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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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DOE OSTI2024

Sound at Scale: Characterizing Impacts of Noise Ordinances on the Onshore Wind Energy Technical Potential for the United States

Recent surveys have documented the rapid rise of sound ordinances across state and county jurisdictions, which has become crucial for wind energy siting. However, the lack of information on ordinances and computational challenges in turbine sound modeling create uncertainties regarding how evolving policies may affect resource potential and clean energy objectives. Therefore, we develop an approach to evaluate wind turbine sound profiles at millions of locations across the U.S. and translate them into setback distances for every residential structure. Compared to a baseline reference scenario, we find a 7% reduction in the national wind energy capacity potential when accounting for counties with existing sound ordinances. Additionally, when expanding the surveyed sound ordinances nationwide, we observe a potential loss of 53% of the national wind capacity under the most stringent ordinances, with a disproportionate share of this lost capacity coming from high-quality and low-cost wind resource. This work reveals that neglecting sound ordinances results in a significant overestimation of wind resource potential and highlights the important trade-offs between increased wind energy deployment to meet target decarbonization goals and the social/environmental impacts of this deployment that must be considered.

aeroacoustics↗
DOE OSTI2024

Capacity Density Considerations for Floating Offshore Wind Farms in Ultradeep Waters

Capacity density describes the concentration of wind energy development in an area and is often specified in terms of megawatts-per-square-kilometer (MW/km2). Understanding capacity density trends in wind energy projects helps to inform both energy system and spatial planning efforts. Borrman et al. (2018) and Mulas Hernando et al. (2023) analyze capacity density trends for fixed-bottom offshore wind farms in Europe and the United States, respectively, and Cooperman et al. (2022) explores how floating offshore wind mooring technology choices may impact wind plant layout through setbacks from lease area boundaries in waters up to 1,300 m deep. Technical challenges facing floating offshore wind development in ultradeep waters (beyond 1,300 m) could impact achievable capacity densities, with potential implications to marine spatial planning and project economics. When compared to fixed-bottom commercial-scale wind farms, mooring system footprints from floating offshore wind systems can constrain capacity density in some circumstances. In this study, we conduct an initial investigation of how taut mooring configurations may constrain floating offshore wind turbine placement and estimate capacity density for representative floating wind plants in generic lease areas. In addition, we explore floating wind plant capacity density drivers in ultradeep waters by characterizing area utilization for a range of lease area characteristics. This analysis highlights the primary challenges that floating offshore wind systems may encounter in achieving capacity densities comparable to commercial-scale fixed-bottom projects at ultradeep water depths, from a technical standpoint.

capacity density↗
DOE OSTI2025

Data-driven modeling of dynamic occupant thermostat override behavior for demand response applications

Buildings consume nearly 40% of global energy and produce similar emissions. Whiletechnological advances address efficiency, occupant behavior causes energy use variations up to 300% between identical buildings. This gap between predicted and actual building performance impacts building design, operations, and grid demand management programs. Through analyses of smart thermostat data from 1,400 single-occupant homes, the researchdemonstrates that occupants respond to 8°F thermostat setpoint changes within a median of 15 minutes, while 2°F changes trigger responses within a median of 30 minutes. This highlights an understudied temporal relationship between thermostat setbacks and response time of occupant behaviors. Models of such behavior dynamics are required to incorporate occupant impacts into building performance simulation. A key contribution of this dissertation is the Thermal Frustration Theory (TFT), which positsthat thermal discomfort driven behaviors are caused by the time-accumulation of discomfort, not simply a temperature deviation threshold or a delay from an initiating event. Using a dataset of 634 thermostats, each with 25+ manual setpoint changes, a comparative analysis of TFT and comfort zone and a delayed response theories demonstrated that personalized TFT models better predict when manual setpoint change occur. This was measured by the area under the curve statistical measure (AUC); all three models perform similarly by a Matthews Correlation Coefficient measure. Higher AUC performance is especially important for modeling occupant behavior in demand response programs where false negatives of rare occupant interactions could adversely affect grid stability. EnergyPlus based simulations were conducted with TFT-derived occupant models, demonstrating the ability to identify parameters of known TFT models from only data observable with smart thermostats, even under the presence of noise from routine overrides. Overall, the dissertation highlights that thermostat interactions are neither static,instantaneous, nor driven solely by the environment. Instead, temporal accumulation of discomfort and routine-based behavior play important roles. The methodology and results offer a pathway towards more accurate modeling of human-building interactions for policy assessment, building design, and demand response programs.

Sharma, Kunind [Northeastern University] (ORCID:00↗
DOE OSTI2020

Impact analysis of personalized thermostat demand response

Demand response (DR) aims to curtail peak electric load to avoid running inefficient power plants, reduce costly transmission capacity increases, and improve grid reliability. One method of DR for residential settings involves the utility or third part remotely adjusting thermostat temperatures. Cooling setpoints may be increased 2°F – 6°F for hours, irrespective of occupant comfort. To maintain their comfort, occupants override these setpoint changes impacting the reliability of DR services provided to the grid. This paper presents a preliminary impact analysis of replacing the current DR approach of uniform thermostat setbacks for an entire population with personalized and context aware DR based on a dynamic model of occupant thermal comfort behavior. Over 151k interactions with ecobee thermostats are analyzed to predict the impact of such personalized DR on overrides, energy curtailment magnitude, and reliability.

Kane, Michael↗
DOE OSTI2026

Solar and Battery Storage Permitting and Siting Requirements - Solar Prize Round 7 (CRADA Final Report)

The purpose of this research project was to aggregate zoning and permitting data for utility-scale solar PV and battery energy storage systems. The ultimate goal of this collaboration is to lower solar and battery energy storage system soft costs by streamlining regulatory due diligence and reducing the burden of conducting feasibility assessments for solar and storage systems. The below sections describe the specific research completed by NLR (the contractor) in furtherance of the agreement with Vanox (the participant).

14 SOLAR ENERGY↗