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The author expresses his views on future energy demand on the west coast of the United States and how that energy demand translates into demand for major fuels. He identifies the major uncertainties in determining what future demands may be. The major supply options that are available to meet projected demands and the policy implications that flow from these options are discussed.
A recent history of electricity forecasting in California is given. Dealing with forecasts and regulatory uncertainty is discussed. Graphs are presented for: (1) Los Angeles Department of Water and Power and Pacific Gas and Electric present and projected reserve margins; (2) California electricity peak demand forecast; and (3) California electricity production.
With the increasing awareness for sustainable future and green energy, the demand for electric vehicles (EVs) is growing rapidly, thus placing immense pressure on the energy grid. To alleviate this, local trading between EVs should be encouraged. In this paper, we propose a blockchain and public key infrastructure (PKI)-based secure vehicle-to-vehicle (V2V) energy-trading protocol. A permissioned blockchain utilizing the proof of authority (PoA) consensus and smart contracts is used to securely store data. Encrypted communication is ensured through transport layer security (TLS), with PKI managing the necessary digital certificates and keys. A multi-leader, multi-follower Stackelberg game-based trade algorithm is formulated to determine the optimal energy demands, supplies, and prices. Finally, we propose a detailed communication protocol that ties all the components together, enabling smooth interaction between them. Key findings, such as system behavior and performance, scalability of the trade algorithm and the blockchain, smart contract execution costs, etc., are presented through numerical results by implementing and simulating the protocol in various scenarios. This work not only enhances local energy trading among EVs, encouraging efficient energy usage and reducing burden on the power grid, but also paves a way for future research in sustainable energy management.
The exploitation of natural gas resources to supply energy demands has resulted in the need to engineer pipelines and plants capable of handling extremely high pressures and throughputs. Consequently, more attention has been directed to evaluating the consequences of releases of material whether accidental or deliberate in nature. An important aspect of assessing the consequences of a release is an understanding of how gas disperses in the atmosphere over a wide range of release and atmospheric conditions. The most cost effective way of providing such information is through the development and use of reliable theoretical prediction methods. The need for some form of remote sensing device was identified. The various possibilities studied led to the conclusion that LIDAR (Light Detection And Ranging) offered the most suitable method. The system designed and built is described, and its recent use in monitoring operational ventings from a high pressure transmission system is discussed.
The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform
The integration of renewable energy sources into power grids necessitates solutions for grid support and stability during fluctuations in electricity generation and demand. Gravity energy storage systems (GESS) are emerging as a promising technology for managing the balance between energy supply and demand. However, their capacity to optimize energy flow and offer voltage and frequency regulation amid imbalances in generation and demand is less reported. This paper investigates the control of GESS for optimizing energy flow during voltage and frequency regulation. The study evaluates the regulation capabilities of GESS with different motor inertias during a Texas grid event: one with a high-speed, low-inertia motor and another with a low-speed, high-inertia motor. Results indicate that both GESS scenarios provide fast frequency response by converting potential energy into kinetic energy and vice versa, with a response time of 1.5 s from the frequency variation. This aligns with grid requirements for primary frequency response from traditional synchronous generators and motors with large inertia. Furthermore, a GESS based on a high-inertia motor may be able to operate over a broader range of frequency variations, whereas a low-inertia system may be limited by thermal constraints of the motor.
The integration of renewable energy sources into power grids necessitates solutions for grid support and stability during fluctuations in electricity generation and demand. Gravity energy storage systems (GESS) are emerging as a promising technology for managing the balance between energy supply and demand. However, their capacity to optimize energy flow and offer voltage and frequency regulation amid imbalances in generation and demand is less reported. This paper investigates the control of GESS for optimizing energy flow during voltage and frequency regulation. The study evaluates the regulation capabilities of GESS with different motor inertias during a Texas grid event: one with a high-speed, low-inertia motor and another with a low-speed, high-inertia motor. Results indicate that both GESS scenarios provide fast frequency response by converting potential energy into kinetic energy and vice versa, with a response time of 1.5 s from the frequency variation. This aligns with grid requirements for primary frequency response from traditional synchronous generators and motors with large inertia. Furthermore, a GESS based on a highinertia motor may be able to operate over a broader range of frequency variations, whereas a low-inertia system may be limited by thermal constraints of the motor.
The integration of renewable energy sources into power grids necessitates solutions for grid support and stability during fluctuations in electricity generation and demand. Gravity energy storage systems (GESS) are emerging as a promising technology for managing the balance between the energy supply and demand. However, their capacity to optimize energy flow and offer voltage and frequency regulation amid generation-demand imbalances is less reported. This paper investigates the control of GESS for optimizing energy flow during voltage and frequency regulation. The study evaluates the regulation capabilities of GESS with different motor inertias during a Texas grid event: one with a high-speed, low-inertia motor and another with a low-speed, high-inertia motor. Results indicate that both GESS systems provide fast frequency response by converting potential energy into kinetic energy and vice versa, with a response time of 1.5 seconds from the frequency variation. This aligns with grid requirements for primary frequency response from traditional synchronous generators and motors with large inertia. Furthermore, a GESS with a high-inertia motor may be able operate over a broader range of frequency variations whereas a low-inertia system may be limited by thermal constraints of the motor.
Latent heat thermal energy storage (LHTES) using phase change material (PCM) has attracted increased attention as a viable solution for overcoming the mismatch between energy supply and demand for renewable energy-based systems. PCM-embedded heat exchangers (PCM-HX) have the potential to significantly improve thermal performance due to high storage capacity and low temperature variation during the phase change process. Most models for simulating LHTES heat transfer use Computational Fluid Dynamics (CFD) simulations, which have high computational costs resulting from considering the complex and time-dependent physics relevant to PCM-HXs. In this paper, a Generalized Resistance Capacitance-based Model (GRCM) was developed to predict the thermal performance of arbitrary PCM-HXs in a computationally efficient manner without compromising modeling accuracy. The GRCM is exercised for three case studies: (i) verification for a single-slabbed finned PCM-HX, (ii) verification and validation for a copper foam/paraffin composite PCM-HX, and (iii) validation for a straight tube annular finned PCM-HX. The copper foam PCM-HX uses an electric heater at the top of HX, while the other two configurations utilize water as heat transfer fluid. For the single-slabbed finned PCM-HX melting case, the mean deviation in average PCM temperature predicted by the GRCM compared to the CFD model was between 0.56 – 0.73 K, with maximum temperature deviation of 2.68 K. For the HTF outlet temperature, the validation results showed that GRCM prediction matches very well with experimental data, with mean temperature deviation of 0.24 K during melting case, while for solidification case was 0.34 K. These results showcase the GRCM’s capability for accurately reproducing the thermal characteristics of PCM-HXs with considerably lower computational effort.
Powered By PRAS features the Probabilistic Resource Adequacy Suite (PRAS), an open-source, research-oriented collection of tools for analyzing the resource adequacy of bulk power systems. PRAS performs low-fidelity, high-speed simulations of multi-region power system operations, considering hundreds of thousands of years of unplanned resource outages to quantify the risk and potential nature of energy supply shortfalls in probabilistic terms.
Two projections of future hydrogen demand, based on the Ford technical fix and the Westinghouse nuclear electric economy energy supply and demand scenarios, are analyzed. It is suggested that hydrogen use will increase during the remainder of this century by at least a factor of five, and perhaps by a factor of twenty. Primary energy sources for producing hydrogen are discussed in terms of the transition from low to high demand for hydrogen.
Anticipated U.S. demands for non-renewable energy and mineral resources exceed domestic supplies essential for economic growth. For the long term changes necessary in the energy supply and demand gap, new technologies and substitute materials as well as legislation and socio-economic strategies are elaborated.
The integration of heat pumps with thermal energy storage (HP-TES) systems is gaining attention as a viable solution for managing peak building demand driven by immense cooling and heating loads. With growing reliance on renewable energy sources, thermal energy storage offers an excellent opportunity to mitigate mismatches in thermal load between energy supply and demand. The use of phase-change material (PCM) TES is especially promising, as PCMs offer significant latent energy storage capacity with smaller temperature glides in smaller volumes compared to other TES technologies. However, challenges arise because current HP-TES architectures can load-shift only cooling or heating, not both, requiring two systems and thus doubling cost, weight, and footprint. Furthermore, current research efforts lack specific tools and techniques to advance integrated systems from concept design to end-user application, focusing on only discharge performance. To address these challenges, this research proposes a dual-mode (heating and cooling) integrated HP-TES system that uses room-temperature PCM-TES as a high-temperature heat source in heating mode and a low-temperature heat sink in cooling mode, thereby reducing temperature lifts and compressor power. Design criteria for PCM-TES heat exchangers were developed, balancing thermal-hydraulic performance with practical constraints such as available building space and weight requirements along with PCM selection considerations such as shipping conditions, moisture exposure, and number of available cycles. A detailed transient model for HP-TES systems was developed to enable rapid annual performance assessments in any US climate zone.
The imperative for strong and rapid emissions reductions to mitigate global warming and enhance air quality necessitates a transition to net-zero emissions. This shift requires significant changes throughout the entire energy supply-demand ecosystems, tailored to various sectors. Transportation stands as the least-diversified energy sector and the largest source of U.S. GHG emissions. As the primary enabler for vehicle decarbonization when paired with clean electricity, electric vehicles (EVs) will play a pivotal role in the future. This talk summarizes current status of EV technologies and markets, future projections, and opportunities associated with a conversion to EV for all on-road vehicles. Moreover, EVs are poised to drive substantial growth in electricity demand and presents a unique opportunity to provide demand-side flexibility that is crucial for future renewable-dominated electricity systems. Smart integration of EVs can strengthen the grid, reducing costs and enhancing resilience.
The global shift towards renewable energy sources to mitigate fossil fuel dependency and meet carbon emission targets by 2050 has underscored the importance of innovative solutions to address energy supply-demand imbalances. Underground Hydrogen Storage (UHS) has emerged as a promising strategy to store excess renewable energy in subsurface formations for future retrieval and utilization. This report focuses on enhancing the site screening process for UHS facilities. By drawing on insights from prior research to identify key criteria influencing site suitability, our objective is to present a comprehensive set of sixteen specific criteria essential for refining the selection of UHS sites. These criteria cover various aspects such as reservoir performance, legal access, regulatory compliance, economic viability, public acceptance, and safety and security considerations. Our proposed methodology allows users to evaluate potential sites using binary responses, transitioning from isolated factors to broader considerations that facilitate a qualitative assessment of site suitability. This method enables comparative analysis and informed decision-making, supporting stakeholders in the site selection process. Our approach is designed as a guiding framework rather than a rigid template for site screening, emphasizing the importance of customizing approaches to individual circumstances. As UHS site development project evolves, adopting a comprehensive selection methodology that integrates holistic evaluations will be essential for ensuring efficient and effective site screening processes tailored to specific project needs.
The global shift towards renewable energy sources to mitigate fossil fuel dependency and meet carbon emission targets by 2050 has underscored the importance of innovative solutions to address energy supply-demand imbalances. Underground Hydrogen Storage (UHS) has emerged as a promising strategy to store excess renewable energy in subsurface formations for future retrieval and utilization. This report focuses on enhancing the site screening process for UHS facilities. By drawing on insights from prior research to identify key criteria influencing site suitability, our objective is to present a comprehensive set of sixteen specific criteria essential for refining the selection of UHS sites. These criteria cover various aspects such as reservoir performance, legal access, regulatory compliance, economic viability, public acceptance, and safety and security considerations. Our proposed methodology allows users to evaluate potential sites using binary responses, transitioning from isolated factors to broader considerations that facilitate a qualitative assessment of site suitability. This method enables comparative analysis and informed decision-making, supporting stakeholders in the site selection process. Our approach is designed as a guiding framework rather than a rigid template for site screening, emphasizing the importance of customizing approaches to individual circumstances. As UHS site development project evolves, adopting a comprehensive selection methodology that integrates holistic evaluations will be essential for ensuring efficient and effective site screening processes tailored to specific project needs.
The use of hydrogen as a synthetic fuel is considered. Processes for the production of hydrogen are described along with the present and future industrial uses of hydrogen as a fuel and as a chemical feedstock. Novel and unconventional hydrogen-production techniques are evaluated, with emphasis placed on thermochemical and electrolytic processes. Potential uses for hydrogen as a fuel in industrial and residential applications are identified and reviewed in the context of anticipated U.S. energy supplies and demands. A detailed plan for the period from 1975 to 1980 prepared for research on and development of hydrogen as an energy carrier is included.
This report presents the results of a study examining the value potential for geothermal energy storage (GES), a long-duration energy storage resource that stores thermal and/or geomechanical energy in the subsurface. GES could benefit the overall U.S. power system by temporally shifting electricity generation (supply-side) or meeting building heating and cooling load (demand-side). This report analyzes supply-side and demand-side opportunities independently because of differences in applications and models. Currently there is significant uncertainty about the development costs for GES, with only a limited number of demonstration plants for electric energy storage and building heating and cooling storage developments. In this report, we estimate the value of supply-side and demand-side GES to the bulk power system in the contiguous United States. Because of the significant uncertainty about GES development costs, this analysis does not consider GES deployment costs but instead focuses on the value of GES to the U.S. electricity system. The estimated values of GES provide reference points for economically competitive commercial cost targets. Supply-side GES is modeled as part of an enhanced geothermal system (EGS) generation plant in NREL's Regional Energy Deployment System (ReEDS) capacity expansion model (Ho et al. 2021). In contrast to conventional geothermal plants, which generate constant power, EGS plants have unique features that may allow for in-reservoir energy storage for flexible generation. Demand-side GES for heating and cooling, including seasonal hot and cold storage and short-duration heat pump storage, is incorporated into a price-taker model using Cambium electricity marginal cost projections. To establish an upper bound for the value of GES, analysis focused on favorable scenarios for storage with high generation from zero marginal cost, variable renewable energy resources. High penetrations of variable renewable energy generation can increase hourly electricity price variability, which increases the value of temporal energy arbitrage for storage technologies like GES.