Model-Based and Data-Driven HVAC Control Strategies for Residential Demand Response
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24 POWER TRANSMISSION AND DISTRIBUTION↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Scheduler Modeling of IBR Plants for Providing Ancillary Services [SWR-25-16]
Inverter-based resources (IBRs) have been integral components of modern power systems and their capability in providing grid services have been widely studied. To promote the deployment of IBR grid services in real utility operation, this software proposes a scheduler model for IBRs. The energy and reserve are co-optimized in day-ahead, various ancillary services, including operating reserve provision, peak load reduction, voltage regulation and power factor control are integrated in the model.
Wang, Xiaofei [National Renewable Energy Laborator↗
EASY-SHIFT v Alpha
The software is a generic, price- and load-responsive control algorithm integrating heat pumps with thermal energy storage. The algorithm leverages simple models of the system and easily accessible data to schedule operation of heat pumps and thermal energy storage in ways that minimize the cost of operating the heating/cooling system. This tool is specifically designed to be easy to interact with, and something that industry partners are able to adopt. There are two current state of the art approaches. Industry tends to develop very simple algorithms, with predetermined schedules that are not capable of changing operation in response to changes in operating environment. For example, a control designed to avoid high-price electricity from 5-8 PM will not be able to adapt if the high-price period changes to 4-9 PM. Academia commonly develops algorithms called Model predictive control (MPC). MPC requires extensive data and highly trained staff to develop a specific type of simulation model of the building, connect the building to optimization algorithms, and leverage powerful computers. Industry, with limited time/finance budgets for any project, is resistant to adopting MPC due to the associated high complexity and cost.
Grant, Peter [Lawrence Berkeley National Laborator↗
A low-cost centralized HVAC control system solution for energy savings, load shedding, and improved maintenance
University campuses rely on centralized controls for managing and optimizing complex HVAC systems in larger buildings. However, most campuses also have many smaller buildings with packaged HVAC systems controlled by a stand-alone thermostat. Even when these distributed and often overlooked systems have modern programmable thermostats, they cannot be centrally monitored or controlled, and they are typically not programmed adequately. This paper describes the implementation of a low-cost centralized control solution for these systems serving smaller campus buildings, mostly under 5,000 sf and representative of light commercial spaces. Thanks to advances in technology spurred by residential and commercial IoT developments, simple networked thermostat solutions exist that can easily replace original thermostats, and, connect these systems to a web-based portal for monitoring and control. We show that, with small customizations, these platforms can be integrated into facility management workflows. Beyond the energy savings potential from improved scheduling and closer management of these systems, there are significant advantages for maintenance crews since these systems can now be monitored on smart phones or tablets. A grid-responsive load-shedding program has also been implemented for additional cost savings. The networked thermostats can also be connected to additional systems such as economizer controls for improved ventilation management and energy savings. With data from these systems integrated centrally, it can also be used for improved analytics and fault detection. A toolkit has been developed to share the program with other campuses, whether for energy savings, improved management of ventilation, or a more proactive maintenance approach.
Fauchier-Magnan, Nicolas↗
Smart Outlets: Wireless Meter and Control Systems for Plug and Process Loads
Smart outlets control the flow of power to devices plugged into them and measure their energy use. The energy use data can be accessed via an online dashboard or smartphone application, allowing the user to turn power to plug-in devices on or off based on a schedule established in the dashboard or application. This four-page resource is a fact sheet meant to educate commercial building owners on smart outlets: what they are, why we use them, and how to use them in a way that will achieve energy savings while maintaining occupant comfort. The resource also describe how to procure a smart outlet system and how to fully capture their benefits over time. This resource was developed to support the Better Buildings Alliance Plug and Process Loads Technology Research Team.
30 DIRECT ENERGY CONVERSION↗
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↗
Simulation of a PCM Integrated Heat Pump Using Time-of-Use Utility Structure based Control Strategy for Demand Response
To mitigate the variation in demand on the electric grid, thermal energy storage (TES) is an alternative to electric batteries and constructing new peaking power plants. The aggressive carbon reduction goals of the United States are accelerating the electrification of building equipment. If space heating and cooling in the US were electrified using conventional heat pump technologies, the winter electric grid peak would approximately double. Integrating TES with heat pump (HP) enables electrification of space cooling and heating devices without overtaxing the grid.This paper evaluates the benefits of a novel phase change material (PCM) integrated heat pump configuration via simulation. A one-dimensional PCM heat exchanger model which discretizes the PCM tank and refrigerant tubes into small control volumes is developed. Each control volume can have different PCM temperatures, PCM properties, and heat transfer coefficients. The PCM tank is charged by a wrapped tank condenser and discharged by an internal refrigerant coil. The PCM heat exchanger model is integrated into DOE/ORNL Heat Pump Design Model for heat pump system simulation.To demonstrate the performance of the PCM integrated heat pump, a case study in Chicago was performed. A Time-of-Use utility structure-based control strategy is implemented to schedule the PCM tank charging and discharging mode switching. Compared with a conventional electric heat pump, the PCM integrated heat pump shows superior performance on load shifting and utility cost reduction. As a result, the proposed system demonstrates 24.6% utility saving for cooling application and 25.8% utility saving for heating application.
Li, Zhenning↗
FLYING SERVING: On-the-Fly Parallelism Switching for Large Language Model Serving
Production LLM serving must simultaneously deliver high throughput, low latency, and sufficient context capacity under non-stationary traffic and mixed request requirements. Data parallelism (DP) maximizes throughput by running independent replicas, while tensor parallelism (TP) reduces per-request latency and pools memory for long-context inference. However, existing serving stacks typically commit to a static parallelism configuration at deployment; adapting to bursts, priorities, or long-context requests is often disruptive and slow. We present Flying Serving, a vLLM-based system that enables online DP-TP switching without restarting engine workers. Flying Serving makes reconfiguration practical by virtualizing the state that would otherwise force data movement: (i) a zero-copy Model Weights Manager that exposes TP shard views on demand, (ii) a KV Cache Adaptor that preserves request KV state across DP/TP layouts, (iii) an eagerly initialized Communicator Pool to amortize collective setup, and (iv) a deadlock-free scheduler that coordinates safe transitions under execution skew. Across three popular LLMs and realistic serving scenarios, Flying Serving improves performance by up to 4.79 × under high load and 3.47 × under low load while supporting latency- and memory-driven requests.
Gao, Shouwei [ORNL]↗
A Secure and Adaptive Hierarchical Multi-Timescale Framework for Resilient Load Restoration Using a Community Microgrid
Distribution system integrated community microgrids (CMGs) can partake in restoring loads during extended duration outages. At such times, the CMGs are challenged with limited resource availability, absence of robust grid support, and heightened demand-supply uncertainty. Here, this paper proposes a secure and adaptive three-stage hierarchical multi-timescale framework for scheduling and real-time (RT) dispatch of CMGs with hybrid PV systems to address these challenges. The framework enables the CMG to dynamically expand its boundary to support the neighboring grid sections and is adaptive to the changing forecast error impacts. The first stage solves a stochastic extended duration scheduling (EDS) problem to obtain referral plans for optimal resource rationing. The intermediate near-real-time (NRT) scheduling stage updates the EDS schedule closer to the dispatch time using new obtained forecasts, followed by the RT dispatch stage. To make the decisions more secure and robust against forecast errors, a novel concept called delayed recourse is designed. The approach is evaluated via numerical simulations on a modified IEEE 123-bus system and validated using OpenDSS and hardware-in-loop simulations. The results show superior performance in maximizing load supply and continuous secure distribution network operation under different operating scenarios.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Floating Offshore Wind US Manufacturing and Commercialization (CRADA Final Report)
Create a detailed manufacturing, assembly, load-out, transportation, upending, turbine integration, and offshore transportation plan for a hypothetical project in one of the California lease areas off the central coast. Develop a detailed schedule and cost estimation for each step of the process and compare with conventional floating platform designs.
17 WIND ENERGY↗
Machine learning-enhanced MPC for demand flexibility in small commercial buildings: An experimental study
Small- and medium-sized commercial buildings (SMCBs) represent the majority of U.S. commercial building stock and a significant share of peak electricity demand, yet they often lack centralized building automation systems, representing a significant untapped resource for urban energy management. This infrastructure gap makes advanced control implementation challenging, limiting the potential for widespread demand flexibility. Model Predictive Control (MPC) has shown strong potential for load shifting, peak demand reduction, and cost savings, but its effectiveness is hindered by unmeasured disturbances such as internal heat gains. This paper presents a Hybrid MPC framework that integrates a physics-based gray-box building thermal model, identified using a lumped disturbance (LD) approach, with a machine learning (ML) model for forecasting unmeasured disturbances. The hybrid approach is designed for buildings with multiple individually controlled heat pump and thermostat pairs, common in SMCBs, and aims to optimize coordinated scheduling of multiple heat pumps under dynamic electricity pricing while respecting comfort constraints. The methodology is validated through both simulations of case study buildings and experimental studies at a highly-instrumented test facility. Simulation results show that the Hybrid MPC achieves substantial load shifting and peak demand reduction, approaching the performance of an ideal MPC with perfect disturbance knowledge, and outperforming a conventional MPC without disturbance forecasting. In experiments, the Hybrid MPC reduced daily HVAC energy costs by 8.7%, peak-price time load (load shifting) by 41.7%, and peak demand by 29.2% compared to baseline control, demonstrating comparable benefits to the 11.6% cost savings, 42.9% load shifting, and 23.2% peak reduction of the ideal MPC. These results demonstrate that the proposed hybrid modeling approach can significantly improve MPC performance in real-world SMCB applications without requiring additional disturbance measurements.
Demand Flexibility↗
Validation Exercise of a Coarse Finite Element Model of Laser Welds
The objective of this project is to validate low-fidelity models of 304L to 304L stainless steel partial-penetration laser welds for thin sheets. Low-fidelity means that the weld is represented by coarsely meshed element blocks. Here, the hexahedral element size is approx imately half the weld penetration depth. The material behavior of the block is represented by a J2 plasticity model with a Voce hardening function. The source of the data used in this work is an extensive experimental study conducted by Sharlotte Kramer (1528) and published in 2015. Figure 1 shows a cross-section of the weld of interest. The nominal thickness of the sheets is 0.063 in. while the target penetration depth of the weld is in the range of 0.028 to 0.032 in., extending about half the sheet thickness. Uniaxial tension tests provided data for calibration of base material and weld models. Results of two validation geometries were also provided. The principal validation geometry is shown in Fig. 2. It consists of a plate specimen with in-plane dimensions 6 in × 2.875 in loaded in tension. A circular plug with a 1.5 in. diameter was cut from the center of the plate and then welded in place. The details of the welding schedule are given. An important assumption is that the welds in the calibration and validation specimens have similar geometric and material properties as those in the validation tests. The task was to first calibrate models for the base material and the welds and then simulate the validation tests until the point of weld first failure.
36 MATERIALS SCIENCE↗
Smarter building start – A distributed solution
A significant focus of research and new technologies for reducing energy use in buildings is on operating the systems more efficiently during the times when the systems are active. However, there is a large potential for energy savings in determining the periods when the systems should or should not be active. This scheduling aspect of operation is often overlooked even though relatively simple solutions can unlock substantial energy savings. In this paper we describe a smart building start (SBS) algorithm that considers multiple zones in a building to determine individual schedules for room controllers as well as the central systems based on solving a simple optimization problem. Application of the SBS algorithm to multiple interconnected systems enables a staggered start-up that minimizes peak loads and also ensures comfort is within a target range with minimal system run time. The SBS algorithm extends the capability of traditional optimal start and is designed to be simple to deploy and robust. Simulation results as well as results from tests in a real building with a VAV system are presented. The presented algorithm is applicable to any type of building with a zonal or multi-zone HVAC system. To function, it needs to be able to change setpoints in rooms and monitor room temperatures, as well as, if desired, turn the central system on or off.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Robust Scheduling of Networked Microgrids for Economics and Resilience Improvement
The benefits of networked microgrids in terms of economics and resilience are investigated and validated in this work. Considering the stochastic unintentional islanding conditions and conventional forecast errors of both renewable generation and loads, a two-stage adaptive robust optimization is proposed to minimize the total operating cost of networked microgrids in the worst scenario of the modeled uncertainties. By coordinating the dispatch of distributed energy resources (DERs) and responsive demand among networked microgrids, the total operating cost is minimized, which includes the start-up and shut-down cost of distributed generators (DGs), the operation and maintenance (O&M) cost of DGs, the cost of buying/selling power from/to the utility grid, the degradation cost of energy storage systems (ESSs), and the cost associated with load shedding. The proposed optimization is solved with the column and constraint generation (C&CG) algorithm. The results of case studies demonstrate the advantages of networked microgrids over independent microgrids in terms of reducing total operating cost and improving the resilience of power supply.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Controlled workplace charging of electric vehicles: The impact of rate schedules on transformer aging
To accelerate adoption of non-residential charging for electric vehicles, sites must maximize utilization of existing electrical infrastructure. In this study we model electric vehicle charging at a workplace using real charging data and evaluate the lifetime of the site’s transformer as the number of charging stations is incrementally increased. We implement and compare a range of control schemes for workplace charging including minimizing the peak load, capping the total load, minimizing bills under different rate structures with time-of-use energy costs and demand charges, and directly minimizing the transformer’s aging. These are compared by the number of vehicles they allow the transformer to support, the transformer’s health, and the operator’s electricity bill. We draw a connection between minimizing the peak load and improving the transformer’s health. We observe that minimizing the electricity bill is the best scheme by both criteria when the bill includes a demand charge; in our experiment it allowed the infrastructure to support over 67% more cars than under uncontrolled charging. To protect the transformer we recommend that demand charges or capacity management be applied to parking lots of charging electric vehicles with high infrastructure utilization, and operators schedule charging to minimize their electricity bills.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Prototype energy models for data centers
Data centers in the United States consume about two percent of the nation’s electricity. Because heat gains from IT equipment drive cooling demand, data centers offer unique opportunities for energy savings. However, no prototype energy model for data centers is available in the suite of existing U.S. Department of Energy’s Commercial Prototype Building Models. Here we present the development of two new data center prototype models and their implementation in OpenStudio and EnergyPlus. The small-size data center model represents a computer room in a building served by computer room air conditioners (CRACs); while the large-sized model represents stand-alone data centers served by computer room air handlers (CRAHs) with a central chiller plant. For each data center model, two levels of IT equipment (ITE) load density were considered, to cover the wide range of IT power density of data centers: 40 and 100 W/ft 2 (430 and 1076 W/m 2 ) for the computer room, and 100 and 500 W/ft 2 (1076 and 5382 W/m 2 ) for the stand-alone data center. All other assumptions, such as building envelope, lighting, HVAC efficiencies and schedules, were based on the minimal requirements of ASHRAE Standard 90.1 at various vintages. We introduced a novel concept of supply and return air approach temperatures to capture the essential effects of non-uniform airflow and temperature distribution in data centers. The approach temperatures were pre-computed by computational fluid dynamics (CFD) simulations for various configurations of ITE loads and airflow containment management in data centers. A new feature was developed in EnergyPlus to implement the approach temperature method. A case study was conducted to demonstrate the use of the data center models. The two data center models cover all U.S. climate zones and can be used to evaluate energy saving measures for data centers, as well as to support development of data center energy efficiency codes and standards.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Energy storage-based packetized delivery of electricity
Systems and methods for Energy Storage-based Packetized Delivery of Electricity (ES-PDE) are disclosed that are radically different from the operation of today's grid. Using ES-PDE, the loads are powered by the energy storage systems (ESS) the majority of the time and only receive packets of electricity periodically to charge the ESSs. Therefore, the grid operators can schedule the delivery of electricity packets to utilize the existing grid infrastructure. Since the customers are powered by the co-located ESSs they are not impacted by the grid operation in short term. Therefore, when grid outages occur, the customers still have power for some time, giving the grid more time to be fully restored.
Nguyen, Tu Anh↗