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At least 739 records · Page 41

Documentation, User Support, and Verification of Wind Turbine and Plant Models (Final Report)

As part of the Utility Wind Energy Integration Group (UWIG) and EnerNex's Wind Turbine Modeling Project, EnerNex has received ARRA (federal stimulus) funding through the Department of Energy (DOE) to further the progress of wind turbine and wind plant models. Despite the large existing and planned wind generation deployment, industry-standard models for wind generation have not been formally adopted. Models commonly provided for interconnection studies are not adequate for use in general transmission planning studies, where public, non-proprietary, documented and validated models are needed. NERC MOD (North American Electric Reliability Corporation) reliability standards require that power flow and dynamics models be provided, in accordance with regional requirements and procedures. The goal of this project is to accelerate the appropriate use of generic wind turbine models for transmission network analysis by: (1) Defining proposed enhancements to the generic wind turbine model structures that would allow representation of more advanced; (2) Comparative testing of the generic models against more detailed (and sometimes proprietary) versions developed by turbine vendors; (3) Developing recommended parameters for the generic models to best mimic the performance of specific commercial wind turbines; (4) Documenting results of the comparative simulations in an application guide for users; (5) Conducting technology transfer activities in regional workshops for dissemination of knowledge and information gained, and to engage electric power and wind industry personnel in the project while underway; (6) Designing of a "living" homepage to establish an online resource for transmission planners.

17 WIND ENERGY↗

Atomic-Scale Surface Studies of Bulk Metallic Glasses. Final Report

Bulk metallic glasses (BMGs) are of both scientific and technological interest because the absence of periodic atomic arrangements provides them with unique physical, chemical, and mechanical properties. Their high strength, superior elasticity, and an ability to be easily formed into virtually unlimited shapes with feature sizes from centimeters to Angstroms by blow molding and thermoplastic forming makes them an attractive choice for more and more practical applications and products. Due to their complex internal structure, however, experiments that yield insight into their exact atomic arrangements have been scarce. As a result, glass physics is one of the last remaining unexplored fields of materials science despite the scientific and technological importance of glasses in our daily lives, and the question how to characterize and control matter away from equilibrium, as glasses are, was listed as one of five Grand Challenges in a recent DoE report. The main reason for the slow progress in glass physics is the lack of experimental tools that enable access to atomic-scale structural and behavioral information for disordered materials. Such atomic-scale knowledge is mandatory to establish structure-property relationships that ultimately could allow to custom-design alloys featuring specific desired characteristics. With no such relationships available, theory development in glass remains basic and the few that exist are often untested. The aim of this research was to enable progress in our understanding of BMGs by developing a new approach that will allow a meaningful application of local surface science methods to specially prepared BMG samples to obtain a wealth of quantitative information on their atomic arrangements. Key was the availability of specially prepared samples whose surfaces feature large atomically flat terraces despite being entirely amorphous, which we have produced from a Pt 57.5 Cu 14.7 Ni 5.3 P 22.5 alloy (‘Pt-BMG’) both under ambient conditions as well as in ultrahigh vacuum using a unique setup that has been specially developed within this grant. Our approach starts with the in-situ preparation of oxide crystals that are terminated by large terraces, from which exact mirror images out of BMG will be produced using thermoplastic forming (TPF); for the research within this grant, we have successfully used (001)-oriented SrTiO 3 single crystal surfaces as well as (100)-, (110)-, and (111)-oriented single crystals made from LaAlO 3 . Since the resulting BMG replicas display all features of the original crystal with sub-Angstrom fidelity, thereby mimicking the original crystal’s termination by atomically flat terraces without being crystalline themselves, they are ideally suited for further investigation. The following atomic-scale local studies were then carried within this proposal: (i) high-resolution surface imaging and local spectroscopy using scanning probe microscopy, which showed disordered atom-like features and revealed changes in the gradient of the local surface potential on a 1-2 nm length scale; (ii) characterization of atomic-scale plastic flow with affected volumes as low as 1000 atoms, which showed local hardness near or above the theoretically predicted maximum and, once plastic deformation was initiated, homogeneous flow of the atoms involved; (iii) characterization of surface relaxation processes and the onset of crystallization induced by annealing, which showed that upon heating over the material’s glass transition temperature, the surface rearranges and relaxes towards a more stable, denser packed glass, which increases on-terrace surface roughness, while surface tension smoothens step edges; and (iv) studies that investigate the dependence of the material’s mechanical properties and structure on processing parameters, revealing that relaxed glasses get denser, harder, and more elastic. In combination, this information allows to combine structural models with mechanical properties and preparation history, thereby facilitating the development of preparation-structure-property relationships for metallic glasses. With the availability of such information, bulk metallic glasses can be further optimized to be used in more and more applications in industry.

36 MATERIALS SCIENCE↗

Advanced Hydropower and PSH Capacity Expansion Modeling (Final Report on HydroWIRES D1 Improvements to Capacity Expansion Modeling)

Hydropower and pumped-storage hydropower (PSH) have played a key role in providing flexible, low-carbon electricity to the U.S. electricity system for over a century. As variable generation (VG) deployment increases the demand for flexible, dispatchable generation, it is important to use all available methods for understanding how hydropower and PSH interfaces with VG in a future low-carbon grid. Capacity expansion models (CEMs) of electricity systems are often used to study future electricity scenarios, but these tools often have difficulty representing site- and technology-details of hydropower and PSH due to limited spatial, temporal, or process resolution. This report demonstrates a set of model advancements to improve hydropower and PSH representations in CEMs and other models that consider hydropower and PSH's role in electricity systems. Model advancements include new data integration to define closed-loop PSH resource availability and cost, along with site-level parameterizations of existing PSH capacity and energy storage specifications. Shifting energy across seasons for both hydropower and PSH is explored to demonstrate the potential value of long-duration storage. New representations of hydropower upgrades offer opportunities to increase dispatchability, add pumps, or independently add capacity or energy depending on what is most valuable. New model structures and data are demonstrated individually and in combination to observe their impact on model results and provide initial insights into what is most important for analysts, electricity system planners, and hydropower decision-makers to consider when assessing future roles of hydropower. Improving flexibility of existing hydropower assets has the potential to reduce CO 2 emissions through complementing VG technologies and/or improve electricity system economics by reducing the need to deploy higher-cost systems. Large-scale energy storage is also shown to provide opportunities for balancing seasonal differences in VG, particularly solar photovoltaics (PV). Initial analysis with a new closed-loop PSH resource and cost dataset also demonstrate the potential for new PSH deployment to offer new grid flexibility opportunities. Future analysis and modeling of hydropower's role in the U.S. and other electricity systems could include methodological improvements based on those discussed here along with sensitivity analysis to better represent current and future potential hydropower and PSH flexibility. Improvements to geospatial and site-level data can further improve the understanding of how hydropower and PSH can be upgraded and operated in response to future electricity system needs. This work lays the groundwork to use advanced planning models to explore the range of roles hydropower and PSH can play in the grid of the future.

13 HYDRO ENERGY↗

A Perspective on Traditional and Data Driven Electrochemical Modeling and Analysis

To understand the behavior of electrochemical systems, we need to reduce the dimensionality of the measured current-voltage-time (I-V-t) data by fitting models, thus enabling us to analyze and compare the governing physics. Traditionally, the process for this is an 'expert first' approach: defining the model and its explicit assumptions based on inductive reasoning or empirical observation, fitting small portions of the I-V-t data where assumptions are most valid or carefully designing experiments to enforce key assumptions, and then interpreting the model parameters. However, modern data-driven methods enable a new paradigm: a 'data first' approach, where the latent behaviors governing the system's measured response are identified directly using machine-learning models that optimize both model structure and parameters from the I-V-t data, guaranteeing that the learned model explains as much of the observed system response as possible. After model identification, the model can then be interrogated by an expert to connect observed behaviors with underlying physics. This talk will review several different types of electrochemical analysis (electrochemical impedance, differential voltage-capacity, electrochemical kinetics) and compare the traditional and data-driven methods for analyzing the data.

42 ENGINEERING↗

Simulated high-latitude soil thermal dynamics during the past 4 decades

Soil temperature ( T s ) change is a key indicator of the dynamics of permafrost. On seasonal and interannual timescales, the variability of T s determines the active-layer depth, which regulates hydrological soil properties and biogeochemical processes. On the multi-decadal scale, increasing T s not only drives permafrost thaw/retreat but can also trigger and accelerate the decomposition of soil organic carbon. The magnitude of permafrost carbon feedbacks is thus closely linked to the rate of change of soil thermal regimes. In this study, we used nine process-based ecosystem models with permafrost processes, all forced by different observation-based climate forcing during the period 1960–2000, to characterize the warming rate of T s in permafrost regions. There is a large spread of T s trends at 20 cm depth across the models, with trend values ranging from 0.010 ± 0.003 to 0.031 ± 0.005 °C yr -1 . Most models show smaller increase in T s with increasing depth. Air temperature ( T sub>a ) and longwave downward radiation (LWDR) are the main drivers of T s trends, but their relative contributions differ amongst the models. Different trends of LWDR used in the forcing of models can explain 61 % of their differences in T s trends, while trends of T a only explain 5 % of the differences in T s trends. Uncertain climate forcing contributes a larger uncertainty in T s trends (0.021 ± 0.008 °C yr -1 , mean ± standard deviation) than the uncertainty of model structure (0.012 ± 0.001 °C yr -1 ), diagnosed from the range of response between different models, normalized to the same forcing. In addition, the loss rate of near-surface permafrost area, defined as total area where the maximum seasonal active-layer thickness (ALT) is less than 3 m loss rate, is found to be significantly correlated with the magnitude of the trends of T s at 1 m depth across the models ( R = -0.85, P = 0.003), but not with the initial total near-surface permafrost area ( R = -0.30, P = 0.438). The sensitivity of the total boreal near-surface permafrost area to T s at 1 m is estimated to be of -2.80 ± 0.67 million km 2 °C -1 . Finally, by using two long-term LWDR data sets and relationships between trends of LWDR and T s across models, we infer an observation-constrained total boreal near-surface permafrost area decrease comprising between 39 ± 14 × 10 3 and 75 ± 14 × 10 3 km 2 yr -1 from 1960 to 2000. This corresponds to 9–18 % degradation of the current permafrost area.

58 GEOSCIENCES↗

Influence of aggregated morphology on carbon dioxide uptake of polythiophene conjugated organic networks

Two novel thiophene-based conjugated networks CMPs-TTT and CMPs-DTBT were designed and prepared with different steric configuration building blocks by FeCl{sub 3} oxidative coupling polymerization. UV–vis spectra, FE-SEM and TEM images showed CMPs-TTT and CMPs-DTBT having the different aggregated morphologies. After porous analysis and gas adsorption test, the result showed CO{sub 2} uptake capacity of CMPs-DTBT with amorphous aggregation model is 2.88 times and 2.66 times greater than that of CMPs-TTT with large lamellar structure model at 273 K and 298 K (1.0 bar), respectively. As a result, this communication proved that change the topological structure of the polymer can influence the CO{sub 2} adsorption capacity significantly. - Graphical abstract: Two thiophene-based conjugated networks were prepared with different steric configuration building blocks, and they show various CO{sub 2} uptake capacity and sorption isosteric enthalpies, although they have identical chemical constitution. - Highlights: • Topological-directed design and synthesis two conjugated porous polymers. • Two thiophene-based CMPs show different aggregated morphologies. • They exhibit similar porosity structure and different CO{sub 2} uptake capacity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis, structures and properties of the new lithium cobalt(II) phosphate Li{sub 4}Co(PO{sub 4}){sub 2}

{alpha}-Li{sub 4}Co(PO{sub 4}){sub 2} has been synthesized and crystallized by solid-state reactions. The new phosphate crystallizes in the monoclinic system (P2{sub 1}/a, Z=4, a=8.117(3) Angstrom-Sign , b=10.303(8) Angstrom-Sign , c=8.118(8) Angstrom-Sign , {beta}=104.36(8) Angstrom-Sign ) and is isotypic to {alpha}-Li{sub 4}Zn(PO{sub 4}){sub 2}. The structure of {alpha}-Li{sub 4}Co(PO{sub 4}){sub 2} has been determined from single-crystal X-ray diffraction data {l_brace}R{sub 1}=0.040, wR{sub 2}=0.135, 2278 unique reflections with F{sub o}>4{sigma}(F{sub o}){r_brace}. The crystal structure, which might be regarded as a superstructure of the wurtzite structure type, is build of layers of regular CoO{sub 4}, PO{sub 4} and Li1O{sub 4} tetrahedra. Lithium atoms Li2, Li3 and Li4 are located between these layers. Thermal investigations by in-situ XRPD, DTA/TG and quenching experiments suggest decomposition followed by formation and phase transformation of Li{sub 4}Co(PO{sub 4}){sub 2}: {alpha}-Li{sub 4}Co(PO{sub 4}){sub 2} Long-Rightwards-Double-Arrow {sup 442 Degree-Sign C}{beta}-Li{sub 3}PO{sub 4}+LiCoPO{sub 4} Rightwards-Harpoon-Over-Leftwards-Harpoon {sup 773 Degree-Sign C}{beta}-Li{sub 4}Co(PO{sub 4}){sub 2} Long-Rightwards-Double-Arrow {sup quenchingto25 Degree-Sign C}{alpha}-Li{sub 4} Co(PO{sub 4}){sub 2} According to HT-XRPD at {theta}=850 Degree-Sign C{beta}-Li{sub 4}Co(PO{sub 4}){sub 2} (Pnma, Z=2, 10.3341(8) A, b=6.5829(5) A, c=5.0428(3) Angstrom-Sign ) is isostructural to {gamma}-Li{sub 3}PO{sub 4}. The powder reflectance spectrum of {alpha}-Li{sub 4}Co(PO{sub 4}){sub 2} shows the typical absorption bands for the tetrahedral chromophore [Co{sup II}O{sub 4}]. - Graphical abstract: The complex formation and decomposition behavior of Li{sub 4}Co(PO{sub 4}){sub 2} with temperature has been elucidated. The crystal structure of its {alpha}-phase was determined from single crystal data, HT-XRPD allowed derivation of a structure model for the {beta}-phase. Both modifications belong to the Li{sub 3}PO{sub 4} structure family. Highlights: Black-Right-Pointing-Pointer Li{sub 4}Co(PO{sub 4}){sub 2} exhibits complex thermal behavior. Black-Right-Pointing-Pointer The new phosphate belongs to the Li{sub 3}PO{sub 4} structure family. Black-Right-Pointing-Pointer A single-crystal structure analysis is provided for the metastable {alpha}-Li{sub 4}Co(PO{sub 4}){sub 2}. Black-Right-Pointing-Pointer From HT-XRPD data a cation distribution model is developed for {beta}-Li{sub 4}Co(PO{sub 4}){sub 2}. Black-Right-Pointing-Pointer No electrochemical delithiation is observed up to 5 V.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advances on statistical/thermodynamical models for unpolarized structure functions

During the eights and nineties many statistical/thermodynamical models were proposed to describe the nucleons' structure functions and distribution of the quarks in the hadrons. Most of these models describe the compound quarks and gluons inside the nucleon as a Fermi / Bose gas respectively, confined in a MIT bag with continuous energy levels. Another models considers discrete spectrum. Some interesting features of the nucleons are obtained by these models, like the sea asymmetries {sup -}d/{sup -}u and {sup -}d-{sup -}u.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Methodology for Irradiation Creep Testing of SiC / SiC Composite Cladding

Irradiation creep compliance is a critical parameter for evaluating the stress evolution of silicon carbide (SiC) components during operation in various reactor concepts. Recent instrumented irradiation creep testing of SiC, performed at low dose in the Halden reactor, showed a creep compliance that is orders of magnitude higher than previous un-instrumented bend relaxation experiments performed in the High Flux Isotope Reactor (HFIR). This discrepancy illustrates the need for additional irradiation creep data for SiC. To this end, a novel irradiation capsule design has been developed to test miniature SiC tensile specimens under loading during irradiation in the HFIR. The experiment design uses the coolant pressure of the HFIR to compress a bellows, which applies the loading on the specimen. Preliminary thermal finite element models were developed to estimate the temperature distribution within the specimen and surrounding capsule components. Similar structural models were developed to evaluate the stress distribution within the specimen. The thermal analyses show that within the gauge section, the specimen temperatures remain within ~10°C of the nominal 300°C design temperature. Similarly, the structural analysis predicts axial stresses within ~10 MPa of the target stress of 100 MPa. These initial analyses show that irradiation creep testing of SiC in the HFIR is feasible and could provide a low-cost, high-throughput vehicle for gathering needed irradiation creep data.

36 MATERIALS SCIENCE↗

Local and long-range atomic/magnetic structure of non-stoichiometric spinel iron oxide nanocrystallites

Spinel iron oxide nanoparticles of different mean sizes in the range 10–25 nm have been prepared by surfactant-free up-scalable near- and super-critical hydrothermal synthesis pathways and characterized using a wide range of advanced structural characterization methods to provide a highly detailed structural description. The atomic structure is examined by combined Rietveld analysis of synchrotron powder X-ray diffraction (PXRD) data and time-of-flight neutron powder-diffraction (NPD) data. The local atomic ordering is further analysed by pair distribution function (PDF) analysis of both X-ray and neutron total-scattering data. It is observed that a non-stoichiometric structural model based on a tetragonal γ-Fe 2 O 3 phase with vacancy ordering in the structure (space group P 4 3 2 1 2) yields the best fit to the PXRD and total-scattering data. Detailed peak-profile analysis reveals a shorter coherence length for the superstructure, which may be attributed to the vacancy-ordered domains being smaller than the size of the crystallites and/or the presence of anti-phase boundaries, faulting or other disorder effects. The intermediate stoichiometry between that of γ-Fe 2 O 3 and Fe 3 O 4 is confirmed by refinement of the Fe/O stoichiometry in the scattering data and quantitative analysis of Mössbauer spectra. The structural characterization is complemented by nano/micro-structural analysis using transmission electron microscopy (TEM), elemental mapping using scanning TEM, energy-dispersive X-ray spectroscopy and the measurement of macroscopic magnetic properties using vibrating sample magnetometry. Notably, no evidence is found of a Fe 3 O 4 /γ-Fe 2 O 3 core-shell nanostructure being present, which had previously been suggested for non-stoichiometric spinel iron oxide nanoparticles. Finally, the study is concluded using the magnetic PDF (mPDF) method to model the neutron total-scattering data and determine the local magnetic ordering and magnetic domain sizes in the iron oxide nanoparticles. The mPDF data analysis reveals ferrimagnetic collinear ordering of the spins in the structure and the magnetic domain sizes to be ∼60–70% of the total nanoparticle sizes. The present study is the first in which mPDF analysis has been applied to magnetic nanoparticles, establishing a successful precedent for future studies of magnetic nanoparticles using this technique.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Extracting structural motifs from pair distribution function data of nanostructures using explainable machine learning

Characterization of material structure with X-ray or neutron scattering using e.g. Pair Distribution Function (PDF) analysis most often rely on refining a structure model against an experimental dataset. However, identifying a suitable model is often a bottleneck. Recently, automated approaches have made it possible to test thousands of models for each dataset, but these methods are computationally expensive and analysing the output, i.e. extracting structural information from the resulting fits in a meaningful way, is challenging. Our Machine Learning based Motif Extractor (ML-MotEx) trains an ML algorithm on thousands of fits, and uses SHAP (SHapley Additive exPlanation) values to identify which model features are important for the fit quality. We use the method for 4 different chemical systems, including disordered nanomaterials and clusters. ML-MotEx opens for a type of modelling where each feature in a model is assigned an importance value for the fit quality based on explainable ML.

36 MATERIALS SCIENCE↗

On the vulnerability of data-driven structural health monitoring models to adversarial attack

Many approaches at the forefront of structural health monitoring rely on cutting-edge techniques from the field of machine learning. Recently, much interest has been directed towards the study of so-called adversarial examples; deliberate input perturbations that deceive machine learning models while remaining semantically identical. This article demonstrates that data-driven approaches to structural health monitoring are vulnerable to attacks of this kind. In the perfect information or ‘white-box’ scenario, a transformation is found that maps every example in the Los Alamos National Laboratory three-storey structure dataset to an adversarial example. Also presented is an adversarial threat model specific to structural health monitoring. The threat model is proposed with a view to motivate discussion into ways in which structural health monitoring approaches might be made more robust to the threat of adversarial attack.

60 APPLIED LIFE SCIENCES↗

Using magnetic moments to study the nuclear structure of I{>=} 2 states

The experimental study of magnetic moments for nuclear states near the ground state, I{>=} 2, provides a powerful tool to test nuclear structure models. Traditionally, the use of Coulomb excitation reactions have been utilized to study low spin states, mostly I= 2. The use of alternative reaction channels, such as {alpha} transfer, for the production of radioactive species that, otherwise, will be only produced in future radioactive beam facilities has proved to be an alternative to measure not only excited states with I > 2, but to populate and study long-live radioactive nuclei. This contribution will present the experimental tools and challenges for the use of the transient field technique for the measurement of g factors in nuclear states with I{>=} 2, using Coulomb excitation and {alpha}-transfer reactions. Recent examples of experimental results near the N= 50 shell closure, and the experimental challenges for future implementations with radioactive beams, will be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Using long‐term data from a whole ecosystem warming experiment to identify best spring and autumn phenology models

Abstract Predicting vegetation phenology in response to changing environmental factors is key in understanding feedbacks between the biosphere and the climate system. Experimental approaches extending the temperature range beyond historic climate variability provide a unique opportunity to identify model structures that are best suited to predicting phenological changes under future climate scenarios. Here, we model spring and autumn phenological transition dates obtained from digital repeat photography in a boreal Picea ‐ Sphagnum bog in response to a gradient of whole ecosystem warming manipulations of up to +9°C, using five years of observational data. In spring, seven equally best‐performing models for Larix utilized the accumulation of growing degree days as a common driver for temperature forcing. For Picea , the best two models were sequential models requiring winter chilling before spring forcing temperature is accumulated. In shrub, parallel models with chilling and forcing requirements occurring simultaneously were identified as the best models. Autumn models were substantially improved when a CO 2 parameter was included. Overall, the combination of experimental manipulations and multiple years of observations combined with variation in weather provided the framework to rule out a large number of candidate models and to identify best spring and autumn models for each plant functional type.

Schädel, Christina↗

Spectral reflectance reconstruction with the locally weighted linear model

Spectral reflectance reconstruction by the local linear model has many advantages such as simple model structure, fast calculation speed and less chance to be over-fitting. However, local linear model often suffers from the outliers and prone to be under-fitting. In this paper, we propose a locally weighted linear model for spectral reflectance reconstruction. It improves the contribution of the local neighbors with higher similarity to the test point, which can reduce the influence of noisy points and redundant points. Experimental results show that the locally weighted linear model can effectively reduce the reconstruction error.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Net-zero CO 2 by 2050 scenarios for the United States in the Energy Modeling Forum 37 study

The Energy Modeling Forum (EMF) 37 study on deep decarbonization and high electrification analyzed a set of scenarios that achieve economy-wide net-zero carbon dioxide (CO 2 ) emissions in North America by mid-century, exploring the implications of different technology evolutions, policies, and behavioral assumptions affecting energy supply and demand. Here, for this paper, 16 modeling teams reported resulting emissions projections, energy system evolution, and economic activity. This paper provides an overview of the study, documents the scenario design, provides a roadmap for complementary forthcoming papers from this study, and offers an initial summary and comparison of results for net-zero CO 2 by 2050 scenarios in the United States. We compare various outcomes across models and scenarios, such as emissions, energy use, fuel mix evolution, and technology adoption. Despite disparate model structure and sources for input assumptions, there is broad agreement in energy system trends across models towards deep decarbonization of the electricity sector coupled with increased end-use electrification of buildings, transportation, and to a lesser extent industry. All models deploy negative emissions technologies (e.g., direct air capture and bioenergy with carbon capture and storage) in addition to land sinks to achieve net-zero CO 2 emissions. Important differences emerged in the results, showing divergent pathways among end-use sectors with deep electrification and grid decarbonization as necessary but not sufficient conditions to achieve net zero. These differences will be explored in the papers complementing this study to inform efforts to reach net-zero emissions and future research needs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Virtual storage capability of residential buildings for sustainable smart city via model-based predictive control

This paper evaluates the virtual storage capability of a residential air-conditioning (AC) system by utilizing the building mass as a thermal storage to enable sustainable cities through model-based predictive control (MPC). The control-oriented building model was developed with a grey-box model structure based on the experimental data to predict the indoor air temperature. Based on the model, the operation cost-saving potential of the MPC was investigated in a single house with different comfort levels, electricity prices, and prediction horizons. The cost-saving of the MPC was approximately 10.6 % compared to the conventional control. The MPC was expanded to a residential building cluster considering the peak demand charge. In an hourly shedding and load-up scenario, the performances of the MPC and the heuristic prior-based control (PBC) are promising. When shedding was enforced all day, the peak demand saving of the MPC was 36~38 %, whereas that of the PBC was 25.7 % compared to the baseline. In addition, the monthly electricity bill, including the operation and peak demand cost, was investigated with different demand charge rates and weather conditions. The total saving decreased with a low demand charge rate and hot conditions, and the operation cost saving was compromised with more aggressive demand shedding.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗