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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 973 records · Page 54

EVALUATING THE COMPETITIVENESS OF ENERGY STORAGE FOR MITIGATING THE STOCHASTIC, VARIABLE ATTRIBUTES OF RENEWABLES ON THE GRID

Energy storage has recently attracted significant interest as an enabling technology for integrating stochastic, variable renewable power into the electric grid. To meet the renewable portfolio standards targets imposed by 29 U.S. states and the District of Columbia, electricity production from wind technology has increased significantly. At the same time, wind turbines, like many renewables, produce power in a manner that is stochastic, variable, and non-dispatchable. These attributes introduce challenges to generation scheduling and the provision of ancillary services. To study the impacts of the stochastic variability of wind on regional grid operation and the role that energy storage could play to mitigate these impacts, Pacific Northwest National Laboratory (PNNL) has developed a series of linked, complex techno-economic-environmental models to address these key questions: a. What are the future expanded balancing requirements necessary to accommodate enhanced wind turbine capacity, so as to meet the renewable portfolio standards in 2020? Specific analyses are conducted for the four North American Electric Reliability Corporation (NERC) western sub-regions. b. What are the most cost-effective technological solutions for providing either fast ramping generation or energy storage to serve these balancing requirements? PNNL applied a stochastic approach to assess the future, expanded balancing requirements for the four western sub-regions with high wind penetration in 2020. The estimated balancing requirements are quantified for four sub-regions: Arizona-New Mexico-Nevada (AZNMNV), California-Mexico (CAMC), Northwest Power Pool (NWPP), and Rocky Mountain Power Pool (RMPP). Model results indicate that the new balancing requirements will span a spectrum of frequencies, from minute-to-minute variability (intra-hour balancing) to those indicating cycles over several hours (inter-hour balancing). The sharp ramp rates in the intra-hour balancing are of significant concern to grid operators. Consequently, this study focuses on analyzing the intra-hour balancing needs. A detailed, life-cycle cost (LCC) modeling effort was used to assess the cost competitiveness of different technologies to address the future, intra-hour balancing requirements. Technological solutions considered include combustion turbines, sodium sulfur (NaS) batteries, lithium ion (Li-ion) batteries, pumped-hydro energy storage (PHES), compressed air energy storage (CAES), flywheels, redox flow batteries, and demand response (DR). Hybrid concepts are also evaluated. For each technology, distinct power and energy capacity requirements are estimated. LCC results indicate that the most cost competitive technologies include electrochemical energy storage and Na-S and Li-Ion. This finding is consistent among the four sub-regions and is generally applicable to other regions.

arbitrage↗

REopt: A Platform for Energy System Integration and Optimization: Preprint

REopt is NREL's energy planning platform offering concurrent, multi-technology integration and optimization capabilities to help clients meet their cost savings and energy performance goals. The REopt platform provides techno-economic decision-support analysis throughout the energy planning process, from agency-level screening and macro planning to project development to energy asset operation. REopt employs an integrated approach to optimizing a site?s energy costs by considering electricity and thermal consumption, resource availability, complex tariff structures including time-of-use, demand and sell-back rates, incentives, net-metering, and interconnection limits. Formulated as a mixed integer linear program, REopt recommends an optimally-sized mix of conventional and renewable energy, and energy storage technologies; estimates the net present value associated with implementing those technologies; and provides the cost-optimal dispatch strategy for operating them at maximum economic efficiency. The REopt platform can be customized to address a variety of energy optimization scenarios including policy, microgrid, and operational energy applications. This paper presents the REopt techno-economic model along with two examples of recently completed analysis projects.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

PHASE CHANGE MATERIAL FOR THERMAL ENERGY STORAGE IN BUILDINGS BASED ON SODIUM SULFATE DECAHYDRATE AND DISODIUM HYDROGEN PHOSPHATE DODECAHYDRATE

The worldwide increasing energy demand and 2050 net zero carbon target urge the globe to solve the energy challenge. Thermal Energy Storage (TES) has received significant attention in recent years as TES can be integrated into heating, ventilation, and air-conditioning systems where the energy would be stored during low-demand times and dispatched during high-demand times, resulting in controlling the peak load and improving energy savings. Material development is an integral part of TES. Salt hydrates are appealing due to cost-effectiveness, low- to no toxicity, and their high melting enthalpy, where energy is stored as latent heat. However, most salt hydrates are prone to incongruent melting (i.e., phase separation upon melting), which results in poor stability and large supercooling. In this study, we produced a highly stable novel energy storage material at a composition of 32 wt% sodium sulfate decahydrate, 52 wt% sodium phosphate dibasic dodecahydrate, 12 wt% milled expanded graphite, and 4 wt% borax. The material has a melting temperature of 28°C and an energy storage capacity of 167 kJ/kg with a supercooling of less than 3°C. The system showed no loss in energy storage performance after 150 cycles. The findings suggest that the novel energy storage material developed in this might be utilized in building heating and cooling applications.

Turnaoglu, Tugba↗

System and Component Development of Particle-Based Pumped Thermal Energy Storage

Reliable power supply from variable renewable resources requires energy storage at various scales to overcome resource intermittency. Long-duration energy storage (LDES, 10-100 hours) can improve dispatchability and grid reliability with increasing levels of renewable power supply. Thermal energy storage (TES) has siting flexibility and the ability to store a large capacity of energy, and thus has the potential to meet the LDES need and provide charging and discharging durations beyond the economic capacity of conventional batteries. TES technology has evolved from concentrating solar thermal power (CSP) generation and is recognized as an economic large-scale energy storage method. A standalone electric-thermal energy storage system supporting renewable integration of wind and solar power without CSP solar field can firm renewable generation and boost overall grid resilience and security.

concentrating solar thermal power↗

LIQUID AIR COMBINED CYCLE

Hybrid integration of thermal energy storage with gas turbines can provide compact, cost-effective, long-duration energy storage while reducing the fuel consumption of dispatchable resources needed for the reliability of renewable dominant electric grids. The Liquid Air Combined Cycle™ (LACC) is a hybrid energy storage system using cryogenic liquid air as an energy storage medium and gas turbine exhaust heat to extract stored energy. The storage tank is charged using liquefaction processes employing electric motor-driven compressors to pressurize the air, heat exchangers to reject heat of compression, and expanders to reduce the temperature and liquefy the air. Proven cryogenic refrigeration processes can be selected based on capital cost (per kg/s of liquid air produced), efficiency (kJ per kg of air produced), and operating factors including startup speed and load following capability. This paper presents results of studies undertaken for the U.S. Department of Energy to evaluate cost and performance tradeoffs for charge and discharge cycle components, optimize charge and discharge cycles, and assess the techno-economic potential of LACC technology.

Conlon, William↗

ORGANIC RANKINE CYCLE TURBINE AND HEAT EXCHANGER SIZING FOR LIQUID AIR COMBINED CYCLE

Cryogenic energy storage offers several opportunities to design turbomachinery and other equipment for novel cycles. This paper presents the design and analysis of turbomachinery and heat exchangers for an Organic Rankine Cycle (ORC) subsystem for a hybrid energy storage concept. The Liquid Air Combined Cycle is an energy storage system that stores air at cryogenic conditions at times with high variable renewable energy to be dispatched along with a gas turbine to recover the exhaust heat. In order to re-vaporize the air, the liquid air is coupled with an ORC as an additional bottoming cycle. The ORC turbine is expected to expand the fluid with a pressure ratio of nearly 30 and a flow rate of approximately 45 kg/s. Sizing calculations for both a radial and axial turbine solution were performed over a range of speeds and stages to determine the optimal design point. The results show that either an axial (8- or 9-stage) or radial (four stages at two shaft speeds) turbine are capable of handling the pressure ratios. Further trades of the two configurations would be required to determine the best option. The ORC system also incorporates five heat exchangers to distribute heat, vaporize the liquid air, or recover exhaust heat from the gas turbine. Three heat exchangers were analyzed to understand the size of heat exchangers and pressure drop for the overall system. Different types of heat exchangers were explored for the different purposes, including plate-fin heat exchangers, gasketed plate heat exchangers and shell-in-tube heat exchangers. It was determined that the ORC recuperator, liquid-air vaporizer, and vaporized air pre-heater would be counter-flow heat exchangers using a gasketed plate design. Keywords: Energy Storage, Liquid Air Energy Storage, Organic Rankine Cycle

Pryor, Owen↗

Decommissioning of magnox Ltd fuel cooling pond facilities in the UK

Magnox reactors were the first generation of nuclear power stations built in the UK; ten sites in total, of which, nine had wet fuel routes with cooling ponds. Five ponds are currently in a decommissioning phase; this paper will focus primarily on Hunterston-A (HNA) Site and the central programme of work which governs its management. During its operation, the Cartridge Cooling Pond at HNA was used to receive the spent fuel discharged from the Site's two reactors, it was then stored for cooling purposes prior to dispatch off site. The current decommissioning phase focusses on draining the 6500 m{sup 3} pond. Due to the Site's limited caesium removal facilities, a stand-alone effluent treatment plant was constructed to improve abatement and reduce the pond activity from 200 to 0.7 Bq/ml (β). This was necessary due to increased environmental standards introduced since the site had ceased generation ten years previously. Early characterisation and experience from other sites concluded that if the pond were to be drained without any treatment to the walls, doses to the Operators, during subsequent decommissioning works, would routinely be in excess of 1 mSv.hr{sup -1}(γ). An opportunity was realised within the Ponds Programme that if the surface layer of the pond walls were to be removed during drain-down, ambient dose rates would be reduced by a factor of 10; this would allow for more cost-effective decommissioning options in the future. Ultrahigh pressure water jetting was tested and proved to yield a ∼95% total-activity reduction on treated surfaces. Challenges were overcome in providing safe and secure access to Decommissioning Operators to perform this operation by means of floating platforms on the surface of the pond. As strategies to clear facilities to exemption levels are becoming both cost prohibitive and not reasonably practicable, work is now underway in the Programme to determine the optimum condition for entry into long-term quiescent storage, prior to final demolition. This paper will discuss the strategy and techniques which led to Magnox Ltd ponds to be of national and international interest to the nuclear community. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Ground Level Integrated Diverse Energy Storage (GLIDES) Cost Analysis

With the increasing penetration of renewable energy, the need for advanced flexible/scalable energy storage technologies with high round-trip efficiency (RTE) and high energy density has become critical. In this paper, a techno-economic model of a novel energy storage technology developed by the Oak Ridge National Laboratory (ORNL) is presented and used to estimate the technology’s capital cost. Ground-Level Integrated Diverse Energy Storage (GLIDES) is an energy storage technology with high efficiency which can store energy via input of electricity and heat and supply dispatchable electricity. GLIDES stores energy by compressing and expanding a gas using a liquid piston. GLIDES performance has been extensively studied analytically and experimentally. This study aims to develop a comprehensive combined performance and cost modeling environment. With the desired system storage capacity kilowattage, storage time (hours), and an initial RTE guess as inputs, the model optimizes the selection of system components to minimize the capital cost. The techno-economic model described in this paper can provide preliminary cost estimates and corresponding performance for various system sizes and storage times.

Kassaee, Saiid↗

Photovoltaics at multi-terawatt scale: Waiting is not an option

We report a major renewable-energy milestone occurred in 2022: Photovoltaics (PV) exceeded a global installed capacity of 1 TW dc . But despite considerable growth and cost reduction over time, PV is still a small part of global electricity generation (4 to 5% for 2022), and the window is increasingly closing to take action at scale to cut greenhouse gas (GHG) emissions while meeting global energy needs for the future. PV is one of very few options that can be dispatched relatively quickly, but discussions of TW-scale growth at the global level may not be clearly communicating the needed size and speed for renewable-energy installation. A major global risk would be to make poor assumptions or mistakes in modeling and promoting the required PV deployment and industry growth and then realize by 2035 that we were profoundly wrong on the low side and need to ramp up manufacturing and deployment to unrealistic or unsustainable levels.

14 SOLAR ENERGY↗

Coordination of Behind-the-Meter Energy Storage and Building Loads: Optimization with Deep Learning Models*

With the increasing penetration of renewable energy systems and energy storage systems in buildings, it is critical to optimize system operation. In this paper, we develop an optimization strategy to minimize the operation cost as well as maintain indoor thermal comfort, for a building integrated with battery and PV. A Recurrent Neural Network (RNN) is used to predict building thermal load and zone temperatures. A black-box optimization algorithm known as nonlinear optimization by mesh adaptive direct search (NOMADS) is employed in simulation to provide look-ahead optimal battery dispatch and zone temperature set-point schedules so that the operation cost is minimized. Field data collected from a medium sized office building at Pacific Northwest National Laboratory (PNNL) integrated with Photovoltaic (PV) system model and battery storage system model is used to demonstrate the proposed methodology. Compared with rule based methods, the optimization strategy obtained a lower cost of operation while satisfying comfort constraints.

Chen, Yimin↗

Thread Batching for High-performance Energy-efficient GPU Memory Design

Massive multi-threading in GPU imposes tremendous pressure on memory subsystems. Due to rapid growth in thread-level parallelism of GPU and slowly improved peak memory bandwidth, memory becomes a bottleneck of GPU’s performance and energy efficiency. In this article, we propose an integrated architectural scheme to optimize the memory accesses and therefore boost the performance and energy efficiency of GPU. First, we propose a thread batch enabled memory partitioning (TEMP) to improve GPU memory access parallelism. In particular, TEMP groups multiple thread blocks that share the same set of pages into a thread batch and applies a page coloring mechanism to bound each stream multiprocessor (SM) to the dedicated memory banks. After that, TEMP dispatches the thread batch to an SM to ensure high-parallel memory-access streaming from the different thread blocks. Second, a thread batch-aware scheduling (TBAS) scheme is introduced to improve the GPU memory access locality and to reduce the contention on memory controllers and interconnection networks. Experimental results show that the integration of TEMP and TBAS can achieve up to 10.3% performance improvement and 11.3% DRAM energy reduction across diverse GPU applications. We also evaluate the performance interference of the mixed CPU+GPU workloads when they are run on a heterogeneous system that employs our proposed schemes. Our results show that a simple solution can effectively ensure the efficient execution of both GPU and CPU applications.

Computer Science↗

A Sparse Distributed Gigascale Resolution Material Point Method

In this paper, we present a four-layer distributed simulation system and its adaptation to the Material Point Method (MPM). The system is built upon a performance portable C++ programming model targeting major High-Performance-Computing (HPC) platforms. A key ingredient of our system is a hierarchical block-tile-cell sparse grid data structure that is distributable to an arbitrary number of Message Passing Interface (MPI) ranks. We additionally propose strategies for efficient dynamic load balance optimization to maximize the efficiency of MPI tasks. Our simulation pipeline can easily switch among backend programming models, including OpenMP and CUDA, and can be effortlessly dispatched onto supercomputers and the cloud. Finally, we construct benchmark experiments and ablation studies on supercomputers and consumer workstations in a local network to evaluate the scalability and load balancing criteria. We demonstrate massively parallel, highly scalable, and gigascale resolution MPM simulations of up to 1.01 billion particles for less than 323.25 seconds per frame with 8 OpenSSH-connected workstations.

97 MATHEMATICS AND COMPUTING↗

Mobility-On-Demand Transportation: A System for Microtransit and Paratransit Operations

New rideshare and shared-mobility services have transformed urban mobility in recent years. Therefore, transit agencies are looking for ways to adapt to this rapidly changing environment. In this space, ridepooling has the potential to improve efficiency and reduce costs by allowing users to share rides in high-capacity vehicles and vans. Most transit agencies already operate various ridepooling services including microtransit and paratransit. However, the objectives and constraints for implementing these services vary greatly between agencies. This brings multiple challenges. First, off-the-shelf ridepooling formulations must be adapted for real-world conditions and constraints. Second, the lack of modular and reusable software makes it hard to implement and evaluate new ridepooling algorithms and approaches in real-world settings. Therefore, we propose an on-demand transportation scheduling software for microtransit and paratransit services. This software is aimed at transit agencies looking to incorporate state-of-the-art rideshare and ridepooling algorithms in their everyday operations. We provide management software for dispatchers and mobile applications for drivers and users. Lastly, we discuss the challenges in adapting state-of-the-art methods to real-world operations.

Wilbur, Michael↗

A Study of Performance Portability of Low-bit Fused Matrix-Vector Multiplication Kernels in SYCL

Understanding the causes of performance gaps between a portable programming model and a vendor-specific programming model is important for improving performance portability. This paper studies performance portability of low-bit fused general matrix-vector multiplication kernels in SYCL on vendors’ graphics processing units (GPUs). This work introduces the use case, explains the kernel implementations in detail, evaluates the performance of the CUDA, HIP, and SYCL kernels on datacenter, desktop, and laptop GPUs, and investigates the causes of performance gaps. The results show that loop unrolling, kernel dispatch overhead, and sum reduction contribute to the gaps.

Jin, Zheming [ORNL] (ORCID:000000027197780X)↗

Hydrogen at Scale (H 2 @Scale): Key to a Clean, Economic, and Sustainable Energy System

Much of hydrogen's value to the energy-system lies in its ability to be cleanly and efficiently converted between chemical and electrical energy, while also possessing the high energy density and long-term storage potential of chemical bonds. For these reasons, hydrogen's importance is expected to grow substantially in the coming decades, providing cross-sector and cross-temporal impact through clean, efficient processes. Many of these processes are electrochemical in nature, such as electrolysis of water and electricity production using fuel cells. Hydrogen also offers significant flexibility in how it can integrate into the energy system as a function of scale (from W to GWs), source (fossil fuels, nuclear, biomass, solar, wind, thermal), and end use (grid, buildings, industry, transportation). This flexibility, along with the ability to be used as a dispatchable load or power generation source, allows hydrogen and hydrogen-based processes to couple with the overall energy system in an integrated or hybridized fashion, offering dramatic system optimization potential. However, achieving the scale necessary to have impact - the vision 'Hydrogen at Scale' (H2@Scale) still has research challenges, many of which center around electrochemistry.

08 HYDROGEN↗

Kokkos Array

The Kokkos Array library implements shared-memory array data structures and parallel task dispatch interfaces for data-parallel computational kernels that are performance-portable to multicore-CPU and manycore-accelerator (e.g., GPGPU) devices.

Edwards Daniel Sunderland, HaroldCarter↗

Multi Infrastructure Control and Optimization Toolkit, Resilient Design Module (MICOT-RDT), version 2.X

MICOT is a tool for optimizing and controlling infrastructure systems. In includes modules for optimizing the operations of an infrastructure structure (for example optimal dispatch), designing infrastructure systems, restoring infrastructures systems, resiliency, preparing for natural disasters, interdicting networks, state estimation, sensor placement, and simulation of infrastructure systems. It implements algorithms developed at LANL that have been published in the academic community. This is a release of the of resilient design module of the MICOT.

Bent, Russell↗

GHOST (Grid Hardware Open Source Testbed) [SWR-18-32]

The software was developed for the purpose of Microgrid Controller Procurement where multiple Microgrid Controller vendors were competing to prove the best performance. Each microgrid controller was connected to Real-Time Simulator (Opal-RT) where the Real-Time model of microgrid was simulated. Microgrid controllers were able to control most of the assets in the model. To be able to fairly compare controller's performance each controller was evaluated using exactly the same model, with the same initial conditions and exactly the same test sequence. The microgrid evaluation test sequence lasted 100 minutes and consist of various grid disturbances to which a microgrid controller must respond. The microgrid and power system will experience multiple types of disturbances while performing dispatch functions. Many functions are tested in grid-connected and islanded modes such as unexpended failures of generators, energy storage trip events, and large load fluctuations. The test sequence focuses on fault scenarios that cause the highest short-circuit fault current contribution; force a swing bus or generator capable of being a swing bus offline; cause the most reconfigurations; and cause conflicting objectives for the microgrid controller. During the test sequence execution multiple datapoints are being recorded and stored. During data postprocessing key performance parameters are extracted allowing quantitative comparison of performance on multiple aspects including: resiliency, fuel utilization, grid interconnection, ancillary services and power quality and eventually after summing all key performance parameters by comparing the overall result. To be able to perform such testing multiple tools had to be developed included in this repository including: - Real time model of microgrid (Urban-Banshee, Remote-smaller model) - Test sequence configuration tools - Test execution real-time scripts - Post processing scripts - Human Machine Interface software

Koralewicz, Przemyslaw↗