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At least 523 records · Page 29

Thermochemical reduction modeling in a high-temperature moving-bed reactor for energy storage: 1D model

The design of robust and efficient high-temperature thermochemical reactors and determination of operating conditions are critical steps toward enabling high-efficiency long-duration solar energy storage. This work presents a computational model for the thermal reduction of a metal oxide material (Mg-Mn-O) up to 1450 °C and the coupled complex transport phenomena in a novel tubular thermal reactor design that features the capability for a high extent-of-reduction (high energy storage density) and inherent heat recuperation. A one-dimensional model coupling counter-current gas–solid flow, two-phase heat transfer, thermochemical redox reactions, and species transport in a moving-bed reactor is developed. Simplified versions of the model are validated with published results in the literature for packed beds with both inert and reactive particles; the fully coupled model is also validated with experimental measurements of a moving-bed reactor in terms of local temperatures and oxygen release at the exit. Detailed comparisons on the effects of different boundary conditions in the reaction zone (prescribed wall temperature vs. heat flux conditions) and formulations based on a simple uniform flow assumption vs. plug flow using Ergun equation for gas flow are investigated. The results are compared with experimental measurements, and for all cases, the energy flow components in the reactor system and the thermal to chemical conversion efficiency and overall system efficiency are computed. Finally, the predicted high thermal-to-chemical efficiency ~95% and system efficiency ~30% agree with experimental measurements.

25 ENERGY STORAGE↗

Behavior, Energy, Autonomy, Mobility Modeling Framework (BEAM) v1.0

The Behavior, Energy, Autonomy, and Mobility (BEAM) model is an integrated, agent-based travel demand simulation framework. Individual agents express preferences through a utility- maximizing evolutionary algorithm that minimizes each individual’s cost and time spent traveling via diverse modal options, including the competition for scarce supply resources such as parking spaces and charging infrastructure. BEAM simulates the essential elements that compose a dynamic transportation system. From the road network, parking and charging infrastructure, to the transit system and a synthetic population with plans and preferences, the virtual system is an amalgamation of multiple spatially resolved layers that together represent an integrated transportation system. BEAM is an extension to the MATSim (Multi-Agent Transportation Simulation) model, where agents employ reinforcement learning across successive simulated days to maximize their personal utility through plan mutation (exploration) and selecting between previously executed plans (exploitation). The BEAM model shifts some of the behavioral emphasis in MATSim from across-day planning to within- day planning, where agents dynamically respond to the state of the system during the mobility simulation. In BEAM, agents can plan across all major modes of travel including driving, walking, biking, transit, and demand-responsive ride hailing. It is designed to integrate with other open source transportation models, such as ActivitySim.

Lazarus, Jessica↗

Steady-state solutions of a diffusive energy-balance climate model and their stability

A diffusive energy-balance climate model, governed by a nonlinear parabolic partial differential equation, was studied. Three positive steady-state solutions of this equation are found; they correspond to three possible climates of our planet: an interglacial (nearly identical to the present climate), a glacial, and a completely ice-covered earth. Models similar to the main one are considered, and the number of their steady states was determined. All the models have albedo continuously varying with latitude and temperature, and entirely diffusive horizontal heat transfer. The stability under small perturbations of the main model's climates was investigated. A stability criterion is derived, and its application shows that the present climate and the deep freeze are stable, whereas the model's glacial is unstable. The dependence was examined of the number of steady states and of their stability on the average solar radiation.

Ghil, M.↗

Energy-balance climate models

An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

North, G. R.↗

Energy balance climate models

An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved, and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

North, G. R.↗

DEEP Solar: Data DrivEn Modeling and Analytics for Enhanced System Layer ImPlementation

Realizing the SETO 2030 mission of reducing solar energy costs to 3-5 c/kWh will require innovative enabling research on effective, cost-efficient integration of local PV within distribution systems. However, the intermittent and variable nature of PVs compels operators to impose conservative hosting capacity constraints. Given the extremely high variability of (intermittent and unpredictable) solar energy generation, relaxing the capacity constraints (which are currently around 15%) and achieving 100% or greater integration of renewables will require a fundamental transformation of the power grid via the utilization of exponentially larger amounts of AMI enabled fine-grained data. To address the challenges in increasing the penetration of renewable energy based DERs, this project envisions an Enhanced System Layer (ESL) at the distribution network level that is reliable, cost-effective and scalable to millions of Distributed Energy Resources (DERs)/devices. This includes developing: 1) Transformative and highly scalable machine learning based predictive analytics tools that plug into distribution system planning and provide real-time situational awareness at the distribution level for short and long-term operational planning. The tools will be built using novel data-driven energy models of millions of active nodes with AMI, 2) Adaptive stochastic analysis and optimization algorithms for real-time grid operations, 3) Dynamic Scenario Analysis using parallel Cloudenabled implementations with < 1 minute computational cycle times.

14 SOLAR ENERGY↗

22” ADP Fan Rig Liners Design Report

A liner design study was conducted as part of a cooperative effort between five (5) government/industry teams that together seek to demonstrate the technology for designing and manufacturing acoustic liners that are twenty five percent (25%) more efficient than 1992 technology liners. The study emphasized teaming collaboration. The improved liners were designed by Pratt & Whitney and Boeing Airplane Company and built by Rohr Inc, and will be tested in the NASA/P& W 22-inch ADP fan rig at NASA Lewis Research Center's 9' x 15' wind tunnel. Design guidelines and decisions were made collectively during monthly design review telecons and at the formal final design review. The tools that were used to design the new improved liners were not new, but the process that was developed as part of this study that led into the evaluation and selection of the final and best liner designs is new. Until now, the liner design process as practiced by different industry teams varied greatly. Some procedures were based on empirical liner attenuation databases which could not adequately account for engine-to-engine hardwall fan noise spectral differences, while others were entirely theoretical. And regardless of which method one chose, the major difficulty was still the lack of understanding and knowledge of the actual hardwall fan source noise modal structure and farfield SPL spectra. The NASA-led effort to attempt actual measurements of the fan source noise modal structure by means of the rotating microphone array is expected to contribute significantly to the understanding of the nature of the fan tone noise modes, but the application to broadband noise is still a long way off. The new design process included consideration of the measured fan tone modes, but for the majority of the spectra a separate, systematic process was used. It is a common practice in the engine/nacelle industry that acoustic liners for new products are designed before actual measured hardwall engine far-field noise spectra are available. Target noise spectra are normally derived from existing engine noise databases with some adjustments to absolute SPLs and frequencies. This practice has been acceptable as long as the new engine was a derivative of the base engine. However, in the case of the ADP, the transition from a current engine base is too - great, and the adjustments could not adequately account for the quantum changes in SPL spectral differences. Examples were the 1992 single degree of freedom (SDOF) inlet and aft liners (designed by P&W) that would be used as the baseline liners against which the new improved liners' efficien¬cies would -be measured. As will be shown, these baseline liners have been found to be deeper than the desire optimum depths. The new liner design process begins with the selection of the target hard wall fan noise spectra. These spectra were obtained by scaling up (5.91 scale factor) the measured hardwall fan spectral data from the 22” ADP fan rig. Next, the modal energy contents for each 1/3-octave band center frequency of these hardwall fan noise spectra are estimated. (Within each 1/3-octave band center frequency, the model energy distribution approximation is for both tone and broadband noise). For the inlet noise, P&W uses a derivative of the NASA Lewis (Ed Rice's) method of classifying; and grouping propagating modes by their cutoff ratios. The next step is to assign energy level to each group of modes having the same cutoff ratio. In Ed Rice's model, the modes were grouped according to ten (10) cutoff ratio intervals with center values located at 1.026, 1.085, 1.155, 1.24, 1.35, 1.49, 1.69, 2.0, and 4.47 (with equal number of modes in each interval). The modes were assumed to have equal energy. P&W’s model expands the cutoff ratio-mode grouping into two hundred (200) smaller cutoff ratio intervals with center values located f1".'m 1.003 to 11.5 in 199 increasing incremental intervals. Next, P&W's model uses a "2-parameter" normal distribution as a template to assign energy levels to these 200 pre-determined cutoff ratio values (for each 1/3-octave band center frequency). In the past, P&W had conducted an extensive study to determine what "2-parameter" values are appropriate for fullscale inlet liners, and had developed a set of twenty-four (24) "2-pararneter" values (i.e. one for each 1/3-octave frequency band) that when used in Ed Rice's Inlet Attenuation Prediction Method produced predicted liner attenuations that closely matched measured liner attenuations from several P&W's engines. In the absence of actual measured tone and broadband modal data from the 22" ADP rig, the process will use P&W's proprietary set of "2-parameter" values for this liner design study. For the aft noise, Boeing uses a modal energy approximation that the "transport energy" of each propagating mode is equal. This approximation is almost the same as the equal energy per mode approximation, except for modes that are near cutoff. Boeing's model forces these modes to have lower energy levels. Both P&W and Boeing agreed that the "transport energy" approximation should work well for the ADP aft fan noise which appears to be dominated by broadband noise. The design process then proceeds to calculate the optimum liner impedances for each frequency in both the inlet and the aft. These optimum impedances represent the target impedances that the designed liners should have. Liners with impedances matching the optimum impedances at all frequencies are "ideal" liners. These ideal liners are theoretically the best liners. Unfortunately, it has been showed that it is impossible to design and build such ideal liners. The next best liners are ones that have impedances matching the optimum impedances over some frequency range (not all frequencies as for the ideal). This is accomplished by the use of "frequency weightings". Several of P&W's and Boeing's existing computer decks were used for optimizing and matching the designed liner impedances to the target optimum values (with the various frequency weightings specified). The optimization produces liner candidates with predicted liner impedances and descriptions of their physical liner characteristics. These candidate liner impedances are then used to predict their spectral attenuation characteristics which are then used together with the target hardwall fan noise spectra to determine the resulting treated noise spectra and PNLT values. Further optimization around the selected candidate designs yield final designs that are best in PNLT attenuations. Use of the optimization decks allowed a large number of liner candidates to be screened in a relatively short period of time. This design process is systematic and is efficient. The new inlet SDOF liner design obtained from the improved process was predicted to be 34% more effective (per unit area) than the 1992 baseline inlet liner. This inlet liner design is a 112 rayl wovenwiremesh facesheet over a 0.312-inch deep honeycomb core. The new aft SDOF liner design was predicted to be 52% more efficient than the aft baseline liner. The new aft SDOF liner is "segmented" with a shallower liner on the core cowl (inner duct wall) and a deeper liner on the fan cowl (outer duct wall). The shallower liner is a 70.6 rayl woven-wiremesh facesheet over a 0.141-inch deep honeycomb core. The deeper liner is a 68 rayl woven-wiremesh facesheet over a 0.309-inch deep honeycomb core. All liner dimensions are for the 22-inch model-scale ADP fan rig liners. The selected advanced liners are "segmented" double-layer (DDOF) liners for the inlet and aft locations. Also, for the inlet, a bulk liner with ceramic foam for wider broadband noise absorption was also selected. Triple-layer liner designs were not considered since the model scaled liners ( 1/5. 91) were dimensionally too small to be built correctly, and irrin earlier concept study, Boeing found a triple-layer to have only very small benefits over a double-layer. The inlet DDOF liner was predicted to be 83% more effective than the baseline. The inlet DDOF design is a 78 rayl facesheet over a 0.080 top cavity depth, a 68 rayl septum and a 0.227-inch bottom cavity depth. The inlet bulk liner is a 60 rayl facesheet over a 0.33-inch deep honeycomb filled with high temperature (HTP) ceramic foam with a density of 4.8 lb/cu.ft and a flow resistivity of 167 rayl/cm. The inlet bulk liner was predicted to be 83% more effective than the baseline liner. The aft DDOF liners are segmented with a shallower liner on the core cowl and a deeper liner on the fan cowl. The shallow DDOF liner is a 49.8 rayl facesheet over a 0.093-inch top cavity depth, a septum of 88.2 rayls over a 0.181-inch bottom cavity depth. The deep DDOF liner is a 12.9 rayl facesheet over a 0.140-inch top cavity depth, a septum of 53.1 ray ls over a 0.258-inch botom cavity depth. The segmented aft DDOF liners were predicted to be 86% more efficient than the baseline liner.

turbofan acoustic treatment↗

EnergyPlus Model Context Protocol Server (EnergyPlus-MCP) v0.1

EnergyPlus-MCP is the first open-source Model Context Protocol server specifically designed for EnergyPlus building energy simulation. This innovative software enables AI assistants and other applications to interact programmatically with EnergyPlus through a standardized, secure interface, eliminating traditional technical barriers in building energy modeling. The software provides specialized tools across five functional domains: server management, model configuration and loading, comprehensive building component inspection, systematic model modification, and simulation execution with results visualization. Key features include automated HVAC system discovery and topology mapping, advanced schedule analysis, intelligent model validation, and interactive visualization capabilities. EnergyPlus-MCP's layered architecture ensures robust separation between protocol communication and domain expertise, enabling scalable deployment across organizations, educational institutions, and research teams. Unlike direct LLM approaches that suffer from inconsistent results and security gaps, EnergyPlus-MCP provides validated, reliable interactions while maintaining scientific rigor. This democratizes sophisticated building energy analysis, making EnergyPlus accessible to broader audiences through conversational interfaces and streamlined workflows.

Li, Han [Lawrence Berkeley National Laboratory (LB↗

Modeled Retrofit Package Performance for Schools

This report details modeled energy performance and savings from retrofit packages in prototypical school buildings in climate zones throughout the U.S. The information herein serves as a reference for elementary and secondary schools interested in implementing retrofit packages in their facilities for energy savings as well as health and safety benefits. School models developed for simulating package performance differentiated between rural and urban environments. Simulations were run for 10 distinct climate zones covering a range of climate conditions throughout the U.S. Results include savings estimates for electricity, natural gas, CO 2 emissions, and annual utility costs for nine different retrofit packages that combine energy conservation measures, including HVAC controls and equipment upgrades, lighting efficiency upgrades, and electrification technologies such as heat pumps for space conditioning and domestic hot water. Nine additional retrofit packages were also developed for elementary schools and modeled in two climate zones. Appendix B describes the additional retrofit packages and presents savings estimates.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The impact of behavioral and geographic heterogeneity on residential-sector carbon abatement costs

Analyses of monetary and emissions savings from residential efficiency upgrades usually neglect behavioral differences between consumers. Variations in behavior are frequently large: 13% of the U.S. population sets thermostats for cooling at 20 °C (68 °F) or lower and 15% at 25.5 °C (78 °F) or higher. Efficiency analyses should account for behavioral heterogeneity as well as variations in climate and housing characteristics. We model energy and economic savings of efficiency upgrades for U.S. single-family detached houses, accounting for differences in thermostat settings, climate zone, fuel prices, and home characteristics. We consider five efficiency interventions: wall insulation, attic insulation, air sealing, high-efficiency furnaces, and high-efficiency air conditioners. Energy and economic savings vary widely by consumer; the average net present value for wall insulation is $3,020 United States Dollar (USD), but considering heterogeneity, it has a 10th percentile value of -$231 and 90th percentile value of $5,000. Neglecting heterogeneity, technology upgrades can be prioritized from lower to higher carbon abatement costs: air conditioners, wall insulation, furnace, air sealing, and attic insulation. Accounting for heterogeneity reorders this prioritization, and consumer-specific conditions affect mitigation costs such that technologies are mixed in with one another and are no longer arranged one after another. These results indicate that interventions to improve efficiency should consider differences between consumers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Nonequilibrium radiation and chemistry models for aerocapture vehicle flowfields

The primary accomplishments of the project were as follows: (1) From an overall standpoint, the primary accomplishment of this research was the development of a complete gasdynamic-radiatively coupled nonequilibrium viscous shock layer solution method for axisymmetric blunt bodies. This method can be used for rapid engineering modeling of nonequilibrium re-entry flowfields over a wide range of conditions. (2) Another significant accomplishment was the development of an air radiation model that included local thermodynamic nonequilibrium (LTNE) phenomena. (3) As part of this research, three electron-electronic energy models were developed. The first was a quasi-equilibrium electron (QEE) model which determined an effective free electron temperature and assumed that the electronic states were in equilibrium with the free electrons. The second was a quasi-equilibrium electron-electronic (QEEE) model which computed an effective electron-electronic temperature. The third model was a full electron-electronic (FEE) differential equation model which included convective, collisional, viscous, conductive, vibrational coupling, and chemical effects on electron-electronic energy. (4) Since vibration-dissociation coupling phenomena as well as vibrational thermal nonequilibrium phenomena are important in the nonequilibrium zone behind a shock front, a vibrational energy and vibration-dissociation coupling model was developed and included in the flowfield model. This model was a modified coupled vibrational dissociation vibrational (MCVDV) model and also included electron-vibrational coupling. (5) Another accomplishment of the project was the usage of the developed models to investigate radiative heating. (6) A multi-component diffusion model which properly models the multi-component nature of diffusion in complex gas mixtures such as air, was developed and incorporated into the blunt body model. (7) A model was developed to predict the magnitude and characteristics of the shock wave precursor ahead of vehicles entering the Earth's atmosphere. (8) Since considerable data exists for radiating nonequilibrium flow behind normal shock waves, a normal shock wave version of the blunt body code was developed. (9) By comparing predictions from the models and codes with available normal shock data and the flight data of Fire II, it is believed that the developed flowfield and nonequilibrium radiation models have been essentially validated for engineering applications.

Carlson, Leland A.↗

OCHRE

OCHRE™ uses a variety of input data sources to run time-series simulations. Building models can be taken from the ResStock™ database or generated using the Building Energy Optimization Tool (BEopt™) or other OpenStudio-HPXML workflows. EV charging profiles can be taken from datasets used in NLR's 2030 National Charging Network project. Weather data can be taken from the National Solar Radiation Database or EnergyPlus® weather files. There are no public datasets with OCHRE outputs at this time. However, a recent project dataset on water heater and EV demand flexibility can be requested. OCHRE is a Python-based energy modeling tool designed to model flexible loads in residential buildings. OCHRE includes detailed models and controls for flexible devices including HVAC equipment, water heaters, EVs, solar PV, and batteries. It is designed to run in co-simulation with custom controllers, aggregators, and grid models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Building Performance Standards and Energy Code Alignment: Technical Brief

Building energy codes focus on building design, construction and renovation and have significantly increased building efficiency since the first national energy code was published in 1975. Most jurisdictions have energy codes based on ANSI/ASHRAE/IES Standard 90.1 (hereto referred to as Standard 90.1) and the International Energy Conservation Code (IECC). Compliance options available in these model energy codes include a prescriptive path, whole building performance paths – including IECC Total Building Performance (TBP), Standard 90.1 Energy Cost Budget (ECB) method and Performance Rating Method (PRM) – and system performance paths for envelope and heating, ventilation, and air-conditioning systems. Building performance standard (BPS) policies are an emerging policy tool used by jurisdictions to reduce the operational energy use or greenhouse gas (GHG) emissions of the existing commercial building stock. BPS policies vary widely between jurisdictions and are tailored to each location’s climate and energy goals. Intuitively, projects that met a recent edition of the energy code should comply with the BPS targets.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Flexible Integration of Diverse HVAC Technologies in EnergyPlus via Python-Enabled Workflows

Analysis of advanced controls and novel system types is often not directly feasible in building energy simulation tools. Various techniques extend building energy simulation tool capabilities to allow the use of user-defined scripts and programs, but these approaches have limitations. The EnergyPlus Python plugin offers users new flexibility to use EnergyPlus to call an external Python module at specific points in the simulation, as well as to use Python to call EnergyPlus functionality through an application programming interface (API). This paper presents four case studies leveraging the EnergyPlus Python plugin to facilitate analysis of advanced controls and system types. The use of the Python plugin offers greater modularity and flexibility relative to previous approaches, is less error prone, and is simpler for users to adopt. The Python plugin allows EnergyPlus to be used in a more flexible manner and to accommodate the expanding realm of energy modeling applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Building Performance Standards and Energy Code Alignment - Technical Brief

Building energy codes focus on building design, construction and renovation and have significantly increased building efficiency since the first national energy code was published in 1975. Most jurisdictions have energy codes based on ANSI/ASHRAE/IES Standard 90.1 (hereto referred to as Standard 90.1) and the International Energy Conservation Code (IECC). Compliance options available in these model energy codes include a prescriptive path, whole building performance paths – including IECC Total Building Performance (TBP), Standard 90.1 Energy Cost Budget (ECB) method and Performance Rating Method (PRM) – and system performance paths for envelope and heating, ventilation, and air-conditioning systems. Building performance standard (BPS) policies are an emerging policy tool used by jurisdictions to reduce the operational energy use or greenhouse gas (GHG) emissions of the existing commercial building stock. BPS policies vary widely between jurisdictions and are tailored to each location’s climate and energy goals. Intuitively, projects that met a recent edition of the energy code should comply with the BPS targets. However, some new buildings may struggle with meeting the BPS for the following reasons: 1. Energy codes focus on the design of the building and its projected ability to perform efficiently, while BPS compliance is dependent on the actual ongoing performance of the building, considering variables like occupancy, operation, and maintenance. 2. There are significant differences in the methodologies used to determine BPS compliance versus code compliance, including how each handles compliance metrics, handling of building amenities, and renewable energy generation. 3. The prescriptive compliance path in the energy code is based on performance of individual building components, as opposed to the performance compliance path which accounts for holistic building design strategies and interdependent building systems. This can result in a significant variability in post-occupancy performance for buildings built using the prescriptive path. Designs on the lower end of the permitted efficiency range may struggle with meeting the BPS.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Equity implications of net-zero emissions: A multi-model analysis of energy expenditures across income classes under economy-wide deep decarbonization policies

With companies, states, and countries targeting net-zero emissions around midcentury, there are questions about how these targets alter household welfare and finances, including distributional effects across income groups. This paper examines the distributional dimensions of technology transitions and net-zero policies with a focus on welfare impacts across household incomes. The analysis uses a model intercomparison with a range of energy-economy models using harmonized policy scenarios reaching economy-wide, net-zero CO 2 emissions across the United States in 2050. Here we employ a novel linking approach that connects output from detailed energy system models with survey microdata on energy expenditures across income classes to provide distributional analysis of net-zero policies. Although there are differences in model structure and input assumptions, we find broad agreement in qualitative trends in policy incidence and energy burdens across income groups. Models generally agree that direct energy expenditures for many households will likely decline over time with reference and net-zero policies. However, there is variation in the extent of changes relative to current levels, energy burdens relative to reference levels, and electricity expenditures. Policy design, primarily how climate policy revenues are used, has first-order impacts on distributional outcomes. Net-zero policy costs, in both absolute and relative terms, are unevenly distributed across households, and relative increases in energy expenditures are higher for lowest-income households. However, we also find that recycled revenues from climate policies have countervailing effects when rebated on a per-capita basis, offsetting higher energy burdens and potentially even leading to net progressive outcomes. Model results also show carbon Laffer curves, where revenues from net-zero policies increase but then decline with higher stringencies, which can diminish the progressive effects of climate policies. We also illustrate how using annual income deciles for distributional analysis instead of expenditure deciles can overstate the progressivity of emissions policies by overweighting revenue impacts on the lowest-income deciles.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Machine learning surrogate of physics-based building-stock simulator for end-use load forecasting

Building energy models are used to simulate heat and mass transfer and estimate end-use load in buildings. With the proliferation of solar photovoltaics on residential and commercial buildings, increasingly, buildings are expected to provide grid services, for which accurate and computationally efficient building energy simulations and end-use load prediction are imperative. Existing building energy simulation tools, however, have significant computational overhead that make them less practical in real-time deployment for optimization, design, uncertainty quantification and control in building energy management systems. Here this article presents a data-driven machine learning model based on light gradient boosting method (LightGBM) as a surrogate for a physics-based simulator for residential buildings to predict end-use load. The machine learning based surrogate model accounts for time-series related variables, seasonality and trend component of end-use load, and history of end-use load. The accuracy of the surrogate model is assessed on the prediction of the load profiles of 100 different houses in Cook County, Illinois, USA. The LightGBM surrogate model is shown to reduce the root-mean-squared error by 53% relative to a reference decision tree (DT) based model reported previously in the literature. Moreover, the model predicts the load spikes and high-ramp rate events throughout the year which are often the Achilles heel of other models in the literature. The machine learning based surrogate model is demonstrated to be computationally efficient, with a ten-fold reduction in the computational time compared to a physics-based building energy simulation, and suitable for uncertainty analysis and real-time control of building characteristics in response to uncertainty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗