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At least 577 records · Page 32

Washington Clean Energy Fund: Energy Storage System Consolidated Performance Test Results

This report provides an overview of test results for four energy storage systems funded under the Washington Clean Energy Fund deployed at three utilities in Washington State. Integration of energy storage into the U.S. grid has been gathering momentum across the industry, especially as penetration of power generated by renewable resources increases. Several states have storage procurement targets to deal with a variety of issues, such as afternoon total system load ramping requirements, frequency regulation/control, and integration power generated from by renewable resources. This report presents the performance test results for battery energy storage systems (BESS) funded by the Washington Clean Energy Fund (CEF) 1 Program ($\$$14.3 million in state funding supporting a total investment of $\$$43 million). For each project, the technical attributes of the BESS were tested, defined, and evaluated in detail. These projects were funded jointly by Avista, the Snohomish Public Utility District (SnoPUD), Puget Sound Energy (PSE), the Washington CEF, and the U.S. Department of Energy Office of Electricity Delivery and Energy Reliability (DOE-OE).

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA's GreenLab Research Facility: A Guide for a Self-Sustainable Renewable Energy Ecosystem

There is a large gap between the production and demand for energy from alternative fuel and alternative renewable energy sources. The sustainability of humanity, as we know it, directly depends on the ability to secure affordable fuel, food, and freshwater. NASA Glenn Research Center (Glenn) has initiated a laboratory pilot study on using biofuels as viable alternative fuel resources for the field of aviation, as well as utilizing wind and solar technology as alternative renewable energy resources. The GreenLab Research Facility focuses on optimizing biomass feedstock using algae and halophytes as the next generation of renewable aviation fuels. The unique approach in this facility helps achieve optimal biomass feedstock through climatic adaptation of balanced ecosystems that do not use freshwater, compete with food crops, or use arable land. In addition, the GreenLab Research Facility is powered, in part, by alternative and renewable energy sources, reducing the major environmental impact of present electricity sources. The ultimate goal is to have a 100 percent clean energy laboratory that, when combined with biomass feedstock research, has the framework in place for a self-sustainable renewable energy ecosystem that can be duplicated anywhere in the world and can potentially be used to mitigate the shortage of food, fuel, and water. This paper describes the GreenLab Research Facility at Glenn and its power and energy sources, and provides recommendations for worldwide expansion and adoption of the facility s concept.

Bomani, B. M. McDowell↗

On the impact of tidal generation and energy storage integration in PV-rich electric distribution systems

Deep decarbonization of power system operations requires the maximal utilization of available renewable resources. At distribution-level operations, however, grid operators can face numerous challenges in integrating renewables at scale owing to the inherent intermittence of renewable energy resources. These include phenomena such as voltage fluctuations, which are typically mitigated through control actuators such as on-load tap changers (OLTC) as well as energy storage devices, such as battery energy storage systems (BESS). On the one hand, high intermittence of the available renewable portfolio may require increasingly aggressive control of actuators, thereby accelerating the probability of equipment failure. On the other hand, integrating BESS operations and having a diverse renewable generation portfolio can typically help stagger power/energy flow to mitigate the aforementioned adverse impacts. In this paper, we employ a Bayesian framework for equipment lifetime estimation to understand the impact of including tidal energy resources and BESS in distribution system operations for feeders having substantial distribution photovoltaic generation. Our results indicate that while tidal energy alone may slightly decrease equipment reliability, the adverse impact on reliability is significantly magnified by a generation portfolio consisting of tidal generation and photovoltaic generation. Here, we also study the tidal and photovoltaic hosting capacity problem with and without energy storage systems using equipment reliability as an added constraint. We conclude that energy storage increases the reliability-constrained hosting capacity of the distribution system.

14 SOLAR ENERGY↗

Optimization and Comparison of Modern Offshore Wind Turbine Generators Using GeneratorSE 2.0

As the offshore wind industry keeps growing at a rapid pace, developers are bracing themselves for a huge demand in critical rare earth metals which will threaten an already vulnerable supply chain. The wind energy industry is addressing this problem by investing in modern generator technologies that employ magnets with reduced rare earth content and high-field magnets enabled by rare-earth-free superconductors. In this paper we introduce the National Renewable Energy Laboratory's newly advanced GeneratorSE 2.0, which is a design and optimization tool that was developed to investigate the feasibility of such modern generators. Two direct-drive generator topologies with different magnet materials and mounting arrangements are investigated: an outer-rotor, V-shaped interior permanent magnet generator, and an inner-rotor normally conducting armature, paired with a low-temperature superconducting field with race-track coils. These technologies were evaluated for a range of power ratings between 15 and 25 MW, which represent the next generation of offshore wind turbines for both fixed-bottom and floating applications. The analyses indicate a new trend favoring the low-temperature superconducting technology for the direct-drive system.

direct-drive generators↗

Scaling Equitable Finance

Driven by dramatic declines in up-front cost, the U.S. solar photovoltaics (PV) industry has taken off over the past decade, growing from 1 gigawatt of installed capacity in 2009 to 89 gigawatts in 2020—or enough capacity to power roughly 19 million homes. The industry is expected to double in size over just the next 5 years.1 Much of the growth has been driven by large, utility-scale projects that can produce 5 mega- watts or more of power—enough to power at least 1,000 homes. The cost of electricity produced by these projects has decreased by more than 70 percent since 2010. As of Q3 2020, development costs of large, util- ity-scale solar PV power plants were under $1 per watt, down by more than 70 percent from 2010.2 A robust array of investors has come forward to efficiently deliver capital to these kinds of utility-scale projects including large banks, insurance companies, pension funds, and others. But low- and moderate-income communities, including communities of color, are at risk of being left behind in the transition to clean energy. Mission- driven solar project developers and financial institu- tions have been working alongside energy justice advocates to open up solar access for these communi- ties, using strategies ranging from community solar, to solar installations on affordable multifamily housing, to distributed solar and storage programs, and more. Their goals go beyond simply generating more green energy to advancing social equity by: • empowering communities to control their energy future • stabilizing energy prices, saving money, and build- ing wealth for low-income families • creating quality jobs • improving health by reducing pollution • providing energy resilience for vulnerable communities Mission-driven actors are successfully deploying a wide variety of strategies to meet these goals, from helping low-income homeowners get solar—and some- times battery storage, to developing solar projects serv- ing affordable rental housing and community facilities, to building larger “shared solar” projects to which households from across the community can subscribe. However, the financing ecosystem does not work nearly as well for these “mission driven” solar proj- ects as it does for utility-scale projects. For home rooftop solar, even if low-income consumers have a home and suitable roof, they may fail to qualify for federal tax incentives, lack adequate credit to qualify for a loan—or the mission-driven lenders seeking to serve them may not be adequately capitalized to make long-term loans. For mission-driven commercial or community-scale projects, assembling nearly every component of the project capital stack—whether bridging early-stage costs, attracting tax credit equity investors, securing long-term debt, or coming up with sponsor equity and filling gaps—can present challenges. A variety of obstacles contribute to the scarcity of financing for low-income solar, including small project sizes, lack of developer balance sheet capacity, both real and perceived issues with credit risk, elevated technical assistance needs, and greater subsidy requirements to pursue goals such as deep energy affordability, climate resilience, or job creation. Still other obstacles are regulatory: for example, not all states allow community solar projects or Power Purchase Agreements, common strategies used for providing low-income solar—and the potential for regulations to shift over time creates risks that mission-driven projects can ill afford. This report synthesizes information garnered from 47 key informant interviews, four focus group discus- sions involving 60 stakeholders, and a review of the substantial existing literature on low-income solar finance to assess the current landscape of mission- driven solar development in the United States, examine the roles that community-based financial institutions could play, and recommend public invest- ments and policy changes that could help to scale the provision of equitable solar finance. Key recommen- dations for policymakers and funders in the renew- able energy and community development fields that emerge from this process include the following: • Help to capitalize and support community-based lenders to provide flexible, low-cost, and long- term financing to mission-driven solar projects— including providing guarantees or other forms of credit enhancement. • Provide federal support for equitable solar, including a grant-in-lieu-of-credits option for the Investment Tax Credit to improve access to this critical government subsidy. • Develop pools of government and philanthropic support that can complement financing from community-based lenders to complete the capi- tal stack for mission-driven projects, as well as to support education and technical assistance to both consumers and potential project sponsors. • Create a national Renewable Energy Credits pro- gram that includes social equity targets to provide a baseline of support for clean energy generation. • Change utility regulations to remove barriers to low-income solar projects; lower permitting costs; provide greater certainty for developers, consumers and owners; and measure progress toward equity in renewable energy policy implementation.

14 SOLAR ENERGY↗

Unveiling the Hidden Evolution of Crystal Defects and Disorder in Energy Materials

Control of point defects and disorder in functional thin films and 2D materials is critical to realizing their full potential in applications ranging from energy storage to advanced electronics. However, these phenomena are often poorly understood, difficult to characterize, and challenging to direct with precision. This presentation explores emerging multi-modal computer vision to decipher and predict order in materials across multiple length scales in the electron microscope, from the atomic to the nanoscale. By fusing data from diverse sources, these powerful models provide unprecedented insights into materials' lifecycles, enabling the control of defects and their associated properties at a fundamental level. This capability promises to transform materials design and accelerate the development of next-generation technologies.

97 MATHEMATICS AND COMPUTING↗

Stochastic Microgrid Scheduling With Chance‐Constrained Resilience Consideration

Traditionally, it is assumed that microgrids transition seamlessly from grid‐connected operation to islanded mode in the event of sudden main grid outages. In reality, the islanding process, especially unintentional islanding, is rarely seamless. Instead, it is subject to voltage and frequency fluctuations caused by the instantaneous disconnection of the point of common coupling (PCC) switch, variations in loads and renewable generation output and even the protection tripping of distributed energy resources (DERs). To mitigate these fluctuations and facilitate a smooth islanding process, we propose a stochastic microgrid scheduling model that incorporates chance‐constrained resilience measures. Specifically, the resilience measure is defined as the probability of successful islanding (PSI), that is, the probability that a microgrid can mitigate the generation‐demand imbalance caused by the disconnection of the PCC switch, variations in load and renewable generation and DER tripping. This measure is modelled using chance constraints. Unlike existing reliability and resilience indices, which typically neglect the possibility of microgrid/DER failure under extreme events and assume their survival while primarily focussing on reducing impact duration or magnitude, the proposed PSI‐based framework explicitly addresses microgrid and DER survival during the islanding transition. The formulated nonlinear chance constraints are approximated using a multiinterval approach and equivalently represented as a mixed‐integer linear programming (MILP) formulation. Case study results validate the proposed method, showing that the PSI estimation error is reduced to less than 8%, compared to approximately 28% with existing methods. Various sensitivity analyses on the DER tripping rate and PSI settings were performed to validate the robustness of the proposed method. In particular, the necessity of accounting for DER tripping in the PSI calculation was demonstrated.

chance constrained optimization↗

Eastern Interconnection Wide-Area Oscillation Assessment and Study Report

To meet the government mandates such as Renewable Portfolio Standards (RPS), conventional synchronous generators with rotating mass are being displaced by inverter-based resources (IBRs), leading to high penetration of renewable energy sources (RES). As a result, the inherent properties and characteristics of the transformed generation mix may significantly impact the grid behaviour, and it is of paramount significance that the impact and the consequences of the resource mix change is thoroughly understood to adopt measures to maintain reliable grid operations. Of great concern is the inter-area low-frequency oscillation, which usually propagates through a large region and has a system-wide impact. Such oscillations may lead to unnecessary or inadvertent tripping of generators, that may be simply reacting to the oscillation originating from geographically remote sites. Such tripping of generators can lead to cascading outages, system split and load loss events. Over the years, several system-wide oscillation events have been observed across all three North American interconnections. This project titled Wide-area Oscillation Assessment and Trending Study, sponsored by the Office of Electricity (OE) of the Department of Energy (DOE), aims to conduct the required research to capture and investigate the potential changes in wide-area oscillatory performance of the system as a result of resource mix transition. The Pacific Northwest National Laboratory (PNNL) conducted this research and technical staff of Federal Energy Regulatory Commission (FERC) served as advisors to the project. The primary objective of this study is to assess whether there are significant trends in the power system wide-area oscillatory behaviours, as a result of the generation-mix changes due to the increased penetration of RES in the U.S. Eastern Interconnection (EI). The analysis presented in this report can serve as reference for future grid planning and operation of the EI system. This research conducted in this project evaluates the wide-area oscillatory behaviour of the EI, using a model-based approach for potential future resource mixes, and the measurement-based analysis with 21-month phasor measurement unit (PMU) time series. The oscillation modes in EI system along with the impact of the changes of the generation mix on the frequency and damping ratio (DR) of the oscillations have been studied.

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Generative AI for Power Grid Operations

Generative artificial intelligence (AI) has captured into the mainstream, demonstrating capabilities that once belonged solely to the realm of human cognition. From defeating world champions in complex games to generating human-quality text and images, Generative AI has proven its potential to revolutionize countless industries. The electric power grid is no exception. Generative AI's ability to process vast amounts of data rapidly, assist decision support and identify patterns could significantly enhance power grid operations. For example, Generative AI could improve state estimation where measurements are not available or integrate renewable energy sources more efficiently with probabilistic forecasting. The key contributions of this whitepaper are outlined below: (1) Comprehensive overview of Generative AI's applications in power grid operations: It highlights the opportunities in areas such as forecasting, state estimation, and demonstrating the potential for enhancing efficiency, reliability, and resilience. (2) Expanding Generative AI's impact through synergies with emerging technologies: The paper introduce NREL developed eGridGPT and explores how AI orchestration, multi-agent systems, and Digital Twins can collaborate to optimize grid operations, addressing the complexities of a decarbonized and electrified future. (3) In-depth analysis of challenges in implementing Generative AI: This includes considerations like data availability and quality, model validation, certification, and ethical concerns, ensuring responsible AI deployment. (4) Emphasizing human-AI collaboration: The whitepaper underscores the importance of trustworthy, transparency, and explainability in AI systems to promote seamless interaction between human operators and AI, ultimately improving decision-making. (5) Exploring future research and development: It identifies critical areas for further advancement to fully realize Generative AI's potential in power grid operations. This whitepaper serves as a valuable resource for researchers, practitioners, and policymakers looking to harness Generative AI for a more reliable, stable, and cost-effective power grid.

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Adaptive PV Frequency Control Strategy Based on Real-time Inertia Estimation

The declining cost of solar Photovoltaics (PV) generation is driving its worldwide deployment. As conventional generation with large rotating masses is being replaced by renewable energy such as PV, the power system’s inertia will be affected. As a result, the system’s frequency may vary more dramatically in the case of a disturbance, and the frequency nadir may be low enough to trigger protection relays such as under-frequency load shedding. The existing frequency-watt function mandated in power inverters cannot provide grid frequency support in a loss-of-generation event, as PV plants usually do not have power reserves. Here, a novel adaptive PV frequency control strategy is proposed to reserve the minimum power required for grid frequency support. A machine learning model is trained to predict system frequency response under varying system conditions, and an adaptive allocation of PV headroom reserves is made based on the machine learning model as well as real-time system conditions including inertia. Case studies show the proposed control method meets the frequency nadir requirements using minimal power reserves compared to a fixed headroom control approach.

14 SOLAR ENERGY↗

Dynamic Material Flow Analysis of Silicon Photovoltaic Modules to Support a Circular Economy Transition

Solar photovoltaics (PV) are the fastest growing renewable energy technologies for clean, cheap, and sustainable electricity generation. To prepare for rapid scale-up, the PV industry needs to project material requirements to build out all aspects of the supply chain appropriately and plan to handle large volumes of module waste. Impacts of deploying different material circularity strategies to reduce waste and conserve primary resources need to be quantified to inform sustainable material management. Here, we introduce the photovoltaic dynamic material flow analysis (PV DMFA) model based on PV electricity generation. The model quantifies material flows and stocks in the cradle-to-cradle life cycles of utility-scale c-Si PV systems in the United States through 2100. We present case studies for solar flat glass and aluminum frame materials under various scenarios to project the impacts of PV performance, reliability, and processing parameters, material circularity strategies, and module design shifts. In the absence of circularity measures, ~100 million MT of flat glass and ~12 million MT of aluminum would be needed for PV installations by 2100 to meet projected growth in domestic utility PV demand to nearly 1000 TWh in 2100. With optimistic but feasible improvements in efficiency, reliability, and circularity, material intensity and waste could be reduced by nearly 50%. Efficient module collection, minimally intrusive recycling, and careful scrap handling and cleaning could improve material circularity in the PV value chain. This model serves as a sustainability data support tool that may aid in the circular economy transition for PV systems.

circular economy↗

A reforecasting-based dynamic reserve estimation for variable renewable generation and demand uncertainty

The installed capacity of renewables-based energy sources has been increasing in traditional power systems. In order to accommodate the increased variability and uncertainty associated with the deeper penetration of renewable sources like solar and wind, adjusted amounts of dynamic reserve are needed. Although probabilistic dynamic reserve estimation methods have been previously developed, most of them consider the uncertainty to be represented by parametric density functions that tend to perform poorly under extreme events and, moreover, neglect uncertainty introduced by the forecasting model itself. Toward addressing these limitations, this work presents, for the first time, a dynamic reserve estimation method for flexibility that incorporates nonparametric density estimation and a machine learning based reforecasting to provide a day-ahead prediction of the mean and spread of uncertainty around the base forecast. The prediction is, in turn, used to estimate the up and down reserve relative to the base forecast. Here, the present method takes various endogenous and exogenous features, including the calendar variables, as input to estimate the day-ahead reserve. Using a combination of reforecasting and dynamic reserve estimation techniques, the method is shown to adjust better to the dynamic nature of reserve requirements providing only what is needed to accommodate the expected deviations. Considering California Independent System Operator (CAISO) solar, wind and load data over an 18 month period, up to 67% reduction in the amount of reserve capacity needed for a one day reserve and reserve penalty for solar uncertainty is demonstrated. Additionally, the risk of reserve insufficiency in meeting the net demand is reduced by 20% with the proposed method.

14 SOLAR ENERGY↗

Developing VSC-HVDC Oscillation Damping Control Constraints in Unit Commitment

High-voltage direct current (HVDC) systems within the existing power grids will play a pivotal role in enabling high share of renewable power integration and transportation electrification. There is a need for transmission planning models to accurately capture the impact of VSC-HVDC oscillation damping control on the system planning and model the constraints in the security constrained unit commitment (SCUC) problem. In this paper, the SCUC problem in a hybrid DC-AC grid considering damping on electromechanical inter-area oscillation is studied. An electromechanical oscillation-driven transmission capability constraints are derived from system swing equation and incorporated into the SCUC. Multiple system damping control scenarios are set based on the extracted plausible bounds of damping coefficient and inertia constant to linearize the nonlinear expressions. The SCUC problem with proposed constraints is tested on the Reliability Test System Grid Modernization Lab Consortium (RTS-GMLC) via PLEXOS. The impact of the proposed constraints on regional generation, inertia, power flow, annual system cost, and renewable energy curtailment are fully assessed.

damping control↗

Grid-Following Inverters and Synchronous Condensers: A Grid-Forming Pair?

As power systems across the globe continue to achieve higher instantaneous penetrations of power electronic converter-interfaced renewable sources, the stability of these power systems is challenged because of the removal of synchronous machines, from which stability is traditionally derived. Although technological solutions to these stability challenges are on the horizon, such as the use of grid-forming inverters, they are not yet widely applied to larger power systems, which presents operational challenges for power systems achieving these high instantaneous penetrations today. A potential interim solution using existing technologies is to pair synchronous condensers with grid-following inverters, which might prolong the stability of an operating power system while synchronous generators are turned off during periods of high renewable energy availability. This work examines the transient stability of such a solution using PSCAD simulations of a two-bus system coupled to a varied-length transmission line, with a synchronous condenser at one bus and a grid-following inverter with grid-support functionality at the other. The system is exposed to load step, balanced fault, and unbalanced fault perturbations. It was found that this simple system returned to a steady state for transmission line lengths up to 125 km after 10% load steps, or a variety of fault types.

grid-following inverters↗

Secured Reserve Scheduling of Pumped-Storage Hydropower Plants in ISO Day-ahead Market

Due to the fast response ability and high ramping rates, pumped-storage hydropower (PSH) plants are playing an increasingly critical role in mitigating power generation fluctuations induced by the growing proliferation of renewable energy resources. However, because they are energy-limited resources, actual reserve deployment from PSHs would cause the deviation of state-of-charge (SOC) from the scheduled value, which, once accumulated over time, could induce potential violations on SOC limits and cause non-dispatchability of PSHs. In recognizing this potential issue, it can become important to securing the reserve schedule of PSHs and other energy limited resources preventively in the day-ahead market clearing. To ensure reserve dispatchability of PSHs despite SOC deviations, this paper proposes the reserve secure constraints, which are cast as a distributionally robust chance-constrained formulation by judiciously introducing random parameters to describe deployment ratios of scheduled regulation reserve from PSHs. Furthermore, these constraints are converted into tractable second-order cone constraints, and further approximated as linear constraints to be compatible with the current ISO day-ahead market clearing model. A modified IEEE 118-bus system with multiple PSHs is adopted to verify the proposed approach.

13 HYDRO ENERGY↗