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DOE OSTI2021

Preparing Distribution Utilities for the Future - Unlocking Demand-Side Management Potential: A Novel Analytical Framework

The balance of supply and demand in the power systems has traditionally been served solely through generation and network capacity planning and operations. However, with increased requirements for flexibility due to the uptake in variable renewable generation sources such as wind and solar there is a need to increased demand-side flexibility. In addition, there are increased communications and flexibility capabilities emerging on the demand-side from the adoption of advanced metering infrastructures and smart meter deployment and intelligent loads such as smart thermostats and schedulable white goods (e.g. dishwashers and washing machines). Unlocking demand-side flexibility can bring system benefits from peak load reduction bringing about generation capacity and network upgrade deferral, to reducing demand and more efficient utilization of generation and network capacity. Unlocking demand-side flexibility is an evolving process for utilities and solutions must be tailored to each specific customer group. Demand-side management (DSM) is a broad set of tools that can include demand response (both dispatchable and non-dispatchable), energy efficiency and distributed energy resources and demand-side technologies. The National Renewable Energy Laboratory (NREL), in collaboration with BSES Rajdhani Power Ltd. (BRPL) and Deloitte, examined the potential of DSM in BRPL’s service territory, developing detailed information on customer classes and willingness to participate in DSM. The study developed modeling frameworks for load analysis and the analysis tools to assess the potential of time-of-use tariffs in motivating customers to reduce their peak period energy consumption. The study shows that BRPL customers, specifically their domestic customers, are willing to participate in DSM programs and that time-of-use pricing can help BRPL reduce their peak demand and help unlock demand-side flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

CondiDiag1.0: a flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)

Abstract. Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes (i.e., phenomena) such as the resolved and unresolved fluid dynamics, radiative transfer, cloud and aerosol life cycles, and mass or energy exchanges with the Earth's surface. In order to identify model deficiencies and improve predictive skills, it is important to obtain process-level understanding of the interactions between different processes. Conditional sampling and budget analysis are powerful tools for process-oriented model evaluation, but they often require tedious ad hoc coding and large amounts of instantaneous model output, resulting in inefficient use of human and computing resources. This paper presents an online diagnostic tool that addresses this challenge by monitoring model variables in a generic manner as they evolve within the time integration cycle. The tool is convenient to use. It allows users to select sampling conditions and specify monitored variables at run time. Both the evolving values of the model variables and their increments caused by different atmospheric processes can be monitored and archived. Online calculation of vertical integrals is also supported. Multiple sampling conditions can be monitored in a single simulation in combination with unconditional sampling. The paper explains in detail the design and implementation of the tool in the Energy Exascale Earth System Model (E3SM) version 1. The usage is demonstrated through three examples: a global budget analysis of dust aerosol mass concentration, a composite analysis of sea salt emission and its dependency on surface wind speed, and a conditionally sampled relative humidity budget. The tool is expected to be easily portable to closely related atmospheric models that use the same or similar data structures and time integration methods.

58 GEOSCIENCES↗

DOE OSTI2022

Review of Wave Energy Converter Power Take-Off Systems, Testing Practices, and Evaluation Metrics: Preprint

While the field of wave energy has been the subject of numerical simulation, scale model testing, and precommercial project testing for decades, wave energy technologies remain in the early stages of development and must continuing proving themselves as a promising modern renewable energy field. One of the difficulties that wave energy systems have been struggling to overcome is the design of highly efficient energy conversion systems that can convert the mechanical power, derived from the oscillation of wave activated bodies, into another useful product. Often the power take-off (PTO) is defined as the single unit responsible for converting mechanical power into another usable form such as electricity, pressurized fluid, compressed air, and others. The PTO, and the entire power conversion chain (PCC), is of great importance as it affects not only how efficient wave power is converted into electricity, but also contributes to the mass, size, structural dynamics, and levelized cost of energy (LCOE) of the wave energy converter (WEC). Unlike wind and solar, there is no industrial standard device, or devices, for wave energy conversion and this diversity is transferred to the PTO system. The majority of current WEC PTO systems incorporate a mechanical or hydraulic drive train, power generator, and an electrical control system. The challenge of WEC PTO designs is designing a mechanical-to-electrical component that can efficiently convert irregular, bi-directional, low frequency and low alternating velocity wave motions. While gross average power levels can be predicted in advance, the variable wave elevation input has to be converted into smooth electrical output and hence usually necessitates some type of energy storage system, such as battery storage, accumulator super capacitors, etc., or other means of compensation such as an array of devices. One of the primary challenges for wave energy converter systems is the fluctuating nature of wave resources, which require WEC components to be designed to handle loads (i.e. torques, forces, and powers) that are many times greater than the average load. This approach requires a much greater PTO capacity than the average power output and indicates a higher cost. In addition, supporting mechanical coupling and or gearing can be added to the PCC to help alleviate the difficulties with transmission and control of fluctuating large loads with low frequencies (indicative of wave forcing) into smaller loads at higher frequencies (optimum for conventional electrical machine design) can quickly increase the complexity of the PCC which could result in a greater number of failure modes and increased maintenance costs. All of the previous points demonstrate how the PTO influences WEC dynamics, reliability, performance and cost which are critical design factors. This paper further explores these topics by providing a review of the state-of-the-art PTO systems currently under development, how these novel PTO systems are tested and derisked prior to precommercial deployment, and the evaluation metrics historically used to differentiate between PTO designs and how they can be improved to support control co-design focused development of wave energy systems.

laboratory testing↗

DOE OSTI2022

Renewable Energy Guidance for Industry

This document is intended to help Better Plants partners navigate the renewable energy market by providing background on renewable technologies and their benefits as well as a wide range of purchasing options available to organizations. This guidance provides helpful information on adopting renewables by highlighting tools and resources for evaluating renewable energy projects. It also provides information on how renewable energy resources are accounted for by Better Plants reporting requirements. A separate supplemental document to this guidance is available that provides more in-depth information about renewable technologies. This guidance document is applicable to Better Plants partners participating at either the program or challenge level. Although the guidance is primarily intended to assist companies participating in Better Plants, the methodologies and information within are applicable to any organization interested in exploring and adopting renewable energy.

09 BIOMASS FUELS↗

DOE OSTI2025

Integration of renewable energy generation and storage systems for emissions reduction in an islanded campus microgrid

Microgrid connected building communities are projected to play an integral part in the clean energy transition. These types of systems, when integrated with distributed energy resources (DERs) such as combined heat and power (CHP), district heating and cooling, renewable generation, and energy storage, can provide clean, reliable power to critical facilities and vulnerable communities. The intermittent nature of renewable generation is a challenge when integrating renewables into any grid system, but particularly in islanded microgrids. The University of Texas at Austin (UT) operates an islanded microgrid powered by a CHP plant, while also utilizing district heating and cooling systems and thermal energy storage (TES). High fidelity operating data was used to develop a validated reduced order model of UT’s integrated campus energy systems to serve as a testbed for use in a case study. Hypothetical renewable energy installations on land owned by UT in west Texas were modeled and integrated into the validated campus models along with battery energy storage (BES). Simulations showed that a combination of renewable energy from wind, and optimally controlled 24-hour thermal and battery storage systems could reduce carbon dioxide emissions on campus by 45.4%. The additional retrofit of burner systems to utilize hydrogen natural gas blends resulted in an overall annual emissions reduction of 54.7%. Carbon capture and storage eliminated the majority of the remaining emissions with increased plant energy expenditure. The presented simulations display the practical limitations of a CHP system complemented by renewable generation and short-term storage in eliminating emissions. Furthermore, results highlight the need for further research and development in long duration storage technologies and hydrogen fueled turbines to increase penetration of renewable energy and reduce emissions.

CHP↗

DOE OSTI2022

A framework for feasibility-level validation of high-resolution wave hindcast models

The value of long-term wave hindcasts for investigating wave climates, wave energy resources, and extreme wave conditions has motivated research developing, calibrating and validating wave hindcast models. Past hindcast model validation studies examined the accuracy in modeling bulk wave parameters of overall sea states without considering the dependency of the model's skill within different sea states. In the present study, a framework for wave hindcast model validation is developed by examining the model accuracy for the most frequently occurring sea states, sea states contributing the most energy to total wave power, sea states associated with hurricane events, and those with the largest model error. Here, validations using bulk wave parameters and frequency-directional spectra at these key sea states and extreme wave conditions based on univariate and bivariate-contour methods provide insights to improve model accuracy, identifying the model's strong and weak points, and pathways for improvement, e.g., modeling wave-current interactions and adjusting wind data. This study adds to a growing body of research demonstrating that a carefully calibrated and verified spectral wave hindcast model can be used to estimate key wave energy parameters over a wide range of wave energy climates, as well as their spatial, temporal, frequency, directional, and probabilistic distributions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Clean Energy Integration in Natural Gas Compressor Station Operations

Integrating renewable energy into oil and gas operations could reduce emissions and maximize higher-value use of produced hydrocarbons. In this study, analysts from the Joint Institute for Strategic Energy Analysis (JISEA) and the National Renewable Energy Laboratory (NREL) evaluated clean power technologies for a natural gas compressor station in Texas, using NREL’s REopt tool. Different configurations of distributed energy resources were evaluated based on the technologies available and the load they can satisfy, available land, and hypothetical carbon pricing. The analysis is part of a collaborative program with industry to understand site-specific energy consumption and prices in the oil and gas supply chain and determine under what conditions clean energy options are economically attractive. This work was sponsored by a consortium including Kinder Morgan, Interstate Natural Gas Association of America Foundation, Extraction Oil & Gas, Baker Hughes, and ConocoPhillips.

03 NATURAL GAS↗

DOE OSTI2021

Cook Inlet Tidal Energy Resource Characterization Effort

Located in the southcentral region of Alaska, Cook Inlet contains one of the greatest tidal resources in the world. A pinch point in the channel increases the water velocity and provides an excellent site for a potential tidal farm. Access to affordable, clean power would provide a cascade of economic benefits to Alaskans, who face some of the highest energy costs and most extreme climates in the U.S. NREL researchers are collaborating with universities and private partners to gain a better understanding of the underwater environment to pave the way for development of an efficient, durable tidal farm. This summer, they will deploy a buoy in Cook Inlet to characterize the site.

50 EE - Wind and Water Power Program - Water (EE-4↗

DOE OSTI2024

Impact of Inverter-Based Resources on Grid Protection: A Review of Negative-Sequence Current Generation

The increasing integration of inverter-based resources (IBRs) in power grids poses challenges to traditional protection systems, primarily due to their different fault current signatures compared to conventional synchronous generators. Unlike synchronous generators whose fault response is dictated by their physical design, IBRs exhibit a wide range of fault characteristics due to manufacturer-specific control algorithms and settings. This dependence on proprietary control schemes makes modeling IBR behavior during faults significantly more complex, especially considering the rapid evolution of inverter technology and the diverse control strategies employed. While much research has focused on the positive-sequence current injections of IBRs during symmetrical faults, the understanding of negative-sequence current generation during non-symmetrical faults remains limited. This report provides an overview of current research on IBRs' negative-sequence current generation during unbalanced faults and its impact on protection schemes based on negative-sequence components. It covers both type III wind turbines and full-size converter-based IBRs. Additionally, this report reviews strategies for grid-forming controlled inverters to generate negative-sequence current during unbalanced faults, in addition to grid-following controlled ones.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Representing the Future Role of Hydropower and Pumped Storage Hydropower (PSH) in Electricity Planning Tools

Existing tools for long-term electric sector planning struggle to represent hydropower's nuanced site-specific technical and operating characteristics, which depend on technical specifications as well as water management practices and regulations. As a result, long-term planning models and tools insufficiently characterize hydropower value and incentives, and they cannot fully represent the role hydropower can play in a future electricity system that could include a high penetration of variable wind and solar generation, battery storage, and other low-carbon technologies. This presentation demonstrates the culmination of a multi-year effort to enhance hydropower representations in electricity planning models at the National Renewable Energy Laboratory (NREL), as part of the U.S. Department of Energy (USDOE) HydroWIRES Initiative. New modeling techniques are demonstrated using the NREL Regional Energy Deployment System (ReEDS), an open-access electric sector capacity expansion model used extensively in a wide range of technology deployment and integration analysis, including the 2016 USDOE Hydropower Vision. ReEDS uses a least-cost optimization approach to understand investment and operation of electricity generation, storage, and transmission technologies under future scenarios of electricity technology innovation, demand, policy, and other sectoral drivers. ReEDS was modified to better represent value and opportunities for both pumped storage hydropower (PSH) and hydropower systems without pumping. We incorporated a new national closed-loop PSH resource and cost assessment to explore new PSH deployment opportunities and added plant-level data to better represent the existing PSH fleet. New upgrade pathways enable opportunities for enhanced hydropower flexibility by adding pumps, upgrading dispatchability, increasing capacity, or increasing energy availability. The model was also modified to better represent the value of long-duration energy storage beyond diurnal time scales, allowing both hydropower and PSH to better balance energy supply and demand variations in high-renewable systems. These new features are demonstrated under reference and high-renewable futures and a range of sensitivity scenarios to understand which hydropower and PSH deployment and upgrade opportunities are the most attractive. These scenarios indicate potential for new closed-loop PSH deployment and for hydropower flexibility improvements to have important impacts on long-term electricity system emissions and economic outcomes. Increasing flexibility of the existing hydropower fleet can reduce the need to invest in new flexible grid technologies and help achieve decarbonization goals. Systems with sufficient energy storage could also be valuable for balancing seasonal differences in renewable energy availability, particularly from solar energy. The methods developed for ReEDS and subsequent scenario results reveal important considerations for future hydropower and grid system planning, and all data and code is freely available in a public code repository for use throughout the hydropower industry.

capacity expansion↗

DOE OSTI2021

Pala Energy Options Analysis (Final Report)

The Pala Energy Options Project scope focused on assessing electric and thermal energy related options for the Pala Band of Mission Indians. Although the assessment also considered options for transportation fuels – including potential for electrification – and other energy uses, initial reviews with PED staff indicated that the most practical and substantial options likely would involve serving current building electric and thermal energy resources and uses. Assessment scope varies by specific options considered; some merited in-depth assessment for immediate action to initiate or advance implementation, while higher level assessments were more appropriate for options that would take longer to implement and would require updated in-depth assessments during project planning and design phases. The primary objectives of the Project were to 1) identify energy resources/loads, 2) assess energy needs and exports, 3) investigate and evaluate supply-side and demand side energy options, and 4) select and prioritize options in an implementation plan.

14 SOLAR ENERGY↗

DOE OSTI2025

Selection of Global Climate Model Data for Downscaling With Generative Machine Learning and Use in the Power Planning for Alignment of Climate and Energy Systems Project

The range of results from climate models and scenarios is important to the understanding of uncertainty in power planning analysis. A U.S. Department of Energy-funded analytic project called Power Planning for Alignment of Climate and Energy Systems is developing data and analytic methods to reflect the effects of climate change on key variables for power system planning, as part of the Grid Modernization Lab Consortium. This project will select and prepare global climate model results for use in power system planning models. A related report (Evaluation of Global Climate Models for Use in Energy Analysis) assesses the performance of various global climate models from the Coupled Model Intercomparison Project Phase 6 data archive for their historical skill with respect to energy system performance and for their future projections under multiple climate change scenarios. Building from that report, we describe the selection of a climate scenario (Shared Socioeconomic Pathway [SSP] 2-4.5) and five climate models: TaiESM1, EC-Earth3-CC, GFDL-CM4, EC-Earth3-Veg, and MPI-ESM1-2-HR. We describe the model selection criteria, which were based on the quality of the match between model results under historical conditions and on the representation of the range of future values for several variables. These results will be downscaled via an open-source generative machine learning method called Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Using a Grid-Forming Inverter to Stabilize a Low-Inertia Power System - Maui Hawaiian Island

As power systems around the world integrate greater amounts of wind and solar photovoltaic power, periods of very high instantaneous power shares of inverters, the primary interfacing technology for these generation sources, are complicating system stability and control. The contemporary, primary mode of inverter operation, grid-following, which explicitly assumes the presence of a local, stable voltage waveform, yields operational inadequacy at high instantaneous power shares potentially leading to instability due to the low-inertia conditions, as well as the correlated reduced voltage forming capacity on the respective system. Parallel connected grid-forming inverters, which directly regulate the local voltage, are a solution that is expected to bolster system stability and mitigate the shortcomings of the grid-following technology. In this paper, grid-following and two types of grid-forming inverter control, the traditional linear droop and the recently introduced nonlinear exponential droop (Droop-e), are simulated on a low-inertia, H = 0.48s, high inverter-based resource scenario, 97%, with a validated electromagentic transient domain model of the Hawaiian island of Maui power system. The benefit of a single grid-forming device over its grid-following counterpart is significant, both in terms frequency deviation and voltage stability. Further, the superiority of the Droop-e and the associated secondary power sharing control over both grid-following and linear droop grid-forming technologies is displayed, with improved nadir and rate of change of frequency over the linear droop control.

droop control↗

DOE OSTI2024

Impact of Glen Canyon Generation Loss

Colorado River Basin hydropower generation has faced challenges due to droughts and ecological and social water requirements. Specifically, Glen Canyon hydropower generation fluctuates substantially with recent extreme weather trends. Further, the western grid evolves with higher wind and solar share, and Glen Canyon hydropower's contribution to grid flexibility services is essential. The Western Area Power Administration (WAPA) markets and schedules electricity production at GCD, and the loss of this power could have significant financial consequences for the WAPA Colorado River Storage Project's (CRSP) Office because it may need to purchase relatively large amounts of energy to serve its firm electrical obligations. In addition, GCD provides grid reliability services for the WAPA Colorado-Missouri (WACM) balancing authority (BA). Both WAPA and DOE's Water & Power Technology Office (WPTO) are interested in researching how these drier hydrological conditions will impact federal electrical energy production, the Western Electricity Coordinating Council (WECC) power grid, and the value of hydropower in the face of lower production. We study multiple hydrologic and power grid scenarios to understand the grid impacts of the loss of Glen Canyon generation. The study uses a production cost model, water resources planning models, water-centric grid models, and various data analytic techniques. The study progress presentation discusses the selection of probable CRSP' hydropower scenarios and power grid scenarios to understand the impacts of Glen Canyon generation, which includes technologies that compensate the Glen Canyon energy and ancillary services contributions, transmission availability, and energy local marginal prices at interested grid locations of WAPA operation.

droughts↗

DOE OSTI2021

Impact of operating reserve rules on electricity prices with high penetrations of renewable energy

In competitive wholesale electricity markets, significant effort is devoted to designing markets that set efficient prices for maintaining supply-demand balance. One factor that can impact prices is administratively-set scarcity pricing, which sets prices to a preset level when the market is not able to meet operating reserve or energy requirements. When energy and operating reserves are co-optimized, assumptions surrounding operating reserve requirements and scarcity pricing can impact system-wide price outcomes for both operating reserves and energy. This study uses production cost modeling of an ERCOT-like system to evaluate the impact of operating reserve eligibility, scarcity pricing, and quantity rules on electricity prices, and therefore also on generator revenues. Results reveal economic and operational benefits with allowing open participation in reserve markets, as this enables greater access to the full set of capable resources at lowest cost. Furthermore, both energy and reserve prices are strongly impacted by reserve scarcity pricing events, which reveals that reserve scarcity pricing assumptions can impact price outcomes even for units not providing reserves. This study highlights the importance of operating reserve scarcity pricing rules because of the strong coupling between energy and reserve prices and because these rules serve as proxies for true price responsive demand.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Capacity Investment under Bayesian Information Updates at Reporting Periods: Model and Application

We consider capacity addition decisions by a new product manufacturer faced with uncertain technology alternatives. The manufacturing capacity addition and technology development occurs in parallel, with preliminary results from a technology project's success providing valuable information to the manufacturer in adding capacity. We solve a stochastic dynamic program with Bayesian updates to obtain the manufacturer's expected profit‐maximizing capacity investment decision. Our model and applications are motivated by the Critical Materials Institute (CMI) (funded by the Department of Energy), which manages research projects focused on mitigating critical material constraints, vital to renewable energy technologies such as direct‐drive wind turbines, electric vehicles, and energy‐efficient lighting. We capture three unique aspects of the problem: first, the learning from project progress depends on task‐based stochastic outcomes and a project's percent‐done. Second, the underlying technology's profitability is based on a model of competition. Third, we evaluate the impact of progress across a portfolio of projects based on a manufacturer's capacity addition. We develop a heuristic that produces results that are close to optimal and can thus be used for large problem sizes. The managerial insights from an application of our model to CMI projects include: (i) technology projects that report the percent‐done of a project earlier increase expected manufacturer profit; (ii) careful choice of “safe bets,” that is, technologies with low profitability but a high probability of success, can increase expected manufacturer profit; (iii) a portfolio of projects can increase profits significantly over separate project evaluation; and (iv) dynamic management of project resources can increase overall profit.

Vedantam, Aditya↗

DOE OSTI2024

A Real-Time Testbed for Smart Inverter Cyber Security Studies

Distributed energy resources (DER) have become a popular solution to modern-day issues surrounding the efficiency and reliability of power generation, as well as climate change concerns. Energy centers are shifting towards incorporating smart inverters with embedded functionalities such as high voltage ride through (HVRT), low voltage ride through (LVRT), active and reactive power compensation. However, the integration of smart inverters leave DER systems highly vulnerable to cybersecurity threats. The distributed network protocol 3 (DNP3) is a common method of communication between grid-tied hardware. Despite its popularity, the level of security leaves all hardware connected to the grid at risk of severe cyber-attacks. Thus, it is important to study any potential cybersecurity threats towards grid-tied smart inverters to mitigate cybersecurity vulnerabilities and refine existing cyber-security protections. This report describes the proposed testbed design to study cybersecurity threats to smart inverters. The testbed utilizes a real-time simulation case in RSCAD that includes a grid-tied wind turbine (WT) topology featuring two back-to-back two-level voltage source converters (BTB,2L-VSCs) and a permanent magnet synchronous machine (PMSM). The simulated case runs within the NovaCor real time digital simulator (RTDS). This report focuses on the design and implementation of a single module of the GTNETx2 card as a distributed network protocol and the configuration of an IEEE 1518 DNP database file that includes input and output variables mapped to different connection points in the grid that transmit and receive discrete, analog, and binary signals on command. This allows realistic emulation of the communication between the smart inverter and the grid for cybersecurity studies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Mortality correlates with tree functional traits across a wood density gradient in the Central Amazon

Introduction: Understanding the mechanisms of tree mortality in tropical ecosystems remains challenging, in part due to the high diversity of tree species and the inherently stochastic nature of mortality. Plant functional traits offer a mechanistic link between plant physiology and performance, yet their ability to predict growth and mortality remains poorly understood. Given recent increases in tree mortality rates in the Amazon forest following extreme drought and wind events, we tested if lower wood density and acquisitive plant functional traits were associated with increased growth and mortality for common co-occurring trees in the Central Amazon. Methods: Seventeen trees of different species with similar sizes but a range in wood density (WD) and wood traits were felled, then assessed for 27 different individual functional parameters, including whole tree architecture, stem xylem anatomical and hydraulic traits and leaf traits. Traits of the individual trees were related to stand-level growth and mortality rates collected periodically over 30 years from nearby permanent inventory plots. Results: Higher wood density was associated with smaller leaf size, lower foliar base cations, lower stem water content and sapwood fraction, in agreement with the fast-slow plant economics spectrum. Lower wood density was associated with more acquisitive characteristics with greater hydraulic capacity and foliar nutrient concentrations, correlating with greater growth and mortality rates. Discussion: Our results show that lower wood density is part of a coordinated suite of traits linked to high resource acquisition, fast growth, and increased mortality risk, providing a functional framework for predicting species performance and forest vulnerability under future climate stress.

demographics↗