome these challenges, this project proposes a cyber-physical dynamic system (CPDS) model to handle the uncertainty of DERs two-layer communication latency and power dynamics. The variability of DERs' communication delay and dynamic constraints will be comprehensively modeled. The DERs' AGC model with communication delay is designed to validate DESs' frequency regulation services. Like current performance-based frequency regulation evaluation, the delivery of DERs' frequency regulation will be assessed through post-analysis of the actual AGC response with respect to the AGC control signal from system operators. Consequently, the reliability improvement with DERs providing reliable frequency regulation services can be evaluated from a comprehensive perspective considering all the dynamics of communication and power.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2013

Demand Response for Ancillary Services

Many demand response resources are technically capable of providing ancillary services. In some cases, they can provide superior response to generators, as the curtailment of load is typically much faster than ramping thermal and hydropower plants. Analysis and quantification of demand response resources providing ancillary services is necessary to understand the resources economic value and impact on the power system. Methodologies used to study grid integration of variable generation can be adapted to the study of demand response. In the present work, we describe and illustrate a methodology to construct detailed temporal and spatial representations of the demand response resource and to examine how to incorporate those resources into power system models. In addition, the paper outlines ways to evaluate barriers to implementation. We demonstrate how the combination of these three analyses can be used to translate the technical potential for demand response providing ancillary services into a realizable potential.

Demand Response - Ancillary Services - Industrial ↗

NASA NTRS1989

Focus of attention in an activity-based scheduler

Earlier research in job shop scheduling has demonstrated the advantages of opportunistically combining order-based and resource-based scheduling techniques. An even more flexible approach is investigated where each activity is considered a decision point by itself. Heuristics to opportunistically select the next decision point on which to focus attention (i.e., variable ordering heuristics) and the next decision to be tried at this point (i.e., value ordering heuristics) are described that probabilistically account for both activity precedence and resource requirement interactions. Preliminary experimental results indicate that the variable ordering heuristic greatly increases search efficiency. While least constraining value ordering heuristics have been advocated in the literature, the experimental results suggest that other value ordering heuristics combined with our variable-ordering heuristic can produce much better schedules without significantly increasing search.

Sadeh, Norman↗

DOE OSTI2014

Demand Response Resources for Energy and Ancillary Services (Presentation)

Demand response (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind an solar power generation. However, DR in grid models is limited by data availability and modeling complexity. This presentation focuses on the co-optimization of DR resources to provide energy and ancillary services in a production cost model of the Colorado test system. We assume each DR resource can provide energy services by either shedding load or shifting its use between different times, as well as operating

14 SOLAR ENERGY↗

DOE OSTI2019

Power Law Growth and Delayed Feedbacks in Socio-Hydrological Systems

Water infrastructure dynamics result from coupled social and physical hydrological processes embedded in “socio-hydrological systems” (SHSs). Freshwater fuels socioeconomic activity, which in turn exerts pressure on water resources through increased water demand and water quality degradation. Many factors emphasize the need for quantitative tools to predict the future of these systems, including SHS failures due to growing water scarcity from population growth and climate change. However, unfolding the interactions between social and hydrological factors continues to resist theoretical treatment, impeding progress toward a predictive framework. To resolve this issue, we propose and evaluate time delays as surrogates for the social dynamics in SHS models. This approach permits the development of models that describe SHS dynamics in terms of observable, physical, hydrological state variables. We apply this approach to two case studies: (a) reservoir storage capacity growth in the world and the U.S. Water Resources Regions and (b) global water withdrawals. Substantial variability was identified in empirical estimates of growth rates and time delays. Reservoir construction typically follows a saturating, logistic curve with periodic, punctuated equilibria, separated by delays ranging from 5 to 20 years both globally and regionally. In contrast, global water withdrawal data display faster-than-exponential growth, characteristic of a positive feedback through which water use drives further water development. Historical analysis suggests that growth trends in water resources systems are superimposed by recurring periods of innovation and inactivity which are indicative of slow memory dissipation and delayed effects of past water use on current water infrastructure decisions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

NREL Integrate: RCS-4-42326

OMNETRIC Corp., Duke Energy, CPS Energy, and the University of Texas at San Antonio (UTSA) created a project team to execute the project 'OpenFMB Reference Architecture Demonstration.' The project included development and demonstration of concepts that will enable the electric utility grid to host larger penetrations of renewable resources. The project concept calls for the aggregation of renewable resources and loads into microgrids and the control of these microgrids with an implementation of the OpenFMB Reference Architecture. The production of power from the renewable resources that are appearing on the grid today is very closely linked to the weather. The difficulty of forecasting the weather, which is well understood, leads to difficulty in forecasting the production of renewable resources. The current state of the art in forecasting the power production from renewables (solar PV and wind) are accuracies in the range of 12-25 percent NMAE. In contrast the demand for electricity aggregated to the system level, is easier to predict. The state of the art of demand forecasting done, 24 hours ahead, is about 2-3% MAPE. Forecasting the load to be supplied from conventional resources (demand minus generation from renewable resources) is thus very hard to forecast. This means that even a few hours before the time of consumption, there can be considerable uncertainty over what must be done to balance supply and demand. Adding to the problem of difficulty of forecasting, is the reality of the variability of the actual production of power from renewables. Due to the variability of wind speeds and solar insolation, the actual output of power from renewable resources can vary significantly over a short period of time. Gusts of winds result is variation of power output of wind turbines. The shadows of clouds moving over solar PV arrays result in the variation of power production of the array. This compounds the problem of balancing supply and demand in real time. Establishing a control system that can manage distribution systems with large penetrations of renewable resources is difficult due to two major issues: (1) the lack of standardization and interoperability between the vast array of equipment in operation and on the market, most of which use different and proprietary means of communication and (2) the magnitude of the network and the information it generates and consumes. The objective of this project is to provide the industry with a design concept and tools that will enable the electric power grid to overcome these barriers and support a larger penetration of clean energy from renewable resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Capturing the Impact of Storage and Other Flexible Technologies on Electric System Planning

Power systems of the future are likely to require additional flexibility. This has been well studied from an operational perspective, but has been more difficult to incorporate into capacity expansion models (CEMs) that study investment decisions on the decadal scale. There are two primary reasons for this. First, the necessary input data, including cost and resource projections, for flexibility options like demand response and storage are significantly uncertain. Second, it is computationally difficult to represent both investment and operational decisions in detail, the latter being necessary to properly value system flexibility, in CEMs for realistically sized systems. In this work, we extend a particular CEM, NREL's Resource Planning Model (RPM), to address the latter issue by better representing variable generation impacts on operations, and then adding two flexible technologies to RPM's suite of investment decisions: interruptible load and utility-scale storage. This work does not develop full suites of input data for these technologies, but is rather methodological and exploratory in nature. We thus exercise these new investment decisions in the context of exploring price points and value streams needed for significant deployment in the Western Interconnection by 2030. Our study of interruptible load finds significant variation by location, year, and overall system conditions. Some locations find no system need for interruptible load even with low costs, while others build the most expensive resources offered. System needs can include planning reserve capacity needs to ensure resource adequacy, but there are also particular cases in which spinning reserve requirements drive deployment. Utility-scale storage is found to require deep cost reductions to achieve wide deployment and is found to be more valuable in some locations with greater renewable deployment. Differences between more solar- and wind-reliant regions are also found: Storage technologies with lower energy capacities are deployed to support solar deployment, and higher energy capacity technologies support wind. Finally, we identify potential future research and areas of improvement to build on this initial analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Universal Compiling and (No-)Free-Lunch Theorems for Continuous-Variable Quantum Learning

Quantum compiling, where a parameterized quantum circuit is trained to learn a target unitary, is an important primitive for quantum computing that can be used as a subroutine to obtain optimal circuits or as a tomographic tool to study the dynamics of an experimental system. While much attention has been paid to quantum compiling on discrete-variable hardware, less has been paid to compiling in the continuous-variable paradigm. Here we motivate several, closely related, short-depth continuous-variable algorithms for quantum compilation. We analyze the trainability of our proposed cost functions and numerically demonstrate our algorithms by learning arbitrary Gaussian operations and Kerr nonlinearities. We further make connections between this framework and quantum learning theory in the continuous-variable setting by deriving no-free-lunch theorems. These generalization bounds demonstrate a linear resource reduction for learning Gaussian unitaries using entangled coherent-Fock states and an exponential resource reduction for learning arbitrary unitaries using two-mode-squeezed states.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Budget Period 2 Summary Report Part 3: Hywind Maine Project

This project was performed under the Work for Others—Funds in Agreement FIA-14-1793 between Statoil and the Alliance for Sustainable Energy, manager and operator of the National Renewable Energy Laboratory (NREL). To support the development of a 6-MW spar-mounted offshore wind turbine, NREL performed tasks on behalf of Statoil in the following three categories: 1. Design and analysis 2. Wake modeling 3. Concept resource assessment. This document summarizes the work performed in Work Package (WP) 3, where the spatial variability and influence that relevant parameters have on levelized cost of energy (LCOE) were analyzed. The study allows Statoil to identify areas of interest for floating wind technology and the Hywind concept in particular. This report describes the results of a study that NREL conducted to provide targeted insight into the United States (U.S.) offshore wind resource area that Statoil can use for taking strategic decisions about how to commercialize and market the company’s Hywind technology. The report centers on a new spatio-economic methodology that NREL has developed to assess how variability in spatial parameters can influence levelized cost of energy (LCOE) for different technologies. The method combines wind plant performance modeling, economic modeling, and national geospatial data layers to estimate the cost of potential projects using Hywind technology, considering the following parameters: • Water depth • Possible inshore assembly areas • Wind resource • Existing grid features and potential connection points • Wave regime • Environmentally sensitive areas • Seabed conditions • Competitive use areas • Prospective staging ports The scope of the study covers the major offshore regions within the contiguous United States, including the Atlantic Ocean, Gulf of Mexico, Pacific Ocean, and the Great Lakes. The spatio-economic assessment extends to 92 km (50 nm) off of the nearest land mass, consistent with the available data on wind characteristics. The study is restricted to those locations that meet the depth criteria for Hywind technology—defined as water depths between 100 m to 1,000 m—and only considered sites with net capacity factors that exceed 30%.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1975

Advances in automatic extraction of earth resources information from multispectral scanner data

The basis of spectral discrimination was briefly examined indicating sources of variability which tend to obscure the spectral attributes of the classes of interest. Spatial and temporal discrimination bases are also discussed. Automatic processing functions, techniques and methods, and equipment are discussed with emphasis on techniques and equipment required for operational large area surveys with satellite data. Techniques for carrying out major functions of preprocessing for signature extension, feature extraction, discrimination, display, and applications modeling were examined. A multiplicative and additive signature correction technique and a proportion estimation technique are discussed. The development of the multivariate interactive digital analysis system multispectral processor system which represents a breakthrough in cost effective high throughput processing for large area surveys from satellites and aircraft is reviewed. Applications and results are discussed briefly for agricultural crop inventories, environmental monitoring, and resources surveys from ERIM LANDSAT and EREP investigations to indicate the substantial progress achieved to date.

Erickson, J. D.↗

DOE OSTI2016

Stochastic population dynamics under resource constraints

This paper investigates the population growth of a certain species in which every generation reproduces thrice over a period of predefined time, under certain constraints of resources needed for survival of population. We study the survival period of a species by randomizing the reproduction probabilities within a window at same predefined ages and the resources are being produced by the working force of the population at a variable rate. This randomness in the reproduction rate makes the population growth stochastic in nature and one cannot predict the exact form of evolution. Hence we study the growth by running simulations for such a population and taking an ensemble averaged over 500 to 5000 such simulations as per the need. While the population reproduces in a stochastic manner, we have implemented a constraint on the amount of resources available for the population. This is important to make the simulations more realistic. The rate of resource production then is tuned to find the rate which suits the survival of the species. We also compute the mean life time of the species corresponding to different resource production rate. Study for these outcomes in the parameter space defined by the reproduction probabilities and rate of resource production is carried out.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2017

The Future of Evapotranspiration: Global Requirements for Ecosystem Functioning, Carbon and Climate Feedbacks, Agricultural Management, and Water Resources

The fate of the terrestrial biosphere is highly uncertain given recent and projected changes in climate. This is especially acute for impacts associated with changes in drought frequency and intensity on the distribution and timing of water availability. The development of effective adaptation strategies for these emerging threats to food and water security are compromised by limitations in our understanding of how natural and managed ecosystems are responding to changing hydrological and climatological regimes. This information gap is exacerbated by insufficient monitoring capabilities from local to global scales. Here, we describe how evapotranspiration (ET) represents the key variable in linking ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources, and highlight both the outstanding science and applications questions and the actions, especially from a space-based perspective, necessary to advance them.

Fisher, Joshua B.↗

DOE OSTI2026

Financial-technical co-design for capital-intensive, resource-responsive energy systems

Because of their capital-intensive operation, wind energy systems that are competitive in terms of the cost of the energy that they produce lead to risk-reward trade-offs that make their business cases less favorable than those of conventional energy generation technologies. However, wind energy systems tend to be designed to maximize energy production or minimize cost of energy rather than to maximize their business cases. In this work, we attempt to exploit designs specifically tailored to business cases. We develop a novel framework for analyzing energy systems that ties their design variables to monthly operating incomes using simple models and historical hourly market and resource data. Using this approach, we demonstrate that for a wind site with abundant wind resource in the California Independent System Operator market, we can control the trade-off between mean and 5th percentile monthly returns by choosing the specific power of the turbine at a fixed modeled initial capital cost. Our framework gives a measure of the risk-reward spectrum of energy generation assets that could be built at a given site with respect to the sub-annual resource/market variation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Wave resource characterization at regional and nearshore scales for the U.S. Alaska coast based on a 32-year high-resolution hindcast

A wave resource characterization was performed for the southern coast of Alaska based on a 32-year hindcast covering the period from 1979 to 2010. The characterization closely followed International Electrotechnical Commission (IEC) Technical Specifications. An unstructured-grid Simulating WAves Nearshore (SWAN) model, which had an approximate spatial resolution of 300 m within 30 km from the nearest shoreline, was developed. Additionally, extensive model validation and error characterization was performed. The model was found to perform well with an average absolute percent error of 8.6% in significant wave height, averaged over 18 buoys. Statistics for the six IEC wave resource parameters were calculated and aggregated at 20 km from shore to quantify the incident wave power and its variability at a regional scale. The southern coast of the Aleutian Archipelago was found to have the most available wave energy in the region. A nearshore resource assessment was performed by evaluating resource hotspots located 1 km from shore. More than 900 nearshore stations had an Optimum Hotspot Identifier value of 5 (kW/m) at diverse water depths, thereby positioning Alaska as a promising location for wave energy development.

54 ENVIRONMENTAL SCIENCES↗