Active Power Control on Wind Turbine Machines (CRADA Final Report)
This project will evaluate the effectiveness of active power control by wind turbine machines.
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This project will evaluate the effectiveness of active power control by wind turbine machines.
Two recent studies sponsored by the U.S. Department of Energy (DOE) and the National Renewable Energy Laboratory (NREL) have examined the impacts of integrating high penetrations of wind and solar energy on the Eastern and Western electric grids. The Eastern Wind Integration and Transmission Study (EWITS), initiated in 2007, examined the impact on power system operations of reaching 20% to 30% wind energy penetration in the Eastern Interconnection. The Western Wind and Solar Integration Study (WWSIS) examined the operational implications of adding up to 35% wind and solar energy penetration to the Western Interconnect. Both studies examined the costs of integrating variable renewable energy generation into the grid and transmission and operational changes that might be necessary to address higher penetrations of wind or solar generation. This paper identifies key insights from these regional studies for integrating high penetrations of renewables in the U.S. electric grid. The studies share a number of key findings, although in some instances the results vary due to differences in grid operations and markets, the geographic location of the renewables, and the need for transmission.
This presentation provides a high-level overview of advanced power electronic functionality for renewable energy integration with the electric power grid.
The H2@Scale concept is focused on developing hydrogen as an energy carrier and using hydrogen's properties to improve the national energy system. Specifically hydrogen has the abilities to (1) supply a clean energy source for industry and transportation and (2) increase the profitability of variable renewable electricity generators such as wind turbines and solar photovoltaic (PV) farms by providing value for otherwise potentially-curtailed electricity. Thus the concept also has the potential to reduce oil dependency by providing a low-carbon fuel for fuel cell electric vehicles (FCEVs), reduce emissions of carbon dioxide and pollutants such as NOx, and support domestic energy production, manufacturing, and U.S. economic competitiveness. The analysis reported here focuses on the potential market size and value proposition for the H2@Scale concept. It involves three analysis phases: 1. Initial phase estimating the technical potential for hydrogen markets and the resources required to meet them; 2. National-scale analysis of the economic potential for hydrogen and the interactions between willingness to pay by hydrogen users and the cost to produce hydrogen from various sources; and 3. In-depth analysis of spatial and economic issues impacting hydrogen production and utilization and the markets. Preliminary analysis of the technical potential indicates that the technical potential for hydrogen use is approximately 60 million metric tons (MMT) annually for light duty FCEVs, heavy duty vehicles, ammonia production, oil refining, biofuel hydrotreating, metals refining, and injection into the natural gas system. The technical potential of utility-scale PV and wind generation independently are much greater than that necessary to produce 60 MMT / year hydrogen. Uranium, natural gas, and coal reserves are each sufficient to produce 60 MMT / year hydrogen in addition to their current uses for decades to centuries. National estimates of the economic potential of hydrogen production using steam methane reforming of natural gas, high temperature electrolysis coupled with nuclear power plants, and low temperature electrolysis are reported. To generate the estimates, supply curves for those technologies are used. They are compared to demand curves that describe the market size for hydrogen uses and willingness to pay for that hydrogen. Scenarios are developed at prices where supply meets demand and are used to estimate energy use, emissions, and economic impacts.
The H2@Scale concept is focused on developing hydrogen as an energy carrier and using hydrogen's properties to improve the national energy system. Specifically hydrogen has the abilities to (1) supply a clean energy source for industry and transportation and (2) increase the profitability of variable renewable electricity generators such as wind turbines and solar photovoltaic (PV) farms by providing value for otherwise potentially-curtailed electricity. Thus the concept also has the potential to reduce oil dependency by providing a low-carbon fuel for fuel cell electric vehicles (FCEVs), reduce emissions of carbon dioxide and pollutants such as NOx, and support domestic energy production, manufacturing, and U.S. economic competitiveness. The analysis reported here focuses on the potential market size and value proposition for the H2@Scale concept. It involves three analysis phases: 1. Initial phase estimating the technical potential for hydrogen markets and the resources required to meet them; 2. National-scale analysis of the economic potential for hydrogen and the interactions between willingness to pay by hydrogen users and the cost to produce hydrogen from various sources; and 3. In-depth analysis of spatial and economic issues impacting hydrogen production and utilization and the markets. Preliminary analysis of the technical potential indicates that the technical potential for hydrogen use is approximately 60 million metric tons (MMT) annually for light duty FCEVs, heavy duty vehicles, ammonia production, oil refining, biofuel hydrotreating, metals refining, and injection into the natural gas system. The technical potential of utility-scale PV and wind generation independently are much greater than that necessary to produce 60 MMT / year hydrogen. Uranium, natural gas, and coal reserves are each sufficient to produce 60 MMT / year hydrogen in addition to their current uses for decades to centuries. National estimates of the economic potential of hydrogen production using steam methane reforming of natural gas, high temperature electrolysis coupled with nuclear power plants, and low temperature electrolysis are reported. To generate the estimates, supply curves for those technologies are used. They are compared to demand curves that describe the market size for hydrogen uses and willingness to pay for that hydrogen. Scenarios are developed at prices where supply meets demand and are used to estimate energy use, emissions, and economic impacts.
This presentation provides an overview of increasing variable renewable electricity generation, its implications on the grid, the opportunity for load side grid support, H2@Scale, the potential need for seasonal electricity storage, and how ammonia production might fit into H2@Scale and its vision.
Transportation is currently the least-diversified energy demand sector, with over 90% of global transportation energy use coming from petroleum product. After over a century of petroleum dominance, however, many leading experts anticipate major electrification trends that could disrupt the transportation energy demand landscape. These changes in electricity demand complement profound changes happening within electric power supply systems, including integration of variable renewables, distributed generation and storage, and greater participation in power system planning and operations from traditionally passive consumers. This broader context underscores the importance of understanding how transportation electrification will impact electricity demand, including changes in the load shapes that characterize the system and the opportunity to leverage flexible EV charging to more cost-effectively balance demand and supply. This talk provides an overview of recent findings on infrastructure requirements to support EV adoption, integration challenges and the impact of EV on power systems, and opportunities to leverage flexible (or smart) EV charging to support power system planning and operations.
The contribution of intermittent (renewable) energy sources such as wind and solar continues to increase as renewables improve in both efficiency and price-point. However, the variability of renewables generates additional challenges for the electric grid in the form of rapidly varying electric loads. Proposed options for accommodating this load have included operating nuclear reactors in a load follow mode, or operating the reactor at or near steady state and bypassing steam directly to the condenser. Both of these strategies result in lost energy potential. In addition to lost energy potential, load follow operation can result in increased stress on the fuel and other mechanical components. A more attractive approach is to operate the reactor at or near steady state and bypass excess steam to a thermal energy storage system. The thermal energy can then be recovered, either for electric generation during periods of peak electric demand, or for use in ancillary applications such as desalination and hydrogen production. Sensible Heat Thermal Energy Storage is a mature technology currently used in solar energy systems. This research focuses on the design and coupling of such a system to Small Modular Reactors (SMRs), typical of Integral Pressurized Water Reactor (IPWR) designs currently under development. (authors)
The volatility of electricity price presents a challenge to market participants as their decision-making process are highly depend on the accuracy of price forecasts. However, there is growing empirical evidence of increasing price volatility and price spikes in electricity markets as a result of variable renewable energy generation, extreme weather events, and other factors. The distribution shift caused by spikes in electricity price data differentiates the forecasting tasks from other renewable energy sources. Moreover, the observations may be compromised by cyberattacks and thus not available in the testing phase. To this end, we propose a Similarity-Enhanced Electricity Decomposition Forecasting model (SEED-Forecaster) to address the missing response problem and spikes capturing in short-term electricity price forecasting. The effectiveness of the proposed framework is tested on real-world electricity price data from California Independent System Operator (CAISO). Numerical results of case studies show that the proposed SEED-Forecsater can enhance forecasting performance, particularly in capturing electricity spikes, even under conditions without regressors during testing stage.
As variable renewable energy penetration increases beyond 80%, clean power systems will require long-duration energy storage or flexible, low-carbon generation. Here, we provide a detailed techno-economic evaluation and uncertainty analysis of applicable technologies and identify challenges and opportunities to support electric grid planning. We show that for a 120-h storage duration rating, hydrogen systems with geologic storage and natural gas with carbon capture are the least-cost low-carbon technologies for both current and future capital costs. These results are robust to uncertainty for the future capital cost scenario, but adiabatic compressed air and pumped thermal storage could be the least-cost technologies in the current capital cost scenario under uncertainty. Finally, we present a new storage system using heavy-duty vehicle fuel cells that could reduce the levelized cost of energy by 13%–20% compared with the best previously considered storage technology and, thus, could help enable very high (>80%) renewable energy grids.
As the nation continues to encourage, through market structures and financial incentives, the proliferation of intermittent renewable electricity, how to optimize the ever-changing electric grid and identify means to retain and improve resilience, while ensuring continued reductions in GHG emissions, will be critical. According to Bloomberg, wind & solar generated 10.5% of US electricity in 2020 and that percentage continues to grow. In support of expanding renewable energy use, and to address its intermittent nature, this project will develop the Hydrogen Storage for Flexible Fossil Fuel Power Generation platform that is dispatchable, reliable, repeatable and have the ability to produce zero or negative carbon power while interfacing with geology capable of CO2 and hydrogen storage. GTI Energy (GTIE) and team members Illinois State Geological Survey (ISGS), Mitsubishi Heavy Industries America (MHIA), Ameren Illinois, Hexagon Purus, and the Low Carbon Resources Initiative (LCRI) completed a Phase I Conceptual Study under contract DE-FE0032012 for Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine. The Hydrogen Storage for Flexible Fossil Fuel Power Generation platform addresses the intermittent nature of the expanding use of Variable Renewable Energy (VRE) generation. The low cost of the electricity (COE) generated results in greater dispatch and more operation at higher power levels (higher efficiency), fewer short intervals, and fewer start/stop cycles. The reliable, resilient system can produce zero carbon power and store hydrogen. It will demonstrate hydrogen storage in geologic formations like those used in natural gas underground storage thus enabling large scale storage of hydrogen in sedimentary strata across the United States rather than in geographically restricted salt caverns. The Phase I study confirmed the system is feasible and generates power at lower cost than other low carbon approaches. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production. The study advanced the maturity of the H 2 storage-based system with flexible power generation by completing a Pre-FEED study (Phase II). The Pre-FEED focused on the selected Energy Farm on the University of Illinois Urbana-Champaign (UIUC) site that includes above ground and underground hydrogen storage, low-carbon hydrogen production (GTI’s Compact Hydrogen Generator, CHG) with underground CO2 sequestration, and a 40-MW class gas turbine. The Pre-FEED addressed the entire system and its interconnection to the natural gas and electric grid and mitigation of key risks, such as storage behavior, load-following, and system operation. During Phase 1 of the project, the team completed key tasks, which moved the entire demonstration project, specific components and approaches closer to commercialization. These Phase I Accomplishments include: Completing System Requirements Review; Completing System Layout and Modeling - Heat & Mass Balance and Process Flow Diagram; Completing modelling of 9 turbine performance cases; Evaluating rock strata for underground storage of hydrogen and sequestration of carbon dioxide; Completing initial modelling of underground storage of hydrogen and withdrawal with evaluation of loss and water production; Identifying roadable storage for above ground hydrogen storage; Identifying existing electrical infrastructure for receiving/delivering electricity; Identifying existing gas supply infrastructure for receiving natural gas; Document concept design/development plans in required reports. Conclusions: The 12-month Feasibility study in Phase I study was completed and confirmed the system is feasible and generates power at lower cost than other low carbon approaches and even lower cost than the reference NGCC plant without carbon capture when taking advantage of 45Q carbon credits. The study enabled the fidelity of the concept to be improved and allowed identification of the requirements for the system. Defining the individual system and component requirements was performed via the system requirements review with the whole team. These requirements were then incorporated into and iterated with our Heat & Mass Balance process model and process flow diagrams were generated to reflect the overall system. This information was then used to complete the TEA and show economic feasibility. Large scale non-salt geologic storage of hydrogen is an enabling technology for a hydrogen-fired turbine that can be retrofitted into large-scale electric generating units (EGU). Our demonstration will include 428 MWh or ~4 hours full load of hydrogen storage (above and underground). Carbon capture inherent to the CHG process can capture 90% CO 2 (with upgrades to >98%). This system provides a COE of 23% savings relative to an NGCC with a post combustion amine system. Our proposed storage system decouples carbon capture and hydrogen production from power production; therefore, we expect our proposed system’s efficiency and variable COE to be superior resulting in overall higher dispatch and reduced deep cycling. Our demonstration will be full to multi-day hydrogen storage and has the potential for longer (seasonal) duration commercially. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production.
Solar photovoltaic (PV) and wind energy systems are crucial for decarbonizing the electricity sector and achieving climate goals. However, these systems are weather-dependent, and ignoring the potential changes in their generation levels due to climate change could compromise achieving climate targets and meeting future electricity demand. This study evaluates the impact of climate change on the generation potential of wind and solar PV systems in India for three future periods, 2030 (2021-2040), 2050 (2041-2060), and 2070 (2061-2080) compared to the baseline year 2000 (1991-2010), under three emission scenarios: SSP245, SSP370, and SSP585. Solar PV generation levels consistently decline (up to 10 %) across all regions and scenarios. Wind energy shows more pronounced variability (-20 % to 30 %). The South and Southeastern regions of India show improvements in wind potential across all scenarios and time periods. This study also investigated the projected changes in the generation droughts of both energy systems. For solar PV, drought days increase across most regions (exceeding 500 days under SSP370 across the 20-year period). In contrast, wind energy sees a reduction in drought days, especially in parts of South and Southeast India (declines exceeding 50 days across different scenarios). For both energy systems, the patterns of generation drought and generation potential are similar, and indicate that Western and Northern India may be less favorable for the future expansion of solar PV and wind energy, respectively. These results highlight the need to account for the potential impacts in future capacity planning.
This document discusses improving system operations with forecasting and solar generation. By integrating variable renewable energy (VRE) forecasts into system operations, power system operators can anticipate up- and down-ramps in VRE generation in order to cost-effectively balance load and generation in intra-day and day-ahead scheduling. This leads to reduced fuel costs, improved system reliability, and maximum use of renewable resources.
Decision makers rely on models to make important regulatory, policy, and investment decisions. For power systems, these models must capture (i) the future challenges introduced by the integration of large quantities of variable renewable energy sources and (ii) the role that energy storage technologies should play. In this paper, we explore several different approaches to selecting representative days for generation expansion planning models, focusing on capturing these dynamics. Further, we propose a new methodology for adjusting the outputs of clustering algorithms that provides three advantages: the targeted level of net demand is captured, the underlying net demand shapes that define ramping challenges are accurately represented, and the relationship between annual energy and peak demand is captured. This weighting methodology reduces the magnitude of the error in the representative day based generation expansion planning models estimation of costs by 61% on average. The results also demonstrate the importance of carefully performing the clustering of representative days for both system costs and technology mix. In most cases improvements to the total cost of different representative day based expansion plans are realised where conventional generation capacity is substituted for energy storage. Based on the energy storage technology selected we conclude this capacity is being used to address ramping challenges as opposed to shifting renewable generation from off to on peak periods, reinforcing the importance of capturing detailed intraday dynamics in the representative day selection process.
If renewable energy resources continue to become a larger part of the generation mix in the United States (U.S.), so does the potential impact of prolonged periods of low wind and solar generation, known as variable renewable energy (VRE) droughts. In such a future, naturally occurring VRE droughts need to be evaluated for their potential impact on grid reliability. This study is the first of its kind to examine the impacts of compound VRE energy droughts in the Western U.S. across a range of potential future climate and infrastructure scenarios. We find that compound VRE drought severity may increase significantly in the future, primarily due to the dramatic increase in wind and solar generation needed in some future infrastructure scenarios. We find that in our future climate scenario, the variability of energy drought severity increases, which has implications for sizing energy storage necessary for mitigating drought events. We also examine the spatial patterns of compound VRE drought events that effect multiple regions of the grid simultaneously. These co-occurring events have distinct spatial patterns depending on the season. We observed overall fewer connected events in the future with the combined effect of potential climate and infrastructure changes, although in the fall we observe a climate-induced shift toward events which impact more regions simultaneously.
This document is the Spanish version of 'Greening the Grid- Forecasting Wind and Solar Generation Improving System Operations'. It discusses improving system operations with forecasting with and solar generation. By integrating variable renewable energy (VRE) forecasts into system operations, power system operators can anticipate up- and down-ramps in VRE generation in order to cost-effectively balance load and generation in intra-day and day-ahead scheduling. This leads to reduced fuel costs, improved system reliability, and maximum use of renewable resources.
With the increasing urgency to decarbonize power systems, while mitigating extreme events, capacity expansion models can play a vital role in reliably planning the expansion of power systems and facilitating the integration of renewable energy sources. Optimizing capacity expansion generally involves selecting surrogate representative days from forecasts of load and the generation profiles of variable renewable energy resources. To properly select those representative days, we propose a novel input-based approach in combination with the k-means clustering algorithm that utilize three unique operational inputs: load shedding, renewable curtailment, and transmission congestion. The proposed method allows for more robust and cost-effective capacity planning. The method is validated using a capacity expansion model and a production cost model based on California Independent System Operator (CAISO)'s decarbonization goals, and results in reduced costs and drastically lower load shedding.
Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision-makers. With the recent surge in variable renewable energy (VRE) generators — primarily wind and solar photovoltaics — the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. This report summarizes the analyses and model experiments that were conducted as part of two workshops on modeling VRE for national-scale capacity expansion models. It discusses the various methods for treating VRE among four modeling teams from the Electric Power Research Institute (EPRI), the U.S. Energy Information Administration (EIA), the U.S. Environmental Protection Agency (EPA), and the National Renewable Energy Laboratory (NREL). The report reviews the findings from the two workshops and emphasizes the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making. This research is intended to inform the energy modeling community on the modeling of variable renewable resources, and is not intended to advocate for or against any particular energy technologies, resources, or policies.