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A structural economic model is presented for estimating the demand functions for natural gas and crude oil in industry and in steam electric power generation. Extensions of the model to other commodities are indicated.
Over the last two decades, grid-connected solar photovoltaic systems have increased from a niche market to one of the leading power generation capacity additions annually. In 2018 the total installed photovoltaic electricity generation capacity exceeded 500 GW. Another doubling is forecasted until the early 2020s. Therefore, the further development is coupled with the question at what prices solar photovoltaic electricity can be provided and delivered to the customers. The installation of PV systems for self-consumption is already now an interesting option for many people but in general limited to those who have access to a rooftop they own or can use. A new envelopment to enable residents of multi apartment buildings to commonly use electricity generated by a PV system (collective self-consumption) is a relatively new development and is still facing a lot of administrative and regulatory challenges.
The residential buildings sector is one of the largest electricity consumers worldwide and contributes disproportionally to peak electricity demand in many regions. Strongly driven by occupant activities, household energy consumption is stochastic and heterogeneous in nature. However, most residential energy models applied by industry use homogeneous, deterministic activity schedules, which work well for predictions of annual energy consumption, but can result in unrealistic hourly or sub-hourly electric load profiles, with exaggerated or muted peaks. The increasing proportion of variable renewable energy generators means that representing the heterogeneity and stochasticity of occupant behavior is now crucial for reliable planning at both bulk-power and distribution-system scales. This work presents a novel and open-source occupancy simulation approach that can simulate a diverse set of individual occupant and household event schedules for all major electricity, fuel, and hot water end uses. To accomplish this, we evaluated three alternative occupant activity simulation approaches before selecting a hybrid combining time-inhomogeneous Markov chains and probability-sampling of event durations and magnitudes. Further, we integrated the stochastic occupancy simulation with an open-source bottom-up physics-simulation building stock model and published a set of 550,000 diverse household end-use activity schedules representing a national housing stock. The simulator was verified against time-use survey data, and simulation results were validated against measured end-use electricity data for accuracy and reliability. While we use data for the United States, our application demonstrates how similar approaches could be applied using the time-use survey data collected in many countries around the world.
Wind energy is investigated as a source of energy. The wind energy program that is managed by the NASA-Lewis Research Center is described. The Lewis Research Center's Wind Power Office, its organization, plans, and status are discussed. Major elements of the wind power project included are: an experimental 100 kW wind-turbine generator; first generation industry-built and user-operated wind turbine generators; and supporting research and technology tasks.
The feasibility of an electric power generation system utilizing a sun-tracking parabolic concentrator and a Stirling engine/linear alternator is being evaluated. Performance predictions and cost analysis of a proposed large distributed system are discussed. Design details and preliminary test results are presented for a 9.5 ft diameter parabolic dish at the Jet Propulsion Laboratory (Caltech) Table Mountain Test Facility. Low temperature calorimetric measurements were conducted to evaluate the concentrator performance, and a helium flow system is being used to test the solar receiver at anticipated working fluid temperatures (up to 650 or 1200 C) to evaluate the receiver thermal performance. The receiver body is designed to adapt to a free-piston Stirling engine which powers a linear alternator assembly for direct electric power generation. During the next phase of the program, experiments with an engine and receiver integrated into the concentrator assembly are planned.
The Energy Technology Innovation Partnership Project (ETIPP) worked with the Makah Tribe on strategic energy planning, including scoping future energy needs of relocated facilities, understanding the potential for new energy generation options to support current and future energy demand, and supporting communication and capacity-building goals.
The U.S. Department of Energy (DOE), Lockheed Martin Corporation (LM), and NASA Glenn Research Center (GRC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. In support of this program, GRC has been involved in testing Stirling convertors, including the Advanced Stirling Convertor (ASC), for use in the ASRG. This testing includes electromagnetic interference/compatibility (EMI/EMC), structural dynamics, advanced materials, organics, and unattended extended operation. The purpose of the durability tests is to experimentally demonstrate the margins in the ASC design. Due to the high value of the hardware, previous ASC tests focused on establishing baseline performance of the convertors within the nominal operating conditions. The durability tests present the first planned extension of the operating conditions into regions beyond those intended to meet the product spec, where the possibility exists of lateral contact, overstroke, or over-temperature events. These tests are not intended to cause damage that would shorten the life of the convertors, so they can transition into extended operation at the conclusion of the tests. This paper describes the four tests included in the durability test sequence: 1) start/stop cycling, 2) exposure to constant acceleration in the lateral and axial directions, 3) random vibration at increased piston amplitude to induce contact events, and 4) overstroke testing to simulate potential failures during processing or during the mission life where contact events could occur. The paper also summarizes the analysis and simulation used to predict the results of each of these tests.
Hydropower generation may play an increasingly important role in the power grid under increasing contribution of variable renewable sources such as wind and solar. An improved understanding of the changes to hydropower dispatch under future higher VRE grid conditions reveals research gap that should be informed power grid planning and reservoir water releases policies considering multiple other water uses and varying hydrologic condition. Here this study aims to understand the role of hydropower in a changing power grid by employing a production cost model, PLEXOS, across future power system scenarios, planning horizons, and regions. We explore optimized hydropower dispatch to understand its potential role in minimizing the system cost and renewable curtailment. We also examine the sensitivity of hydropower revenue under various grid scenarios of the Eastern U.S. and hydrology conditions. Results indicate hydropower generation follows net load and compensates for the variability of solar and wind generation. Although energy prices are lower during some periods in the future grid scenarios, there is a potential for higher revenue for hydropower by providing both energy and ancillary services during times of stress. Additionally, hydropower revenue is sensitive to hydrology in the SERC region, which we considered as an example. The feasibility of hydropower dispatching with higher ramps between low and high hourly-capacity factors, as indicated in the optimization model, requires further study to consider other water use and ecology constraints.
The U.S. Department of Energy (DOE), Lockheed Martin Corporation (LM), and NASA Glenn Research Center (GRC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. In support of this program, NASA?s Glenn Research Center (GRC) has been involved in testing Stirling convertors, including the Advanced Stirling Convertor (ASC), for use in the ASRG. This testing includes electromagnetic interference/compatibility (EMI/EMC), structural dynamics, advanced materials, organics, and unattended extended operation. The purpose of the durability tests is to experimentally demonstrate the margins in the ASC design. Due to the high value of the hardware, previous ASC tests focused on establishing baseline performance of the convertors within the nominal operating conditions. The durability tests present the first planned extension of the operating conditions into regions beyond those intended to meet the product spec, where the possibility exists of lateral contact, overstroke, or over-temperature events. These tests are not intended to cause damage that would shorten the life of the convertors, so they can transition into extended operation at the conclusion of the tests. This paper describes the four tests included in the durability test sequence: 1) start/stop cycling, 2) exposure to constant acceleration in the lateral and axial directions, 3) random vibration at increased piston amplitude to induce contact events, and 4) overstroke testing to simulate potential failures during processing or during the mission life where contact events could occur. The paper also summarizes the analysis and simulation used to predict the results of each of these tests.
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.
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.
A developer will install a renewable energy system on DOE property. In exchange, DOE agrees to purchase the power generated by the system. These power purchase payments repay the developer over the contract term. The developer owns, operates, and maintains the system for the life of the contract.
The purpose of this grant was to support NASA in modeling efforts to predict the transient dynamic and thermodynamic response of the space station solar dynamic power generation system. In order to meet the initial schedule requirement of providing results in time to support installation of the system as part of the initial phase of space station, early efforts were executed with alacrity and often in parallel. Initially, methods to predict the transient response of a Rankine as well as a Brayton cycle were developed. Review of preliminary design concepts led NASA to select a regenerative gas-turbine cycle using a helium-xenon mixture as the working fluid and, from that point forward, the modeling effort focused exclusively on that system. Although initial project planning called for a three year period of performance, revised NASA schedules moved system installation to later and later phases of station deployment. Eventually, NASA selected to halt development of the solar dynamic power generation system for space station and to reduce support for this project to two-thirds of the original level.
Today’s power grid is becoming more diverse and integrated with high-level distributed energy resources and smart control technologies that is creating a new set of grid management challenges in terms of large-scale, nonlinear, and non-convex problem modeling, complex and time-consuming computation, as well as difficult uncertainty handling. This project focused on solving a challenging multi-period security-constrained generation scheduling problem, which is of great importance for maximizing the social welfare of real-time dispatch, day-ahead market, as well as weekly planning of power systems. Our developed software explored parallel optimization algorithms for complex and realistic power system models, and develop fast, efficient, and robust grid optimization solutions on the high-performance computing platform that will enable increased grid economics, flexibility, resilience, as well as energy security in the United States.
As the demands and applications of wearable electronics increase, the need of power supply for wearable electronics becomes the critical issue. Both batteries and capacitors can be used as power supplier. In terms of energy storage device, capacitors have many advantages over the batteries, but have a lower energy storage density. To improve the energy density, composites, in which inorganic particles are embedded in a polymer matrix, have been identified as a promising approach to create the dielectrics with a higher energy storage density. The physics behind the composite approach is that the inorganics have a higher dielectric constant and polymers can stand with a higher electric field so that the composites can exhibit a relative dielectric constant and stand with a relative electric field. Therefore, the composites can exhibit a higher energy storage density. However, the embedment of inorganic particles into polymer severely reduces the flexibility of the polymer. To develop flexible energy storage ultracapacitors as an energy storage device for wearable electronics, an all-organic composite approach, in which a dielectric polymer is mixed with polar organic molecules, is introduced. It is experimentally found that by adding a small amount of polar organic molecules into dielectric polymers, the polymers exhibits a high dielectric constant and can stand with a higher electric field. More importantly, the flexibility of the all-organic composites is better than the polymer matrix. Therefore, the all-organic composites can be a strong and promising candidate for the development of flexible energy storage devices for the wearable electronics. In this study, three different dielectric polymers and three different polar molecules were studied. All the all-organic composite systems exhibit a significant improvement on the energy storage density. These new flexible energy storage devices are being developed to be fabricated with on-demandadditive electronics manufacturing processes, so that they can be fabricated when needed in space on the International Space Station and planned lunar habitat and other future missions. These flexible energy storage devices will provide the storage in concert with other printed power generation devices to allow crew health and structural health monitoring sensor devices and systems to be self-powered, not requiring any external power or batteries.
The rapid growth of hyperscale AI data centers is bringing renewed attention to the reliability risk that sustained forced oscillations pose to bulk power systems, with cyclic computational workloads emerging as a new forcing source. Unlike the broadband, stochastic disturbances from traditional industrial loads such as arc furnaces, AI training and inference facilities can inject large active power swings concentrated at specific frequencies over extended durations - characteristics that existing grid planning practices do not account for. While the North American Electric Reliability Corporation (NERC) has recognized this gap and called for system-level studies of large load interconnections, no standardized methodology exists to screen, simulate, and quantify these risks at the planning stage. This report presents the Risk Assessment Tool for Large Load-induced Events (RATLLE), a Python-based, publicly available script suite developed at the Pacific Northwest National Laboratory to evaluate bulk power system reliability risks from data center-induced oscillations. RATLLE implements a three-module workflow: a screening module that identifies vulnerable interconnection locations and excitable system modes; a simulation module that models cyclic data center load behavior using a commercial positive sequence simulation platform; and an analysis module that computes risk metrics and generates interactive visualization dashboards. The risk metrics, formulated around simulation observables, map oscillation impacts to a three-stage severity scale spanning latent equipment fatigue through imminent cascading failure. The methodology is demonstrated on two Western Electricity Coordinating Council (WECC) system models: a publicly available 240-bus reduced representation and a detailed 2031 Heavy Winter planning case. Case studies illustrate that even modest 50 MW forced oscillations at resonant frequencies can produce wide-area power swings, N-1 security constraint violations, and cascading generator trips through protection actions - outcomes that would not occur under normal operating conditions without oscillations present. The results underscore the need for standardized oscillation impact assessment in large load interconnection studies and provide a reproducible, extensible framework for utilities to adopt or customize within their existing planning workflows.
Special considerations exist for island grids seeking to smoothly integrate distributed energy resources (DERs), such as rooftop photovoltaics (PV), with an existing fossil fuel-based grid without compromising system stability and reliability. Hawaii, having successfully integrated nonconventional renewable energy sources for a hybrid electricity grid, may serve as a guide for technical specifications and interconnection policy. Island grid planners may seek to follow Hawaii's example by standardizing technical specifications of generators, particularly for advanced inverter components.
In real-world domains (e.g., a mobile robot environment), things do not always proceed as planned, so it is important to develop better execution-monitoring techniques and replanning capabilities. These capabilities in the SIPE planning system are described. The motivation behind SIPE is to place enough limitations on the representation so that planning can be done efficiently, while retaining sufficient power to still be useful. This work assumes that new information given to the execution monitor is in the form of predicates, thus avoiding the difficult problem of how to generate these predicates from information provided by sensors. The replanning module presented here takes advantage of the rich structure of SIPE plans and is intimately connected with the planner, which can be called as a subroutine. This allows the use of SIPE's capabilities to determine efficiently how unexpected events affect the plan being executed and, in many cases, to retain most of the original plan by making changes in it to avoid problems caused by these unexpected events. SIPE is also capable of shortening the original plan when serendipitous events occur. A general set of replanning actions is presented along with a general replanning capability that has been implemented by using these actions.