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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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A fact sheet of best practices and guidelines around HVAC, exhaust systems, BAS, elevators, and space use for retail operators.
Laboratories are often overlooked in demand flexibility research due to constraints on their operations as mission critical facilities, despite the major role they play in an organization's emissions. Laboratories consume 3-4 times more energy than a typical office building and are commonly the largest energy users on any campus. Consequently, most laboratories in the United States are significant contributors to their organization's carbon footprint if their energy needs are met through the combustion of fossil fuels. As part of the initiative to decarbonize laboratories, this report documents an analysis on specifically grid-interactive efficient building (GEB) opportunities for reducing energy costs and emissions associated with laboratory operations. The goal of this initiative was to provide a case study and guidance on how to use OpenStudio and REopt as modeling tools for GEB technologies and strategies in laboratory environments across different climate zones in the United States. The analysis found that efficiency-based GEB strategies had the most significant impact on laboratory operations, while load-shedding and load-shifting GEB strategies produced smaller results. The culmination of these approaches applied across all five climate zones generated on average: 1) 28% energy cost savings and 30% greenhouse gas (GHG) emissions reductions, and 2) 4% enhanced energy cost savings under a time-of-use (TOU) pricing schedule compared to traditional pricing schemes. Grid-interactive efficiency building measures were found to produce the greatest energy savings in both electricity and natural gas, particularly in regions with high electrical loads, such as warm climates for cooling. Laboratories that had high levels of natural gas consumption, meanwhile, experienced the greatest emission reductions. The report concludes with an analysis on the opportunities for flexible loads in lab spaces and how small-scale measures in addition to opaque pricing structures for peak demand could become barriers to demand flexibility planning. The report also explores how electrifying laboratory buildings with heat pumps could reduce energy costs and GHG emissions.
OpenStudio®-MCP is a Model Context Protocol (MCP) server that lets AI assistants perform building energy modeling through natural language. Rather than requiring users to learn the OpenStudio® SDK, EnergyPlus® scripting, or Ruby/Python automation, the server translates conversational requests into sequences of tool calls that create models, design HVAC systems, run simulations, and extract results — all within a single chat session. The server's 124 tools are organized into a skills architecture where each skill encapsulates a domain of building energy modeling (envelope, HVAC, loads, weather, simulation, results) behind typed, LLM-friendly interfaces. High-leverage operations like applying ASHRAE 90.1 baseline systems or generating standards-compliant typical buildings are exposed as single tool calls that internally wire dozens of OpenStudio® objects. Bundled measures from ComStock™ and Openstudio® -common-measures-gem are wrapped with dedicated tools and typed arguments rather than exposed through a generic measure interface, so AI models get consistent, error-resistant recipes without needing to discover measure arguments at runtime. A key design decision is structured results extraction: six SQL-based tools return surgical ~300–1,000 token responses (end-use breakdowns, envelope summaries, HVAC sizing, timeseries data) instead of requiring the AI to parse ~100K-token raw HTML reports, making iterative design exploration practical within context window limits. The codebase is designed as a reference implementation — explicit, well-commented, and modular — so that other simulation engines (EnergyPlus® standalone, TRNSYS, DOE-2) can use it as a template for building their own MCP servers.
This guide was developed with partners throughout the United States to demonstrate how implementing district-scale high-performance strategies can be successful and scalable approaches to achieving deep energy savings that increase affordability, improve resilience, reduce emissions, and foster economic development. This document serves as a framework for districts, campuses, and communities, illustrating an iterative process of building support for, planning, and implementing high-performance districts by engaging stakeholders, setting aggressive energy goals, completing technical and financial planning, and implementing a high-performance energy master plan. The information in this guide is based on a 3-year U.S. Department of Energy Zero Energy District Accelerator and a range of real-world examples of emerging high-performance districts. It is particularly useful for architects, planners, engineers, local government agencies, and real estate developers in the early phases of planning a district with high-performance or other deep energy goals. For the purposes of this guide, a high-performance district is a multibuilding development that achieves aggressive energy and related goals such as zero energy, carbon neutrality, sustainability, ultra-efficiency, etc. High-performance districts optimize energy efficiency to reduce energy loads and use renewable energy resources to meet the remaining loads whenever possible. The Energy Independence and Security Act of 2007 defines a high-performance building as “a building that integrates and optimizes on a life cycle basis all major high-performance attributes, including energy conservation, environment, safety, security, durability, accessibility, cost-benefit, productivity, sustainability, functionality, and operational considerations.” High-performance districts are collections of such buildings that take advantage of the synergies available when energy consumption and production are considered at a district level rather than one building at a time.
Optimizing the placement of photovoltaic (PV) panels on residential buildings has the potential to significantly increase energy efficiency benefits to both homeowners and communities. Strategic PV placement can lower electricity costs by reducing the electricity fed from the grid during on-peak hours, while maintaining PV panel efficiency in terms of the amount of solar radiation received. In this article, we present a framework that identifies the ideal location of PV panels on residential rooftops. Our framework combines energy and environmental simulation, parametric modeling, and optimization to inform PV placement as it relates to and affects the entire community (in terms of both energy use and financial cost), as well as individual buildings. Ensuring that our framework accounts for shading from nearby buildings, different utility rate structures, and different buildings’ energy demand profiles means that existing communities and future housing developments can be optimized for energy savings and PV efficiency. The framework comprises two workflows, each contributing to optimal PV placement with a unique target: (a) maximizing PV panel efficiency (i.e., solar generation) and (b) minimizing operational energy cost considering utility rate structures for operational energy. We apply our framework to a residential community in Fort Collins, Colorado, to demonstrate the optimal PV placement, considering the two workflow targets. Here, we present our results and illustrate the effect of PV location and orientation on solar energy production efficiency and operational energy cost.
The rapid adoption of electric vehicles (EVs) has resulted in significant new household electric loads that have the potential to change how energy costs are incurred by homeowners and the landscape of utility operations and energy infrastructure. Whereas adoption patterns and magnitudes of residential building and EV charging loads are influenced by distinct factors, the loads themselves are tightly coupled with the behavior of the individual occupants and EV owners.
The growing deployment of utility-scale photovoltaic (PV) systems has increased the importance of techno-economic modeling operational photovoltaic (PV) systems for predicting energy yield, optimizing asset management, and informing financial decisions. Through a systematic review of literature and current industry practices, we review the different common modeling practices of a system's configuration and age, performance and degradation, operation and maintenance (O&M), while also focusing on specific considerations for repowering, revamping, and decommissioning. Building on the synthesis, we develop a structured framework for techno-economic modeling of operating PV systems that integrate performance and degradation analysis, a decommissioning and repowering cost model that estimates the system's end-of-life costs to reduce uncertainty quantifications and improve consistency across the sector. This research contributes to improved modeling methodologies and potentially to reduced financial performance requirements by providing practitioners with input resources and practical approaches to estimate performance, degradation, and costs associated with continued operation, revamping, repowering, or decommissioning decisions.
ASHRAE Standard 241’s requirements can make indoor spaces more resilient to the spread of airborne infectious diseases. Buildings that comply with ASHRAE Standard 241-2023, Control of Infectious Aerosols,1 will have the capacity to respond during times of elevated risk with systems that provide the necessary equivalent clean airflow for infection control (VECAi). To reduce risk effectively, these systems need to operate properly. This column explores Standard 241’s requirements for operations and maintenance in high-risk times (infection risk management mode or IRMM) and the importance of creating a Building Readiness Plan.
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College buildings have unique characteristics compared with school buildings. Therefore, defining the realistic occupancy schedule in a prototype college building has significant research opportunities. In this study, the actual operating schedules of each space type were collected and generated based on the class reservation schedule and compared with the previous reference schedule (primary/secondary school). Here, the schedules were analyzed for their effect on the OpenStudio prototype college building model. The findings highlight that the use of a typical school building schedule in a college building impairs the granularity of information. The analysis shows significant differences between the previous occupancy schedule and the updated occupancy schedule of the college building, leading to a considerable decrease in occupancy density. Furthermore, the effect of these occupancy pattern changes on the prototype building model is examined. The variations were observed in minimum ventilation requirements, the average mechanical ventilation rate, and energy consumption attributed to changes in occupancy density.
Increasing energy demand and rising peak loads present significant challenges for energy management in commercial and institutional settings. As climate change drives greater cooling needs, central plants must navigate the complex tradeoffs between operational efficiency, cost control, and grid stability. Thermal energy storage (TES) systems offer a viable solution by shifting energy consumption from peak to off-peak periods, thereby reducing peak demand, lowering utility expenses, and improving grid resilience. However, the success of TES implementation hinges on appropriate system sizing, effective control strategies, and alignment with local utility rate structures. This article presents a techno-economic analysis of integrating a chilled water TES system into the central plant at California State University, Dominguez Hills. Drawing on historical load profiles and utility tariffs, we assess three TES sizing approaches and their corresponding control strategies from both energy and economic perspectives. This article utilizes a model-based approach to assess the impact of TES sizing and control strategies on the techno-economic feasibility of integrating TES into an existing central plant. The models employed for this analysis were calibrated using 4 years of historical data. Here, the results demonstrated that utility tariffs and the campus's operational profiles dictate the most feasible sizing and control methods. The findings offer valuable insights for institutions and commercial building managers exploring sustainable energy solutions. By demonstrating how optimized TES strategies can improve operational efficiency while achieving financial savings, this study highlights the potential for TES to align performance with cost effectiveness in real-world applications.
ABSTRACT Monoclonal antibodies (mAbs) represent a majority of biotherapeutics in the market today. These glycoproteins undergo posttranslational modifications, such as N‐linked glycosylation, that influence the structural & functional characteristics of the antibody. Glycosylation is a heterogenous posttranslational modification that may influence therapeutic glycoprotein stability and clinical efficacy, which is why it is often considered a critical quality attribute (CQA) of the mAb product. While much is known about the glycosylation pathways of Chinese Hamster Ovary (CHO) cells and how cell culture chemical modifiers may influence the N‐glycosylation profile of the final product, this knowledge is often based on the final cumulative glycan profile at the end of the batch process. Building a temporal understanding of N‐glycosylation and how mAb glycoform composition responds to real‐time changes in the biomanufacturing process will help build integrated process models that may allow for glycosylation control to produce a more homogenous product. Here, we look at the effect of specific nutrient feed media additives (e.g., galactose, manganese) and feeding times on the N‐glycosylation pathway to modulate N‐glycosylation of a Herceptin biosimilar mAb (i.e., Trastuzumab). We deploy the N‐GLYcanyzer process analytical technology (PAT) to monitor glycoforms in near real‐time for bench‐scale bioprocesses operated in both fed‐batch and perfusion modes to build an understanding of how temporal changes in mAb N‐glycosylation are dependent on specific media additives. We find that Trastuzumab terminal galactosylation is sensitive to media feeding times and intracellular nucleotide sugar pools. Temporal analysis reveals an increased desirable production of single and double galactose‐occupied glycoforms over time under glucose‐starved fed‐batch cultures. Comparable galactosylation profiles were also observed between fed‐batch (nutrient‐limited) and perfusion (non‐nutrient‐limited) bioprocess conditions. In summary, our results demonstrate the utility of real‐time monitoring of mAb glycoforms and feeding critical cell culture nutrients under fed‐batch and perfusion bioprocessing conditions to produce higher‐quality biologics.
Achieving the goals of green buildings critically depends on the fault-free operation of heating, ventilation and air conditioning and refrigeration (HVAC&R) systems. However, faults frequently occur in these systems, causing a range of negative consequences, including increased energy consumption, diminished operational performance, compromised indoor environmental quality, higher operational costs, and shortened system lifespan. The evaluation of fault behaviors and impacts plays a critical role in revealing fault characteristics and consequently supports many research areas, including the design of the high-performance equipment, development of fault detection and diagnostics (FDD) and robust control approaches, as well as the enhancement of maintenance decision-making activities. This paper systematically reviews 112 research publications that reported the analysis and evaluation of fault behaviors and impacts in HVAC&R systems over the past thirty years. Here, we designed a review approach to address five crucial research questions, namely: 1) the objectives of analysis and evaluation of fault behaviors and impacts, 2) data sources, 3) equipment/system types and fault types, 4) evaluation methods including evaluation measures and associated metrics, and 5) challenges and future directions in the research on evaluating of fault behaviors and impacts. In-depth discussions on these questions help bridge the gap between the evaluation of fault behaviors and impacts and their practical applications, such as the development of high-performance systems, fault models, FDD methods, and maintenance decision-making tools within the HVAC&R FDD domain.
The CyDER project aimed at developing an open-source, modular and scalable co-simulation platform for power grids with large shares of Distributed Energy Resources (DERs). The project partners are the Lawrence Berkeley National Lab (LBNL), Lawrence Livermore National Lab (LLNL), PG&E, SolarCity, and ChargePoint. The prime recipient is LBNL; SolarCity and ChargePoint were partners for the project’s first two years. Increased DER integration introduces a number of challenges in power grid operation including a more dynamic interaction between the transmission grid and distribution grids, and increased modeling complexity. Although specialized software exists to precisely model different components of the power system, it is far from trivial to integrate all various models and perform a holistic simulation. Instead of replicating all models in a common simulation program, a commonly accepted approach to tackle this model diversity is to couple third-party simulators and models through a co-simulation platform that coordinates information exchange among the various components. Following this line of research, this project’s objective was to develop a co-simulation platform based on a widely accepted industrial standard called Functional Mockup Interface (FMI). Within this process, the project developed models compliant with the FMI standard, called Functional Mockup Units (FMUs), and used them to perform various operational and planning power system analyses. Relying and building upon an industrial standard is the main differentiation of this project compared with previous or parallel efforts in the co-simulation area. Particular emphasis was put on delivering software utilities to facilitate setting up and running co-simulations by end-users. Furthermore, a strong aspect of this project is demonstrating that co-simulation techniques can be used to perform Hardware-in-the-Loop (HIL) simulations that couple software components (e.g., simulated models) with hardware components (e.g., real devices such PV systems and batteries). The long-term goal of CyDER project is to help establish FMI as a powerful standard for co-simulation and promote adoption by electric utilities and other interested stakeholders. The main accomplishments of the project include the development of several FMUs including distribution and transmission grid models, PV inverters with Volt/Var/Watt controllers, batteries, and predictive optimal controllers. Additionally, a unique software package was developed, called SimulatorToFMU, which is capable of exporting any Python-driven simulator or Python script as an FMU. This is an important contribution towards establishing FMI as one of the main co-simulation standards, because more and more third-party programs for sub-system modeling and simulation are delivered with Python APIs. The CyDER platform was used to perform PV hosting capacity analyses in real utility feeders with and without smart inverter controls, battery storage, and EV charging. Smart inverter controls include conventional Volt/Var/Watt controls for reactive power support and active power curtailment, but also predictive controls that optimize the charging and discharging profile of the battery connected on the DC side in order to minimize the customer’s economic benefit. Finally, an important result of this project is delivering an experimental setup that consists of residential-scale PV inverters with battery storage, a real-time grid simulator with an ideal voltage source as grid emulator, and micro Phasor Measurement Units (PMUs). All these components and additional software modules are coupled to one another using the FMI standard and can be co-simulated with the CyDER platform.
Ukraine’s district heating (DH) system is an essential resource for the country and has the potential to provide efficient, local, and renewable energy to a large share of the population. However, inefficient regulation and management have caused the sector to experience a vicious cycle of financial, operational, and technological problems. Overcoming these challenges and building a sustainable DH system requires comprehensive reforms, which could attract significant investment, improve the quality of services, and increase the efficiency of DH. One of the key elements of a comprehensive reform program should be a comprehensive reform of the tariff system. The purpose of this report is to provide analysis of European models for tariff regulation and recommendations for reforms to Ukraine’s DH tariff system. The report presents several case studies from European countries, followed by analysis of the current tariff system in Ukraine and barriers to effective regulation. Based on these findings, the report proposes actions Ukraine could take to improve the tariff regulatory system and promote a sustainable DH sector.
Scorpius is an electron accelerator designed to take x-ray images of weapon components (Flash Radiography). The final design was completed in January 2022. The accelerator start-up will begin in 2025. The Weapons Labs and NNSS are building the Scorpius Accelerator. The NNSS will commission, operate, maintain and upgrade Scorpius.
Energy efficient heat pump water heaters (HPWHs) reduce customer energy costs; grid-connected controls further increase HPWH value by enabling energy storage and shifting demand to cheaper, off-peak periods. However, a HPWH’s first cost premium can put it out of reach for low-income customers. This paper will present results of an ongoing study exploring the benefits of load shifting HPWHs for 24 low-income households, aiming to support increased product deployment in this demographic. The study uses EcoPort modules to shift HPWH load for a study sample consisting primarily of low-income adults and seniors in North Carolina. Building upon prior studies, the study’s HPWH operating schedules are designed to maximize shifted energy and minimize participant electricity costs based on local time-of-use rates. The study documents load profiles of grid-connected HPWHs in a less-studied demographic group and explores how certain groups may have particularly flexible loads due to their unique usage profiles. The results are relevant for HPWH product performance in the Southeast. The study will quantify HPWH load shifting performance during North Carolina’s hot summer, temperate shoulder, and occasionally sub-freezing winter seasons, and the study includes installations in conditioned, semi-conditioned, and unconditioned spaces. Finally, study results will also explore how controlled HPWHs can provide value to the regional grid by reducing seasonal peaks via demand response. Lessons learned include HPWH acceptance for low-income and senior users, best practices for maintaining HPWH connectivity among users without prior product experience, and strategies to leverage remote monitoring to ensure optimal operation and enhance HPWH reliability.
A summary of NLR's stewardship of the nationally unique Energy Systems Integration Facility (ESIF) highlighting performance metrics, capability upgrades, and examples of R&D impact. 2025 brought a national focus on energy and ESIF is meeting the moment. All eyes are on data centers and domestic manufacturing and bringing the benefits of artificial intelligence to power system planning and operations. In step with national priorities, ESIF is building out capabilities that advance secure, reliable, and affordable power. ESIF hosted 190 multidisciplinary research projects, 855 high-performance computer users, and collaborated with 81 partners from industry, academia, research, and federal agencies. These research projects resulted in an AI method for detecting high-impedance faults with 90% accuracy, a grid controls demonstration in Connecticut, power quality validation of CorePower's flagship inductor, and a cybersecurity assessment of potential rogue capabilities in digitally connected energy devices. Facility infrastructure improvements enhanced the thermal research network, the SCADA system, the cyber range, power hardware-in-the-loop testing, and more. With support from the U.S Department of Energy (DOE), the ESIF laboratories continue to deliver leading solutions for secure, reliable, and affordable power.