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At least 325 records · Page 18

A higher-order finite-element implementation of the nonlinear Fokker–Planck collision operator for charged particle collisions in a low density plasma

Collisions between particles in a low density plasma are described by the Fokker–Planck collision operator. In applications, this nonlinear integro-differential operator is often approximated by linearised or ad-hoc model operators due to computational cost and complexity. In this work, we present an implementation of the nonlinear Fokker–Planck collision operator written in terms of Rosenbluth potentials in the Rosenbluth–MacDonald–Judd (RMJ) form. The Rosenbluth potentials may be obtained either by direct integration or by solving partial differential equations (PDEs) similar to Poisson's equation: we optimise for performance and scalability by using sparse matrices to solve the relevant PDEs. We represent the distribution function using a tensor-product continuous-Galerkin finite-element representation and we derive and describe the implementation of the weak form of the collision operator. We present tests demonstrating a successful implementation using an explicit time integrator and we comment on the speed and accuracy of the operator. Finally, we speculate on the potential for applications in the current and next generation of kinetic plasma models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Selective Ligand Modification of Cobalt Porphyrins for Carbon Dioxide Electrolysis: Generation of a Renewable H2/CO Feedstock for Downstream Catalytic Hydrogenation

Catalytic hydrogenation is an attractive approach to produce green fuels and chemicals. The building blocks for these processes may be effectively produced from renewable power via direct electrochemical reduction of carbon dioxide in an aqueous media. For the first time, the impact of increasing the local proton concentration of cobalt porphyrin was examined by synthesizing new cobalt porphyrins 2, Co(o-OCH3)TPP and cobalt porphyrin 3, Co(o-OH)TPP. Cobalt porphyrins coated on carbon paper converted carbon dioxide and water into a mixture of hydrogen and carbon monoxide in an aqueous electrolyte at near neutral pH. Increasing the local proton availability of the commercial cobalt porphyrin 1, accelerates hydrogen generation under heterogeneous conditions across the range of potentials tested (-0.85 to -1.5 V vs. Ag/AgCl) and demonstrates high Faradaic efficiencies (ca. 90%) at low over-potentials (ca. 540 mV). The culmination of this work can help identify key parameters that facilitate generation of sustainable reagents for catalytic hydrogenation under practical and scalable conditions.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

A generative machine learning model for designing metal hydrides applied to hydrogen storage

Developing new metal hydrides is a critical step toward efficient hydrogen storage in carbon-neutral energy systems. However, existing materials databases, such as the Materials Project, contain a limited number of well-characterized hydrides, which constrains the discovery of optimal candidates. This work presents a framework that integrates causal discovery with a lightweight generative machine learning model to generate novel metal hydride candidates that may not exist in current databases. Using a dataset of 450 samples (270 training, 90 validation, and 90 testing), the model generates 1000 candidates. After ranking and filtering, six previously unreported chemical formulas and crystal structures are identified, four of which are validated by density functional theory simulations and show strong potential for future experimental investigation. Overall, the proposed framework provides a scalable and time-efficient approach for expanding hydrogen storage datasets and accelerating materials discovery.

generative model↗

Red-Light-Driven Biophotochemical Diode Based on a Microorganism–Silicon Nanowire Interface for Stable and Efficient Bias-Free CO 2 Reduction

Artificial photosynthesis offers a promising route for sustainable liquid fuel and feedstock production, yet integrating efficient CO 2 reduction catalysts with light-harvesting systems remains challenging. Here, in this study, we present a biophotochemical diode that couples microorganism-driven CO 2 reduction with glycerol oxidation, enabled by silicon nanowire photoelectrodes under varying red-light intensities. Tuning the biotic-abiotic interface─by increasing biocatalyst loading and adjusting the catholyte pH to mitigate local alkalization─significantly improves performance and stability. The enhanced-loading biocathode maintains a high faradaic efficiency across a wide potential range, even under elevated light intensities. At 60 mW/cm 2 , the system achieves a bias-free current density of 3.5 mA/cm 2 . Long-term stability testing at 40 mW/cm 2 demonstrates stable operation for over 100 h. The photoanode generates valuable C 3 products, primarily glycerate and lactate, enhancing the economic viability. This work showcases the importance of microenvironmental control at the biotic-abiotic interface and establishes a scalable platform for light-driven CO 2 reduction using earth-abundant silicon.

Artificial Photosynthesis↗

Assessment of Blocking Contacts in Suppressing Polarization Effects in CsPbBr 3 Perovskite Detectors

The CsPbBr 3 perovskite has garnered significant attention as a room-temperature semiconductor for hard radiation detection due to straightforward synthesis, scalable crystal growth, low cost, and excellent energy resolution. However, despite these advantages, at ambient temperature, CsPbBr 3 devices may experience performance deterioration and irreversible failure due to “polarization” induced by electromigration of ions to electrical connections on the device. In this study, we tested several contact materials and their optimization deposition techniques to assess the stability of high-performance CsPbBr 3 γ-ray detectors. Metals, with low work functions (Ti, In, Sn, Sb, Pb, Bi, Al, Au, and TiC) and high-work-function (Au or Pt) contacts, were used to form different Schottky junctions using vacuum thermal evaporation, electron-beam evaporation, and sputtering methods. These detectors were tested in intermittent and continuous modes to assess their stability. Among the tested detectors, the Bi/CLB/Pt electrode configuration demonstrated superior stability, operating effectively for 11 months under periodic testing and 16 days under continuous testing. In contrast, other configurations functioned only for a few months under intermittent conditions. Upon incorporating a ~40-nm-thick TiC passivation layer on the anode side (Bi/TiC/CLB/Pt), the CLB device operated continuously for 36 days without degradation. In many cases, the failure mode of the devices was due to the degradation of the anode. Here, the chemical changes in the fresh and deteriorated anodes were characterized using scanning electron microscopy and energydispersive X-ray spectroscopy

CsPbBr3 perovskite↗

A State-Space Model of an Inverter-Based Microgrid for Multivariable Feedback Control Analysis and Design

In this work, a synchronous model for grid-connected and islanded microgrids is presented. The grid-connected model is based on the premise that the reference frame is synchronized with the AC bus. The quadrature component of the AC bus voltage can be cancelled, which allows to express output power as a linear equation for nominal values in the AC bus amplitude voltage. The model for the islanded microgrid is developed by integrating all the inverter dynamics using a state-space model for the load currents. This model is presented in a comprehensive way such that it could be scalable to any number of inverter-based generators using inductor–capacitor–inductor (LCL) output filters. The use of these models allows designers to assess microgrid stability and robustness using modern control methods such as eigenvalue analysis and singular value diagrams. Both models were tested and validated in an experimental setup to demonstrate their accuracy in describing microgrid dynamics. In addition, three scenarios are presented: non-controlled model, Linear-Quadratic Integrator (LQI) power control, and Power-Voltage (PQ/Vdq) droop–boost controller. Experimental results demonstrate the effectiveness of the control strategies and the accuracy of the models to describe microgrid dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advanced blade-shaped thermal energy storage device: Development and application

Thermal energy storage (TES) using phase change materials (PCMs) is a promising approach for capturing and reusing excess thermal energy, yet widespread adoption is limited by low thermal conductivity, bulky configurations, and inadequate scalability. Here, this study presents a modular, blade-shaped TES prototype designed to address these challenges. The device integrates a lightweight aluminum shell, an embedded serpentine coil for active or passive heat exchange, and a cost-effective corrugated metal mesh for enhanced PCM thermal conductivity. With thickness-to-length and thickness-to-width ratios of 0.03 and 0.08, respectively, the blade-shaped TES achieves a compact, modular form factor suitable for space-constrained applications. Experimental testing demonstrated the efficient charge and discharge behavior of blade-shaped TES, capturing PCM superheating, phase-change transitions, and subcooling dynamics, with charging and discharging efficiencies of 94.9% and 94.6%, respectively. Also, the system can potentially achieve higher energy density than that of conventional TES designs. When integrated into a household refrigerator during the study, three blade-shaped TES modules successfully shifted 100% of peak-time compressor operation to off-peak hours, reducing energy consumption while maintaining more stable compartment temperatures. The blade-shaped TES's thin geometry, modularity, and enhanced thermal performance support scalable deployment across residential, commercial, and industrial applications, providing a versatile, cost-effective solution for high-efficiency, demand-flexible thermal energy management.

Blade-shaped↗

A Scalable & Non-Destructive Characterization Strategy to Study Semiconductor/Dielectric Interfaces and Predict Wafer-Level Device Performance

The defect density present at the dielectric-semiconductor interface in an MOS structure directly influences the channel carrier characteristics in semiconductor devices, especially in wide bandgap material systems used in power devices. While these trap defects are typically quantified through electrical characterization of MOS-capacitor test structures, this treatment offers very little insight into the physical nature of interface defects. Such shortcomings demand a physical characterization strategy to guide fabrication optimization. X-ray photoelectron spectroscopy (XPS) is suggested as a viable technique to determine chemical data for dielectric interfaces formed using atomic layer deposition (ALD) on GaN substrates. Previously, 1-D XPS characterization has confirmed the presence of a Ga x O y interlayer between ALD dielectrics and the GaN substrate. In this work, XPS data is serially collected to form 2-D images of an ALD-Al 2 O 3 /GaN interface as a proof-of-concept experiment for in-situ XPS quality monitoring during ALD processing. The information provided by this work reveals some of the challenges for incorporating XPS characterization as an in-situ strategy during fabrication of GaN-based devices. Separately, electrical mapping of a 2-D array of ALD-Al 2 O 3 /GaN MOS-capacitor devices provide a means to quantify the spatial variations in interface quality across a single wafer. Physical characterization techniques, such as time-of-flight secondary ion mass spectroscopy, provide additional chemical information about the Al 2 O 3 /Ga x O y /GaN structure that complement the electrical mapping results. This analysis shows that a higher Ga x O y content correlates with higher interface state defects for trap energies deep in the band gap.

42 ENGINEERING↗

Adaptive finite differencing in high accuracy electronic structure calculations

Abstract A multi-order Adaptive Finite Differencing (AFD) method is developed for the kinetic energy operator in real-space, grid-based electronic structure codes. It uses atomic pseudo orbitals produced by the corresponding pseudopotential codes to optimize the standard finite difference (SFD) operators for improved precision. Results are presented for a variety of test systems and Bravais lattice types, including the well-known Δ test for 71 elements in the periodic table, the Mott insulator NiO, and borax decahydrate, which contains covalent, ionic, and hydrogen bonds. The tests show that an 8th-order AFD operator leads to the same average Δ value as that achieved by plane-wave codes and is typically far more accurate and has a much lower computational cost than a 12th-order SFD operator. The scalability of real-space electronic calculations is demonstrated for a 2016-atom NiO cell, for which the computational time decreases nearly linearly when scaled from 18 to 144 CPU-GPU nodes.

Briggs, E. L. (ORCID:0000000343983492)↗

Scaling-Up and Roll-to-Roll Processing if Highly Conductive Sulfide Solid-State Electrolytes (CRADA 510)

This project aims to identify and address key technical barriers in scale-up synthesis and roll-to-roll processing of highly conductive solid-state electrolytes (SSEs) by leveraging PNNL’s patent pending SSEs, Ampcera Inc.’s environmentally friendly manufacturing capability, and UW’s rollto-roll processing. The ultimate goals are 1) development of novel sulfide SSEs with room temperature Li+ conductivity > 5 mS/cm and Li/SSE interfacial resistance <5 Ωcm2, 2) scalable production of sulfide SSEs at 1 metric ton/year, and 3) a high throughput roll-to-roll processing of highly conductive (>1 mS/cm) and ultra-thin solid film (10-100 μm). The materials and the solid film achieved in the project will be tested at practical conditions and validated in a realistic pouch cell format with achievable energy > 300 Wh/Kg.

36 MATERIALS SCIENCE↗

In-situ Photophysical Monitors and Corrective Algorithms for Photovoltaic Film Deposition and Rapid Thermal Processing in Scalable Roll-to-Roll Manufacturing

This project evaluated three photophysics-based approaches for in situ process monitoring of the scalable deposition of perovskite photovoltaic films. Based on stakeholder input and the results of laboratory trials and literature analysis, two techniques, angle resolved elastic light scattering (ARLS) and time-resolved photoluminescence (TRPL) were prototyped and demonstrated with a mixture of simulation, offline and online tests. Also, a hybrid gas flow and humidity control enclosure was constructed and demonstrated to stabilize the ambient conditions around the slot die deposition process and were demonstrated to meet the target humidity control in situ. Due in part to a delayed start and COVID-related lab restrictions and personnel changes, some of the milestones were not met. In spite of these challenges, however, both techniques were prototyped through several iterations and demonstrated significant promise for rapid in line perovskite characterization within the targeted characterization time windows and these techniques are under further development for use in DE-FOA000235:2357-1586. The TRPL system was fully mounted and demonstrated on the scaled slot die roll to roll and sheet coating systems at the Washington Clean Energy Testbeds (WCET). Motivated by significant internal and stakeholder interest, the successful prototyping achieved here, the ongoing need for in-situ characterization for the scale-up of perovskite manufacturing, and the benefits of in situ photophysical characterization for future funded process development research, we are continuing with the principle aims of the project to develop effect in situ photophysical probes for fast analysis of the optoelectronic and structural quality of sheet based and roll to roll process perovskites. TRPLS and ARLS probes proposed in the project are to be completed with external support from the Washington Research Foundation at the WCET. We are currently actively engaged in the acquisition of components and plan to complete and test the probes within three months. It is our intention that these probes will then be used in ongoing perovskite development with our research and commercialization partners including First Solar and other member of the US MAP consortium in future funded development work.

14 SOLAR ENERGY↗

A Smart and Flexible Microgrid with a Low-cost Scalable Open-source Controller (Final Report)

This report contains information regarding the activities carried out in the project "A Smart and Flexible Microgrid with a Low-cost Scalable Open-source Controller. The project aims at developing a community-based flexible microgrid (FMG) with smart grid features, including multiple utility feeders and dynamic boundaries that utilize intelligent switches and ultra-high-speed communication links already in a smart grid. The project also aims at developing a corresponding controller for such an FMG with low cost and high scalability. With distributed renewable energy resources (DERs) and the intelligent microgrid controller, the FMG will achieve aggressive emission reduction, increased energy use efficiency, and reliability improvement goals. The FMG and its controller design will be scalable for different geographic areas, load sizes, distributed generation source number and types, and even multiple MGs within a distribution electric power system. In order to achieve these project objectives, three main development tasks were carried out: FMG design, FMG controller development, and FMG controller testing. The fourth task was technology to market.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems

Simulation of multiphase flow in the subsurface is well-known to be computationally challenging. While there have been many studies that have explored approaches to overcoming these challenges, they often utilize relatively simple case studies. In this paper, we focus on the unique numerical challenges posed by modeling large-scale engineered subsurface systems, characterized by discrete features embedded in a heterogeneous natural subsurface setting. The man-made features such as shafts, tunnels, and barriers often cause multiple challenges in modeling the domain for multiphase porous media flow. This flow scenario can have a wide range of applications such as nuclear waste repositories, enhanced recovery of a petroleum reservoir, geothermal engineering, and carbon sequestration. An example of these severe numerical challenges is the case of performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the only operating deep geological repository in the US, which simulates extreme material properties of bedded salt rock formation and extreme contrast due to open excavation next to the formation. The models have extremes not only of permeability and porosity but also of the constitutive models needed for multiphase flow; additionally, they have process models like salt creep closure reducing porosity over time, fracturing in clay and anhydrite interbeds of the bedded salt, gas generation from the waste materials, and unintentional human borehole intrusions in some scenarios. Numerical simulations require the solution of coupled systems of nonlinear PDEs; in our work, we use the open-source simulator PFLOTRAN which is based on Finite Volume discretization. The solution of the nonlinear equations requires use of the Newton-Raphson iteration at each time step, which entails the solution of the linearized Jacobian system at each iteration. The effects of all the processes (i.e., large number of unknowns, highly nonlinear constitutive relations, large contrasts in material properties in short distances) lead to an ill-conditioned Jacobian matrix that severely challenges traditional linear solver, i.e., stabilized biconjugate gradient with block Jacobi incomplete LU preconditioner (BCGS-ILU) leading to non-convergence for traditional Newton-Raphson nonlinear solver causing unacceptably long computation time for each model. This paper presents linear solvers such as constrained pressure residual (CPR) two-stage preconditioner with alternate-block-factorization (ABF) and quasi- implicit pressure and explicit saturation (QIMPES) decouplers and flexible generalized residual solver (FGMRES). The new general-purpose nonlinear solver, Newton trust-region dogleg Cauchy (NTRDC), is also introduced to resolve extreme nonlinearities in the models. We demonstrate the effectiveness of each method relative to the default BCGS-Newton solver. The two best cases had nearly 50 times speed-up and achieved completion of a simulation in 14 hours that never completed due to non-convergence with the default solver. We also investigate the strong scalability of each method and discuss some of the deficiencies found for Block Jacobi preconditioner using parallel domain decomposition, and node packing effects of modern processor architecture.

Preconditioner, Nonlinear, Porous media, Multiphas↗

Self-Heating Conductive Ceramic Composites for High Temperature Thermal Energy Storage

The absence of affordable and deployable large-scale energy storage poses a major barrier to providing zero-emission energy on demand for societal decarbonization. High temperature thermal energy storage is one promising option with low cost and high scalability, but it is hindered by the inherent complexity of simultaneously satisfying all of the material requirements. Here we design a class of ceramic–carbon composites based on co-optimizing mechanical, electrical, and thermal properties. Further, these composites demonstrate stability in soak-and-hold tests and direct self-heating up to 1,936 °C and 750 thermal cycles from 500 to 1,630 °C without degradation. This thermal performance derives from their composition and microstructural design as verified by in situ high-temperature transmission electron microscopy and X-ray diffraction. They offer both higher energy density and lower cost than conventional storage technologies with a projected system Levelized Cost of Storage below the U.S. Department of Energy’s 2030 target 5 ¢/kWh (electric).

25 ENERGY STORAGE↗

NRC Multiphysics Analysis Capability Deployment FY2020: Part 3

This report details progress and activities of Idaho National Laboratory (INL) on the Nuclear Regulatory Commission (NRC) project “Development and Modeling Sup- port for Advanced Non-Light Water Reactors.” The tasks completed for this report are: Task2c: Explicit modeling of pebble transient temperature response. In this simulation, the 400 MWth Pebble-Bed Modular Reactor (PBMR) design, PBMR- 400, experiences a 20-second power ramp from 100% to 150% power. This is followed by a similar reduction in the power back to 100%. Several multiscale pebble coupling approaches are tested with one pebble per mesh element in the active core region. The results show good conservation behavior and the stability of the coupling.; Extended scope part 1: An assessment of the computational efficiency of the Discontinuous Finite Element Method (DFEM) heat transfer solver shows good scalability. The DFEM solver is a factor of 4 more expensive in solution time than the Finite Element Method (FEM) solver for heat transfer problems due to the increased number of degrees of freedom. Nonetheless, the DFEM approach provides the user with the flexibility to model gap heat transfer problems.; Extended scope part 2: The GapHeatTransferInterfaceMaterial was improved to give the user increased flexibility with the modeling of heat transfer through gaps with the DFEM solver. A number of gap parameters can now be coupled both through functions and variables.; Extended scope part 3: Demonstration of how the gap width between hexagonal fuel cells can be calculated during a heat-up transient and used in the GapHeatTransferInterface model. A full-domain DFEM model with gap expansion is coupled to a SubApp that models the thermal expansion of the base plate. The results show the expected physical behavior, although have not been fully bench-marked at this point in time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multiscale characterization of phase change materials for building thermal energy storage applications

Phase change materials (PCMs) store and release large amounts of thermal energy because of their high latent energy storage capacity. However, long-term cyclic stability, supercooling and performance-scalability are some of the major challenges for their use in building thermal energy storage (TES) applications. Here, in this study, we present a comprehensive multiscale characterization of two commercially available organic PCMs, Puretemp 18 and Puretemp 23. At the microscale, differential scanning calorimetry (DSC) was used to characterize phase change temperature, specific heat, and latent heat. At the mesoscale, a heat flow meter apparatus (HFMA), following the ASTM C1784 standard, was employed to measure the phase change temperature, specific heat, and latent heat properties. A comparative analysis of latent heat as a function of temperature was conducted by integrating the DSC and HFMA results. At the macroscale, the thermal performance and cyclic stability of the TES system was evaluated using Puretemp 23. The TES system consisted of a finned tube heat exchanger with a storage volume of 0.0189 m 3 (5 gal), which represents a compact, real-world TES solution suitable for building energy storage. The results showed consistent thermal stability of the PCM over 200 cycles, and the supercooling temperature remained within 0.2 °C, which was not detected in smaller-scale characterization methods. Additionally, the macroscale testing methodology of the PCM revealed that the TES is able to charge and discharge stored latent energy within 2 h under a temperature differential of 16.67 °C measured between the inlet water temperature and the phase transition temperature of the PCM. The proposed multiscale PCM characterization method provides a systematic basis for comparing important thermal storage properties while also investigating the scalability, reliability and integration challenges in large scale TES applications.

Latent heat↗

TrustDER: Trusted, Private and Scalable Coordination of Distributed Energy Resources

In this project, the Stanford and SLAC Teams have developed a Trusted, Private and Scalable platform for coordinating Coordination of Distributed Energy Resources (TrustDER). This is a layered system that ensures private, trusted and scalable coordination and monitoring of DERs. It accommodates a variety of resources, such as solar generation, gensets and loads, with a particular focus on battery systems-based resources, as they are a transformational technology experiencing fast growth in adoption by large critical facilities. The platform can be used as standalone or added to existing aggregation systems to enable trust, privacy and resilience. TrustDER consists of layers that address each of the shortcomings of the existing state of the art. Each layer in the platform can operate independently but provides information to the layers above it to enable a novel form of overall coordination architecture. The project consists of several tasks, with each task dedicated to the design of each layer. Task 2 Resource Virtualization defined a software abstraction layer for distributed energy resources (DERs). The goal of this abstraction was to simplify the implementation of algorithms utilizing cooperation of DERs resources in a variety of use cases. Task 3 is on Secure ID for Asset Authentication. Identity Management Systems (IDMS) are a foundational infrastructure for interactions between entities (organizations, users, devices, and services). Secure ID is blockchain-based a distributed identity management system allowing (1) identity provisioning, (2) authentication, (3) authorization, and (4) identity data sharing for IoT-enabled assets on the electricity grid. In this project, the SLAC team focused on designing and testing Keymaker, a protocol for authenticating device identity managed by Secure ID. Task 5 Private and Safe Integration is focused on the design and evaluation of a DER cooperation scheme which allows for the aggregation of DERs without impacting network reliability. The approach is designed based on realistic assumptions regarding data availability, communication infrastructure limitations, and privacy. Task 6 Scalable Distributed Privacy for Information explored how virtualized batteries could be managed privately. Specifically, it examined the case in which a principal provides a partitioned battery to multiple clients. Task 7 Use Cases was to ensure that this technology was applied in relevant situations and scenarios. Primarily, this means that virtualization needed to be employed in a manner that either improved flexibility, bolstered security or privacy, or decreased costs.

25 ENERGY STORAGE↗

HP-FLEX: Field demonstration of the semantics-driven configuration of a Model Predictive Control system to make heat pumps flexible

Model Predictive Control (MPC) has demonstrated significant potential for optimizing building operations and enabling demand flexibility. However, the widespread adoption of MPC is hindered by complex manual configuration and commissioning processes that must be conducted by control experts working alongside building operators. These challenges drive up costs and reduce scalability, particularly when technical human resources and building automation systems are limited, such as in small and medium commercial buildings (SMCBs). This paper demonstrates how semantic standards, specifically ASHRAE 223P, can accelerate the adoption of MPC applications for load flexibility in SMCBs. The authors present a replicable control framework, titled “HP-FLEX” that leverages a building’s semantic model to bootstrap the required data configuration for an MPC controller developed for optimizing heat pump systems as flexible grid resources. The semantic model helps streamline the deployment workflow, particularly for site setup, data/control commissioning, and model setup. This integration enhances portability, transferability, and scalability of the HP-FLEX MPC, which has been developed to support MPC-based supervisory HVAC controllers in SMCBs. Additionally, the paper details the required building and thermostat metadata information to enable the HP-FLEX MPC based on field demonstrations. The new workflow was tested in a small commercial building located in California, U.S., and demonstrated a load shifting performance of 9% based on a dynamic pricing signal that varies by the hour. This work provides a practical pathway for transitioning sophisticated building applications from custom to standardized semantic representations, supporting the broader adoption of advanced control strategies like MPC. The framework also establishes a foundation for evolving metadata requirements as applications mature while maintaining compatibility with industry standards.

Paul, Lazlo↗