Recent lbnl_et items

Least-cost Optimal Distribution Grid Expansion (LODGE): Utility Pilots

Mon, 14 Sep 2026 00:00:00 +0000

The Least-cost Optimal Distribution Grid Expansion (LODGE) model provides the optimal portfolio of distribution system upgrades—e.g., voltage regulators, feeder reconductoring, transformer upgrades and non-wires alternatives (NWA), such as strategic siting of storage and distributed generation—to interconnect distributed energy resources (DERs) and enable load growth. It can be used to assess grid infrastructure costs and explore policy and regulatory solutions for distribution planning and DER valuation.

In 2025, Berkeley Lab conducted three pilot analyses to validate LODGE results with empirical utility data before the model’s first release in 2026. The pilots, done with utilities in Washington, Colorado, and New Mexico, provide examples that illustrate how the model works, what it can do, and the value of the analysis.

Author Correction: US oil and gas system emissions from nearly one million aerial site measurements

Fri, 11 Sep 2026 00:00:00 +0000

Correction to: Naturehttps://doi.org/10.1038/s41586-024-07117-5 Published online 13 March 2024 In the version of the article initially published, several errors were present and have been corrected in the HTML and PDF versions of the article and Supplementary Information. The main results, conclusions, and our interpretations of the data remain unchanged. See the new Supplementary Information Section S15 for a more detailed description of the errors corrected and the resulting effects on the analysis. Data processing and methods corrections Overflight count correction: We previously used pre-computed source coverage data for some Carbon Mapper campaigns that was computed differently than was required for our analysis. We have re-computed Carbon Mapper source coverage based on flightline polygons and source coordinates. Transition point computation, well sites: The updated version now correctly compares the cumulative emissions distribution of simulated well site emissions with...

A review of United States energy-only generator interconnection service policy and considerations for reform

Fri, 11 Sep 2026 00:00:00 +0000

Grid interconnection has emerged as a significant obstacle to the development of new electricity resources. There is growing interest in energy-only interconnection, which is an interconnection service option meant to allow the interconnection of new generators without ensuring their energy deliverability during all hours through the transmission system to customers. This approach potentially avoids upfront congestion-related transmission upgrades but could increase curtailment risk. Interest in energy-only interconnection is shaped by incomplete understanding of how interconnection policy functions in different jurisdictions, a knowledge gap that makes it difficult to determine how energy-only interconnection might be better used or re-designed. In this paper, we provide a regulatory review of energy-only interconnection in U.S. interconnection policy and practice, identifying jurisdictions in which rules are close to -or farther from-the theoretical concept of energy-only interconnection...

U.S. ESCO Industry Report: Industry Size and Recent Market Trends, 2022- 2024

Fri, 11 Sep 2026 00:00:00 +0000

The latest edition of the U.S. Energy Service Company (ESCO) Industry Report by Lawrence Berkeley National Laboratory (LBNL) finds that the U.S. ESCO industry continues to show strong growth. The report draws from ESCO industry reported revenue data for the 2022-2024 period, detailing the current size and characteristics of the U.S. ESCO industry. Following 20 years of ESCO industry reports, the 2024 report explores significant revenue trends across market segments, geographic regions, ESCO size, financing structures, and business activities. New analysis in this report outlines customer priorities and non-energy benefit drivers of Energy Savings Performance Contract projects, adjusted revenue analysis detailing the impacts of inflation on industry growth, and project challenges by market segment.

Evaluating technology upgrades as a complement to traditional bill assistance programs

Thu, 10 Sep 2026 00:00:00 +0000

State programs to improve energy affordability and reduce energy burden (the share of income spent on energy) could mitigate concerns about rising electricity prices. Many states offer bill assistance and rebates for weatherization and rooftop solar to income-qualifying households. Here, we analyse how these approaches may complement one another to improve energy affordability. Results illustrate trade offs between program costs and energy burden reduction, as well as between a program’s upfront and ongoing costs. Generally, the three strategies complement one another to improve energy affordability at lower net present cost than bill assistance alone, with varying effects across regions. Weatherization can reduce the solar installation capacity needed, and both together can reduce or eliminate ongoing reliance on bill assistance. Under full uptake among cost-effective households, fully rebated weatherization and solar rebated at $0.48/Watt, combined with bill assistance, yield...

A Signal‐Derived Retrieval Reduces Bias in TEMPO NO2

Wed, 9 Sep 2026 00:00:00 +0000

Abstract Satellite measurements of are widely used for investigations of emissions, pollution exposure, and photochemical ozone production. The most commonly available data products compromise on accuracy and spatial resolution in favor of lower compute time. In addition to limited spatial resolution, inaccurate modeling of winds and misrepresentation of the lifetime contribute to large systematic errors in the satellite retrievals that depend on these modeled outputs. We introduce a signal‐derived retrieval (SDR) for Tropospheric Emissions: Monitoring of Pollution (TEMPO) which derives instrument‐resolution a priori profiles from measured slant column densities. This approach enables fast reprocessing of TEMPO data and removes the gradient smoothing caused by low resolution priors and systematic errors in models. The SDR product reduces the negative bias of TEMPO total against Pandora reference measurements by , with a larger impact on the tropospheric column. This bias correction...

Ten questions on digital twins of buildings for transforming building operations

Wed, 9 Sep 2026 00:00:00 +0000

Buildings are becoming ever more complex to manage during operations, driven by increasing dynamics in energy demand, intermittent on-site power generation, and distributed energy resources, compounded by variable grid pricing signals and the rising threat of extreme weather events causing large-scale power outages. To achieve optimal performance in energy efficiency, demand flexibility, energy resilience, and occupant comfort, new methods and tools are essential for transforming design and operations across a building’s entire life cycle. Digital Twins (DTs), enabled by recent advances in ubiquitous sensing, big data, cloud computing, and AI, offer a transformative approach to creating a real-time, bi-directional digital counterpart of a physical building. This paper presents ten critical questions highlighting the most foundational issues underpinning the successful deployment of digital twins for buildings. The questions are holistically structured around three core themes...

Interconnection Timelines and Costs for Distributed Energy Projects in the United States (2000-2025)

Fri, 4 Sep 2026 00:00:00 +0000

These slides summarize and explain empirical data on interconnection timelines and costs for distributed energy projects connected to U.S. utility distribution systems. The study explores how interconnection metrics vary across states, project sizes, technology types, and over time to indicate progress toward simple, fast, and affordable interconnection. Data encompasses 188 utilities in 24 states. Project types include biomass/biofuels, coal, hydropower, natural gas/oil, solar, storage, wind, hybrid, and

Field Validation of Electrochemical Water Filtration System on an Open Loop Cooling Tower at Toyota Motor Manufacturing Plant in Blue Springs, Mississippi

Thu, 3 Sep 2026 00:00:00 +0000

The U.S. Department of Energy Industrial Efficiency and Decarbonization Office’s Industrial Technology Validation (ITV) program aims to identify and demonstrate the performance of new, emerging, and underutilized technologies in the industrial sector to help inform decisions towards accelerating commercialization and deployment. One such ITV project is to demonstrate the performance of an electrochemical water treatment technology on a cooling tower at an automotive plant. Cooling towers are vital equipment for dissipating heat from industrial processes. However, they face challenges related to scaling, corrosion, and the growth of biological contaminants. Effective cooling tower water filtration and treatment is essential to reduce these contaminants, along with other total suspended solids (TSS) and total dissolved solids (TDS) in the system. Various treatment systems, such as sand-based filters, centrifugal separators, and disc filters, offer distinct advantages and limitations....

Technical assessment of the negative solar radiative forcing and atmospheric cooling benefits of surface brightening projects

Thu, 3 Sep 2026 00:00:00 +0000

Brightening the Earth’s surface can increase the outflux of sunlight to space. This diminishes the net (downward minus upward) solar flux into the Earth’s radiative system, providing negative solar radiative forcing that can cool the atmosphere. We are quantifying the extent to which surface-brightening projects, such as installing solar-reflective roofs and pavements, can raise bottom-of-atmosphere (BOA) albedo, increase top-of-atmosphere (TOA) solar outflux, and reduce regional and global atmospheric temperatures. We compared four approaches to assessing BOA albedo: roof- or pavement-product documentation; local measurements with an albedometer (back-to-back pyranometers); extrapolation from extended-color aerial images (blue, green, red, and near-infrared); and multispectral satellite images sharpened by convolution with aerial images, selecting the last. We developed a technique to calculate the atmosphere’s upward solar transmittance anywhere in the Earth’s tropical and temperate...

Towards robust laser beam propagation in atmospheric turbulence

Tue, 1 Sep 2026 00:00:00 +0000

High-fidelity optical propagation through the atmosphere is essential for free-space optical technologies, including laser-based remote sensing and optical communication. However, atmospheric turbulence severely distorts beams and compromises system performance. In this work, we employ hypergeometric-Gaussian (HyGG) vortex beams as probes to characterize and mitigate atmospheric turbulence. Using over 250,000 experimental and simulated frames, we show that refining the power spectrum density (PSD) can reduce numerical prediction errors by up to 79.8%. Concurrently, experimental observations supported by numerical simulations demonstrate that HyGG beams exhibit superior turbulence resilience across multiple metrics compared to conventional Gaussian beams, particularly in their ability to withstand over 5 times stronger turbulence while maintaining similar intensity fluctuations. These dual investigations, on both turbulence mitigation and robust beam solutions, converge to form...

Selecting Critical Scenarios of DER Adoption in Distribution Grids Using Bayesian Optimization

Tue, 1 Sep 2026 00:00:00 +0000

We develop a new methodology to select scenarios of DER adoption most critical for distribution grids. Anticipating risks of future voltage and line flow violations due to additional PV adopters is central for utility investment planning but continues to rely on deterministic or ad hoc scenario selection. We propose a highly efficient search framework based on multi-objective Bayesian Optimization. We treat underlying grid stress metrics as computationally expensive black-box functions, approximated via Gaussian Process surrogates and design an acquisition function based on probability of scenarios being Pareto-critical across a collection of line- and bus-based violation objectives. Our approach provides a statistical guarantee and offers an order of magnitude speed-up relative to a conservative exhaustive search. Case studies on realistic feeders with 200-400 buses demonstrate the effectiveness and accuracy of our approach.

Simple device modification simultaneously enhances indoor passive evaporative cooling power and duration

Tue, 1 Sep 2026 00:00:00 +0000

Passive evaporative cooling from a damp cloth or vessel can be used for localized cooling of perishables such as food and medicine, drinking water, and even people. Such applications have two key objectives, which are normally in tension with each other: minimizing the water consumption rate and maximizing the cooling (steady-state temperature swing between the cool cloth and the warm surroundings). Here, we present a simple device that delivers higher performance in both metrics simultaneously by adding a perforated aluminum foil sheet suspended over a stagnant air layer to thermally shield the evaporating surface while also facilitating mass transfer. Experimental results demonstrate a simultaneous 10%–25% increase in temperature swing and 2–3× reduction in water consumption rate as compared to conventional evaporative cooling. This improvement is achieved through careful modeling to optimize the coupled heat and mass transfer through the airgap (thermally insulating and vapor...

Market participation strategy of hybrid energy resources: A New York ISO case study

Tue, 1 Sep 2026 00:00:00 +0000

Drawing on existing market designs with independent resource participation in electricity markets, this study analyzes participation models for hybrid resources combining renewable generation and storage. Two models are considered: in the first, the components operate independently, with the Independent System Operator (ISO) managing the storage state of charge (SoC); in the second, the hybrid resource acts as an integrated unit, submitting offers as a “black box” and managing its SoC internally. Using a production cost model for the zonal New York Bulk Power System, we evaluate trade-offs in system reliability, market efficiency, and asset profitability. Our results provide several key insights for policymakers, showing that the ISO-managed granular model enhances social welfare through explicit SoC management, while the simpler integrated model is more computationally efficient, but may cause more real-time violations and lower overall profits.

Ultrafast Nanoimaging of Carrier Funneling in Composition-Graded Semiconductor Nanowires

Tue, 1 Sep 2026 00:00:00 +0000

Recent advances in bandgap engineering of low-dimensional semiconductors have enabled high-efficiency carrier transport in miniaturized electronic and optoelectronic devices. The physical properties and functionalities of these materials are governed by complex carrier dynamics coupled with multiple transport mechanisms in tailored band structures. Here, we report ultrafast nanoimaging of carrier funneling and recombination in composition-grade CdS_xSe_1-x nanowires using pump-probe near-field nanoscopy. Leveraging the high resolution of this technique in both space and time, we resolve nanoscale local carrier dynamics along composition-graded nanowires, revealing the local variation of composition-dependent carrier mobilities and lifetimes that significantly differ from their uniform composition counterparts. Furthermore, we demonstrate a length-dependent behavior wherein shorter nanowires exhibit enhanced funneling effects, accelerating carrier...

Joint scheduling of energy, fast and primary frequency response reserves in integrated transmission–distribution networks

Tue, 1 Sep 2026 00:00:00 +0000

Inverter-based distributed energy resources (DERs) connected to distribution networks (DNs) can provide fast frequency support, but their reserve deliverability depends on feeder constraints and differs from synchronous primary frequency response (PFR). Existing transmission–distribution coordination studies usually treat reserve generically or neglect feeder-level feasibility, while frequency-security scheduling studies rarely represent distribution feeders explicitly. This paper develops a bi-level day-ahead scheduling framework for integrated transmission–distribution networks that jointly clears energy, transmission-side PFR, and distribution-side fast frequency response (FFR) under exogenous hourly inertia and largest-loss inputs from an external unit commitment (UC) schedule. The transmission problem is modeled with DC-optimal power flow (OPF) and closed-form second-order cone (SOC) frequency-security constraints, whereas each DN is represented by a reserve-aware branch-flow...

A model for selecting the best sustainable airport technology alternatives

Tue, 1 Sep 2026 00:00:00 +0000

Air transport is a continually expanding industry, a fact that has become even more evident with the recovery of the aviation industry post-COVID-19. This expansion amplified energy consumption at airports, which was already significantly high. Airport decision-makers are increasingly focusing on improving sustainability and addressing social, economic, and environmental criteria across airports worldwide. In this article, we propose a decision-making model for identifying a sustainable airport technology solution that minimizes the energy consumption of airport lighting while considering economic, emission, and life-cycle criteria. The proposed model combines data envelopment analysis and multi-criteria decision making techniques. We applied the model to the Dallas/Fort Worth International Airport (DFW) as a case study, considering eight lighting technology solutions, each with five luminous flux alternatives. Our model identified the best lighting technology solution for DFW...

Endogenous Interface Pricing for Consistent Transmission–Distribution Co-Optimization With Discrete Distribution Controls

Tue, 1 Sep 2026 00:00:00 +0000

This paper proposes an endogenous interface pricing model for day-ahead transmission–distribution co-optimization that co-determines the interface locational marginal price (LMP) and the transmission–distribution exchange, ensuring price–dispatch consistency while optimally scheduling discrete distribution controls. The formulation couples a DC optimal power flow (OPF) with a branch-flow AC OPF that schedules distributed energy resources (DERs), tap-changer settings, capacitor banks (CBs), and multi-period energy storage systems (ESSs) under feeder voltage and current limits, and is solved as a mixed-integer second-order cone program (MISOCP). In a T14–D33 system, coordinated device scheduling recovers about 90% of the distribution-to-transmission export achievable in a reference case that ignores distribution network (DN) limits, while satisfying a 1.05 p.u. voltage upper bound. In a T39–D34/D37/D123 system, a sequential decoupled benchmark produces interface LMP distortions...

Cataloging US state policy patterns towards microgrid deployment

Tue, 1 Sep 2026 00:00:00 +0000

Frequent extreme weather events have called for rigorous and timely efforts for alternative non-wire solutions. These efforts are getting more widespread to offer a perfect alternative as the conventional grid becomes progressively less resilient. One of these solutions is microgrids that can disconnect from the grid and offer grid resilience during an outage. While this technology is still finding its footing in the industry, states across the US are employing policy patterns and forms of instruments to support its deployment. This study includes a systemic review of the US by conducting a binary analysis of all 50 states (including Washington D.C, excluding other US territories) using seven variables. The results show four major policy approaches to microgrids: i) supporting microgrids through a definitive legislative activity leading to further policy action; ii) direct efforts from the public utilities commissions without a concrete legislative push; iii) initiatives from...

Burst delay line for generating ultrashort pulse bursts with interval tunability from femtoseconds to nanoseconds.

Tue, 1 Sep 2026 00:00:00 +0000

Ultrashort burst laser pulses are important for applications in laser processing and spectroscopy. However, existing burst generators face limitations in pulse time interval tunability and coaxiality. Here, we present a burst pulse generator that delivers coaxial ultrashort pulses with tunable pulse time intervals using a single translation stage. The constructed system produced eight femtosecond pulses with uniform intervals tunable from 100 fs to 1.93 ns, equivalent to burst-internal repetition rates spanning 10 THz to 0.52 GHz. We further demonstrated interval-dependent plasma emission in air filamentation, providing a compact platform to study burst-laser-induced phenomena.

Nanoscale Compositional and Strain Gradients Enable High‐Speed and Amplitude‐Resolved Pyroelectric Sensing

Tue, 1 Sep 2026 00:00:00 +0000

The frequency response of pyroelectric sensors is fundamentally governed by thermal time constant (τ_th, determined by thermal mass and thermal conductance) and electrical impedance arising from film capacitance and readout circuit. Conventional bulk LiTaO₃ detectors are optimized for high responsivity at low modulation frequencies (0.1-10 Hz), possessing a large τ_th that thermally averages rapid temperature oscillations at elevated modulation frequencies, limiting fidelity in resolving dynamic varying thermal signals. Here, compositional and strain gradients are introduced into 100-nm-thick relaxor-ferroelectric films reducing τ_th to ≈2 µs and producing built-in potentials (≈1.45 V or 145 kV cm^-1) that enhance the pyroelectric coefficient and suppress the dielectric constant. This enables complementary dual-mode operation by enhancing current-mode electrical responsivity and improving the voltage-mode figure...

Netload Range Cost Curves for Coordinated Transmission-Distribution Planning Under DER Growth Uncertainty

Tue, 1 Sep 2026 00:00:00 +0000

The increasing penetration of distributed energy resources (DERs) requires better coordination between transmission and distribution (T&D) planning to ensure system security and cost efficiency. However, misaligned planning horizons, computational burdens, and privacy concerns hinder effective coordination, leading to either underutilized resources caused by overinvestments or reliability risks due to underinvestment. To address this challenge, we introduce netload range cost curves (NRCCs), a novel approach for managing long-term DER growth uncertainty through T&D coordination, while preserving existing data-sharing and regulatory structures. NRCCs provide pairs of (i) peak substation netload guarantees and (ii) corresponding distribution upgrade options and costs, enabling their seamless integration into transmission planning workflows. To compute NRCCs efficiently, we develop a transmission-aware distribution network planning (TADNP), which is subsequently integrated...

Decision-Dependent Resilience Enhancement Strategy for Distribution Systems Against Endogenous Wildfires

Mon, 31 Aug 2026 00:00:00 +0000

The increasing frequency and severity of wildfires pose significant threats to utility infrastructure and community safety. Wildfires can be ignited due to component failures under extreme weather conditions. System hardening measures aimed at preventing these failures can reduce the probability of endogenous wildfire ignition, introducing decision-dependent uncertainty (DDU). However, existing methods that consider such DDU typically assume independent component failures, neglecting the critical interdependencies between components destroyed by wildfire and those affected by their spread. These interdependencies render such methods inadequate. To address this, we propose a novel formulation that incorporates both wildfire-ignition DDU and a second type of DDU — the interdependency between wildfire-ignited and wildfire-affected components. We develop a two-stage wildfire-preventive decision-dependent resilience enhancement (WDDRE) model for distribution systems. The model optimizes...

Pattern similarity-based phase identification problem formulation for medium voltage distribution networks

Mon, 31 Aug 2026 00:00:00 +0000

In this work, we propose an enhanced phase identification method to support distributed energy resources management in a medium voltage network. The problem is formulated with the objective function of minimizing the sum of the modified Kirchhoff’s Current Law at the branch node and power-current pattern similarity. This combined objective function is then linearized by introducing auxiliary variables and subsequently resolved through Mixed-Integer Linear Programming. A permutation matrix is employed to establish a correlation between the magnitudes of electrical currents across distinct phases, achieved through manipulation based on empirical data. Subsequently, by comparing this matrix with the observed magnitudes of currents, the approach facilitates the deduction and identification of phase information inherent in the electrical signals. Consequently, the permutation matrix functions as decision variables to identify the phases of currents for wye-connected loads, delta-connected...

The global policy landscape of ISO 50001 energy management systems

Mon, 31 Aug 2026 00:00:00 +0000

While many options exist to improve industrial demand-side energy efficiency, energy management systems (EnMSs)—particularly those aligned with ISO 50001—are proven to drive continuous and meaningful energy performance improvements. Governments leverage these EnMSs in their policies to advance national objectives including enhancing industrial competitiveness and achieving environmental goals. Existing research has focused on the impact of EnMSs at the company level, while comprehensive work on EnMSs in a global policy context is lacking. We seek to close this gap by investigating the extent to which current national policies incorporate the utilization of EnMSs, particularly the ISO 50001 standard. Our paper employs a hybrid approach, combining a literature review and expert interviews across 28 governments representing > 86% of global primary energy consumption. We dissect policy mechanisms, governance levels, underlying motivations, and trends in present EnMS policies. We...

Bio-inspired micro-architected mechanochromic materials with radiative signature modulation

Mon, 31 Aug 2026 00:00:00 +0000

Drawing inspiration from the panther chameleon's sophisticated color-adaptive abilities, we introduce a unified design framework for a new class of bio-inspired mechanochromic materials with tailored reflectivity across the electromagnetic spectrum. While structural coloration in nature relies on the mechanical adjustment of photonic crystal spacing, engineering such systems is often hindered by the barreling effect, the lateral bulging of bulk materials caused by Poisson's effect. To address this, we developed a mechanical metamaterial substrate optimized through a genetic algorithm and modeled it using Timoshenko beam theory to ensure a uniform strain field during deformation. The proposed system features a two-dimensional hexagonal lattice of composite dielectric nanopillars positioned on top of a micro-architected substrate fabricated via Multiphoton Lithography (MPL). The nanopillars consist of an MPL core coated with a high-refractive-index material to achieve complete...

Prediction of Metastable States for Throttling in Pressure Relief Valves for Sustainable CO₂ Heat Pump Technologies

Mon, 31 Aug 2026 00:00:00 +0000

Abstract: Incorporating carbon dioxide (CO2) refrigerant into the heat pump (HP) technology can reduce climate change effects due to working fluid loss. However, CO2 refrigerants in an HP system may change from a gaseous state to a liquid or solid “snow” during the throttling and pressure-relief valve processes, which may block downstream flow in pipes and cause unsafe operation issues. This paper describes a Soave–Redlich–Kwong (SRK) statistical-thermodynamics-based model to predict CO2 refrigerant metastable state properties (enthalpy, temperature, and volume) exhibited during throttling through a leakage path or pressure relief valve in HP technologies. In addition, the simulation can predict changes in density fluctuations states exhibited during the process that can indicate an impending phase change and can predict exit state conditions for widely varying supercritical initial equilibrium states. Results indicate that when a constant enthalpy throttling...

Adaptive Distributionally Robust Planning for Renewable-Powered Fast Charging Stations Under Decision-Dependent EV Diffusion Uncertainty

Mon, 31 Aug 2026 00:00:00 +0000

When deploying fast charging stations (FCSs) to support long-distance trips of electric vehicles (EVs), there exist indirect network effects: while the gradual diffusion of EVs directly influences the timing and capacities of FCS allocation, the decisions for FCS allocations, in turn, impact the drivers’ willingness to adopt EVs. This interplay, if neglected, can result in uncovered EVs and security issues and even hinder the effective diffusion of EVs. In this paper, we explicitly incorporate this interdependence by quantifying EV adoption rates as decision-dependent uncertainties (DDUs) using decision-dependent ambiguity sets (DDASs). Then, a two-stage decision-dependent distributionally robust FCS planning (D3R-FCSP) model is developed for adaptively deploying FCSs with on-site sources and expanding the coupled distribution network. A multi-period capacitated arc cover-path cover (MCACPC) model is incorporated to capture the EVs’ recharging patterns to ensure the feasibility...

Optimized mechano-fluidic metamaterials inspired by deep-sea sponges

Mon, 31 Aug 2026 00:00:00 +0000

Multifunctional materials that balance mechanical resilience and fluid dynamic efficiency are critical in engineering applications, yet their synergistic optimization remains challenging due to inherent trade-offs, computational expense, and high-dimensional design spaces. Inspired by the skeleton of the deep-sea sponge Euplectella aspergillum, this work presents an automated framework integrating Finite Element Analysis for mechanics, Computational Fluid Dynamics for flow behavior, and multi-objective Bayesian optimization. Leveraging high-performance computing, the framework efficiently explores complex design spaces to identify Pareto-optimal solutions. Optimized lattices achieve an average 140% increase in critical buckling load across a range of volume fractions relative to baseline designs, while simultaneously reducing drag, lift, and vortex shedding at porosities as low as 5%. We fabricate selected designs via stereolithography and validate them through compression experiments...

US Representative Feeder Sets for Distribution Grid Economics and Policy Applications

Mon, 31 Aug 2026 00:00:00 +0000

This paper proposes a methodology to generate sets of distribution feeders representative of any U.S. county for economic and policy studies. The methodology modifies prototypical feeders and organizes them into sets that (i) reproduce historical economic and infrastructure investment patterns and (ii) accommodate county-specific demand characteristics, including energy, peak, and building types. The approach relies on publicly available data, enabling systematic application across all U.S. counties and adaptation to other regions. The use of the resulting feeders is demonstrated through an electrification impact study in Alameda County, California.

Capillary Leidenfrost effect

Mon, 31 Aug 2026 00:00:00 +0000

The Leidenfrost effect, best known as the formation of an insulating vapour layer beneath a liquid droplet that delays boiling, offers great potential for droplet manipulation and drag reduction. However, regulating the conventional Leidenfrost effect remains challenging due to the complex liquid dynamics involved. Here we report a behaviour that we term the capillary Leidenfrost effect, which enables stable and sustained solid levitation driven by liquid evaporation. It occurs at a temperature threshold that is below the Leidenfrost point of its droplet counterpart, yet without the need for specialized surface manufacturing techniques. Our structure is composed of periodically arranged capillaries that stabilize the liquid interface, enhance heat conduction and provide liquid storage capacities. The capillary Leidenfrost effect is generic in widely accessible natural materials and metals. Our experiments demonstrate the feasibility of long-distance, sustained self-propulsion...

The Potential and Cost of Carbon Dioxide Removal Using Direct Air Capture with Land-Based Wind and Utility-Scale Photovoltaics

Mon, 31 Aug 2026 00:00:00 +0000

The rapid deployment of direct air capture and storage (DACS) is critical for achieving emission targets, necessitating precise evaluation of the scale and cost of carbon dioxide removal. This study examines the availability of land, electricity generation, and geologic CO₂ storage within the United States, estimating a technical potential for low-temperature, adsorbent-based DACS to remove approximately 9 gigatonnes of CO₂ annually. By 2050, a substantial portion of this removal could be achieved at net-removed costs below $300/tonneCO₂, though costs are highly variable depending on factors such as facility scale, construction expenses, climate-dependent productivity and heating efficiency, and geologic storage conditions. In the short term, DACS deployment will help identify key research priorities for advancing technology and reducing removal costs. Concurrently, there is an urgent need for scientifically robust and standardized frameworks for...

Hydrogen diffusion induced dislocation transformations in a nickel superalloy

Mon, 31 Aug 2026 00:00:00 +0000

The diffusion of hydrogen in metals and alloys induces embrittlement that can adversely affect the structural properties. We examine the adsorption and diffusion of hydrogen in Inconel-718 (IN-718), and scrutinize the ensuing effects on the dislocation behavior in the alloy to elucidate the fundamental mechanisms of hydrogen-microstructure interactions from classical molecular simulations. Hydrogen adsorption increases with time until the surface saturates, while hydrogen diffusion exhibits strong temperature dependence, with diffusion coefficients converging above 1300 K regardless of the initial hydrogen concentration in the alloy. The diffusion in IN-718 is significantly sluggish than in pure Ni, Fe, or Cr, and is strongly impacted by hydrogen concentrations, resulting in an order of magnitude higher diffusion coefficient for hydrogen (10-14 m2/s relative to 10-15 m2/s) at high concentrations, especially below 600 K. Hydrogen diffusion coefficient varies from 10-12...

Distribution System Expansion Planning with Nonlinear Power Flow Models

Mon, 31 Aug 2026 00:00:00 +0000

We consider the electric distribution system expansion planning problem of selecting the least-cost set of upgrades to alleviate voltage magnitude violations. To this end, we use the full nonlinear power flow model to account for losses and represent meshed networks. The underlying problem is highly nonconvex due to the nonlinear power flow equations and the presence of discrete variables. Leveraging the efficacy of local search methods for handling continuous subproblems, a bilevel heuristic algorithm is proposed based on outer-approximation mixed-integer programming techniques. The proposed algorithm is shown to achieve the same optimal value as off-the-shelf mixed-integer nonlinear solvers with much less computation time on five benchmark IEEE distribution feeders.

Nanoengineering Scalephobic Surfaces for Liquid Cooling Enhancement

Mon, 31 Aug 2026 00:00:00 +0000

Abstract Crystallization fouling, a process where mineral scales form on surfaces, is of broad importance in nature and technology, negatively impacting water treatment and electricity production. However, a rational methodology for designing materials with intrinsic resistance to scaling and scale adhesion remains elusive. Here, guided by nucleation physics, this work investigates the effect of coating composition and surface structure on the nucleation and growth mechanism of scale on metallic heat transfer surfaces nanoengineered by large‐area techniques. This work observes that on hydrophilic nanostructured copper, despite its significantly enlarged surface area compared to smooth surfaces, scale formation is substantially suppressed leading to sustained, efficient cooling performance. This work reveals the mechanism through thermofluidic modeling coupled with in situ optical characterization and show that surface bubble formation through degassing is responsible for generating...

A Probabilistic Approach to Load Modeling for Central HVAC Systems in Large Commercial Buildings for Retrofit Decisions Under Uncertainty

Fri, 28 Aug 2026 00:00:00 +0000

Retrofitting central HVAC systems in large commercial buildings with advanced technologies like heat recovery chillers (HRCs) offers a significant opportunity to enhance energy efficiency. However, analyzing these retrofits is challenging with traditional whole-building simulation tools, which require intensive calibration and struggle to model innovative system configurations and controls. To overcome these limitations, this study proposes a load profilebased retrofit analysis framework that provides better decisions under uncertainty. The main focus of this paper is the development of a probabilistic load profile model that can be used in the framework by using exploratory data analysis (EDA) of measured building data to properly quantify its inherent variability. A non-parametric Gaussian Process (GP) model was employed to capture the time- and weather-dependent characteristics of the heating load while explicitly modeling its uncertainty. The model's effectiveness is demonstrated...

Author Correction: Typical and extreme weather datasets for studying the resilience of buildings to climate change and heatwaves

Fri, 28 Aug 2026 00:00:00 +0000

Correction to: Scientific Datahttps://doi.org/10.1038/s41597-024-03319-8, published online 23 May 2024 In this article the author’s name Marcelo Salles Olinger was incorrectly given as Marcello Salles Olinger. The original article has been corrected.

Heat Pump Retrofits for Central Plant Hydronic Heating Systems: A Software Toolkit for Screening and Design

Fri, 28 Aug 2026 00:00:00 +0000

Retrofitting existing central plants with high-efficiency heat pump technologies can play a crucial role in achieving long-term planning goals. Modern heat pump technologies are able to use waste heat recovery to meet a building's heating demand, but there is a lack of accessible tools designed for non-HVAC experts, such as building owners, to quickly and easily conduct what-if analysis, e.g., estimating retrofit costs and payback period for their partial or full equipment replacement. This paper introduces an open-source software toolkit designed to facilitate the initial screening and decision-making of heat pump retrofits in existing central plants using a building's yearly load profile from metered or utility bill data. The toolkit evaluates the technical and economic viability of replacing traditional central plant equipment with various options including water-to-water or air-to-water heat pumps, which can provide efficient and lower-cost heating and cooling. It allows users...

The hidden costs of concealing outdoor air conditioning units

Thu, 27 Aug 2026 00:00:00 +0000

The beautification of urban facades in China often includes covers for the outdoor units of air conditioners. Although these covers improve cityscapes, they reduce cooling efficiency, increase noise pollution, risk system failures and embody carbon emissions. A call urges rethinking their necessity, and presses for sustainable, efficient design to counteract extreme heat.

Seasonal performance evaluation of zero-superheat active refrigerant charge control for variable-speed heat pumps

Thu, 27 Aug 2026 00:00:00 +0000

Heat pumps account for a significant portion of electricity consumption in buildings, making their energy efficiency a critical area of research. Control optimization is recognized as an effective approach for enhancing the efficiency of building HVAC systems. Specifically, since the efficiency of heat pumps increases with reduced superheat and the optimal refrigerant charge level varies with operating conditions, zero-superheat active charge control is a promising strategy to maximize the system’s COP. However, due to its complexity, this control strategy remains in the research phase and has only been tested under limited operating conditions. This paper proposes a methodology to evaluate the seasonal performance improvement of zero-superheat active charge control across a full range of heating conditions in buildings. The methodology includes the development of an optimal controller that utilizes an accumulator to store excess refrigerant and manages the active charge level...

Ten questions concerning housing sufficiency

Thu, 27 Aug 2026 00:00:00 +0000

Housing sufficiency is an emerging concept in the provision of environmentally sustainable housing. It aims for demand-side strategies that reduce excessive, aggregate consumption levels to promote efficient resource utilization and sustainability in the construction sector while providing everyone with a decent standard of housing. However, it is challenging to implement as it interferes with housing-related social and cultural norms. This paper poses and answers ten questions that highlight the challenges, opportunities, and examples of sufficiency strategies in the context of housing provision and the environmental crisis. Question 1 discusses the need for sufficiency as a tool to complement supply-side strategies including efficiency and renewable energy strategies in providing housing. Question 2 examines the concept of housing sufficiency from different perspectives, such as ecological economics and social ecology. Question 3 summarizes the methods used to measure housing...

Approximation of refrigerant thermophysical properties using neural networks to speed up transient thermofluid simulations

Thu, 27 Aug 2026 00:00:00 +0000

Accurate and efficient evaluations of refrigerant thermophysical properties and their partial derivatives are essential for transient simulations of thermofluid systems, where several computations need to be executed at each integration time step. Since the utilization of an Equation of State for retrieving properties based on a pair of independent inputs typically involves numerical iterations in solution procedures, when the input variables differ from the refrigerant state variables employed in dynamic models, a variety of approaches including lookup table interpolation and curve fitting have been developed to explicitly approximate these properties based on the state variables, and consequently eliminate internal iterations. This paper presents an alternative method that exploits derivative-informed neural networks to model refrigerant properties explicitly from inputs of pressure and enthalpy, while ensuring consistent partial derivatives generated by differentiating the...

IoT-based retrofit information diffusion in future smart communities

Thu, 27 Aug 2026 00:00:00 +0000

Community-scale building retrofits are not merely scaled-up versions of single-building retrofits. They involve complex challenges, such as reconciling individual interests with collective goals and managing the dynamic interplay between buildings through mechanisms like power grids and social connections. Internet of Things (IoT) connectivity holds the potential to leverage these interplays to balance individual and collective interests effectively in smart communities. One critical aspect of this interplay is information diffusion, which shapes how retrofit decisions spread among neighbors, influencing individual choices and ultimately impacting community-level retrofit outcomes. In other words, IoT-based smart devices automatically push tailored retrofit notifications to homeowners, which completely changes the format of information diffusion in the future. To investigate this influence by such information diffusion, the study used CityBES to simulate energy performance for...

CityLearn v2: energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities

Thu, 27 Aug 2026 00:00:00 +0000

As more distributed energy resources become part of the demand-side infrastructure, quantifying their energy flexibility on a community scale is crucial. CityLearn v1 provided an environment for benchmarking control algorithms. However, there is no standardized environment utilizing realistic building-stock datasets for distributed energy resource control benchmarking without co-simulation or third-party frameworks. CityLearn v2 extends CityLearn v1 by providing a stand-alone simulation environment that leverages the End-Use Load Profiles for the U.S. Building Stock dataset to create grid-interactive communities for resilient, multi-agent, and objective control of distributed energy resources with dynamic occupant feedback. While the v1 environment used pre-simulated building thermal loads, the v2 environment uses data-driven thermal dynamics and eliminates the need for co-simulation with building energy performance software. This work details the v2 environment and provides application...

Short-term electricity load forecasting: Application-driven evaluation of machine learning models across spatial and temporal scales

Thu, 27 Aug 2026 00:00:00 +0000

As we transition towards a decarbonized economy, the integration of variable renewable energy resources and new demands (e.g., electric vehicles, heat pumps) into the electricity grid places unprecedented pressure on grid operators to effectively anticipate and manage peak load. In this context, machine learning algorithms are proving to be indispensable for accurate short-term load forecasting, a crucial task to address these challenges. This study benchmarks 6 machine learning algorithms, including three neural networks and three tree-based algorithms, across various levels of spatial aggregation and time horizons (1, 4, 8, 24, and 48 h). The central contribution of this work is the comparison and analysis of load forecasting models not only based on statistical metrics, but also based on a novel error metric, which evaluates the cost implications of forecast errors for power system stakeholders. Results show that tree-based models outperform neural networks, based on statistical...

Hydrogen Electrocatalysis on Perfluorosulfonic-Acid-Coated Pt

Thu, 27 Aug 2026 00:00:00 +0000

Membrane-electrode assemblies utilize ionomer-coated electrocatalysts to achieve facile ion transport. Consequently, isolation of intrinsic catalyst kinetics from measured polarization curves is challenging, as the properties of the catalyst and ionomer both affect the measurements. Here, we employ a Pt microelectrode coated by a thin perfluorosulfonic acid (PFSA) layer to measure polarization curves for the hydrogen oxidation reaction/hydrogen evolution reaction (HER/HOR). Intrinsic electrode kinetics are isolated by theoretical analysis of the local catalyst microenvironment, accounting for mass transport and thermodynamics. The observed enhancements in HER and HOR rates with increasing relative humidity (RH) at the working electrode are attributable to two competing factors: the decrease in activity of H+ in the ionomer and the dominant decrease in the water reorganization energy in the Marcus–Hush–Chidsey representation of HER/HOR kinetics. The increase in intrinsic rate with...

Framework to select robust energy retrofit measures for residential communities

Thu, 27 Aug 2026 00:00:00 +0000

Residential building energy retrofits are essential for enhancing environmental sustainability and reducing energy costs. The selection of retrofit measures is influenced by factors such as building systems, occupant behavior, government policy, weather variability, and climate change, all of which can significantly impact energy performance. Compared to retrofitting individual homes, evaluating and selecting optimal retrofit solutions for an entire community is challenging due to diverse residential compositions and variability present. Therefore, engineering robustness is crucial for ensuring consistent energy performance and resilience across different conditions. In this context, robustness refers to the ability of a retrofit measure to maintain its functionality and remain an optimal choice despite external disturbances or changes in inputs and conditions. This study presents a framework for evaluating the robustness of multiple retrofit measures across various building systems,...

A practical control strategy for demand flexibility with ensured occupant comfort in grid-interactive efficient buildings

Thu, 27 Aug 2026 00:00:00 +0000

This study proposes a practical and simplified demand response (DR) control strategy from the perspective of grid-interactive efficient buildings (GEBs), aiming to secure demand flexibility while ensuring occupant thermal comfort. Focusing on summer on-peak periods, a linear demand response (LDR) strategy that integrates cooling setpoint adjustment and lighting dimming was designed, and its performance was quantitatively evaluated. A case study was conducted using EnergyPlus-based simulations for a U.S. DOE small office prototype building under summer on-peak weather conditions. Compared with a conventional rapid demand response (RDR) strategy, the proposed LDR approach gradually reduced electrical loads while maintaining occupant thermal comfort indices, including predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD), within acceptable comfort ranges. Quantitative analysis of demand flexibility using the grid-interactive impact index (GII) and the flexibility...

Reduced-dimension Bayesian optimization for model calibration of transient vapor compression cycles

Thu, 27 Aug 2026 00:00:00 +0000

Development and calibration of first-principles dynamic models of vapor compression cycles (VCCs) is of critical importance for applications that include control design and fault detection and diagnostics. Nevertheless, the inherent complexity of models that are represented by large systems of differential–algebraic equations leads to significant challenges for model calibration processes that utilize classical gradient-based methods. Bayesian optimization (BO) is a sample-efficient and gradient-free approach using a probabilistic surrogate model and optimal search over a feasible parameter space. Despite the benefits of BO in reducing computational costs, challenges remain in dealing with a high-dimensional calibration task resulting from a large set of parameters that have significant impacts on system behavior and need to be calibrated simultaneously. This paper presents a reduced-dimension BO framework for calibrating transient VCCs models where the calibration space is projected...

Virtual refrigerant charge sensor for variable-speed heat pumps based on feature selection

Thu, 27 Aug 2026 00:00:00 +0000

The refrigerant charge level in heat pump systems significantly impacts their energy efficiency. Virtual refrigerant charge (VRC) sensing technology has been comprehensively investigated and well-established due to its lower cost compared to physical sensors. However, the previous VRC research often relied on expert judgment and physical reasoning for their variable selection, which can potentially select redundant (or highly correlated) or insignificant features, and it is also primarily focused on single-speed systems. To address these challenges, this study proposes a VRC algorithm for variable-speed heat pumps that selects features through a rigorous feature selection method in combination with physical insights. We also propose a piecewise linear model structure segmented by subcooling temperature to accurately predict charge levels, particularly when subcooling temperatures are substantially low. The proposed algorithm was evaluated using experimental data of a residential...

Virtual Refrigerant Charge Sensing Method for Next-Generation Refrigerant in Residential Heat Pumps

Thu, 27 Aug 2026 00:00:00 +0000

The charge level of refrigerant in heat pump systems significantly affects their operational performance. Virtual refrigerant charge (VRC) sensing technology has been well-established for traditional refrigerants (HFCs and HCFCs) for its low cost compared to physical sensors. However, other than traditional refrigerants, HFOs are increasingly used in next-generation heat pumps; whether these conventional VRC sensing methods remain applicable for heat pump systems utilizing next-generation refrigerants requires further investigation. To address these issues, this study develops a low-cost VRC sensing method for next-generation refrigerant heat pumps used in residential buildings. The developed algorithm is evaluated by using simulation models to evaluate the accuracy, considering an R454B heat pump with a nominal heating capacity of 51K Btu/hr (14.95 kW) as an example, and compared with those of the two reference VRC sensing algorithms. Though the developed VRC sensing algorithm...

IBPSA Project 2 BOPTEST: An update on the test cases available in the framework for testing advanced control strategies in buildings

Thu, 27 Aug 2026 00:00:00 +0000

Project 2 develops software infrastructure, test cases, and extensions for the Building Optimization Testing Framework (BOPTEST) to address the expanding needs of building and urban energy system controls through open international collaboration. This paper provides an overview of the new test cases available as of BOPTEST version 0.7.1. Each test case is developed using open-source Modelica libraries and Spawn of EnergyPlus, enabling the creation of high-fidelity building models that incorporate envelope dynamics, Heating Ventilation and Air Conditioning (HVAC) systems, and explicit control representations. Currently, eight test cases are available, with five additional cases under development. These test cases cover a wide range of climates, building types, and HVAC systems. This paper compiles and summarizes test case descriptions, cites original manuscripts that developed them for a more detailed description, and reports baseline control performance metrics. Furthermore, two...

Reinforcement Learning Control for Buildings Co-Optimizing Energy, Comfort, and Indoor Air Quality: An Annual Assessment

Thu, 27 Aug 2026 00:00:00 +0000

Efficient control of Heating, Ventilation, and Air Conditioning (HVAC) systems is crucial for optimizing energy use and maintaining indoor comfort in buildings. Traditional control methods, such as PID control, cannot handle energy use trade-offs among multiple components in the building energy system at a supervisory level. Reinforcement learning (RL) presents a promising solution, offering adaptive and data-driven control strategies that optimize performance over time. However, RL also faces several challenges, including the conflicts encountered in co-optimizing energy savings, occupant comfort, and indoor air quality, and the requirement for extensive interactions with the environment in training. We proposed a flexible simulation platform that integrates a hybrid model for RL training and designed an RL agent to control the entire central HVAC system, focusing on co-optimizing energy consumption, thermal comfort, and indoor air quality ($\text{CO}_{2}$ and PM2.5 concentrations)....

Cooling performance of direct expansion system using multiple stages and adjustable heat exchange areas for fresh air handling