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DOE OSTI2024

Freestanding and Flexible Micrometer-Thick PEDOT:PSS Film with High Power Factor

High-efficiency thermoelectric materials are vital for sustainable energy. This work presents a reliable method to fabricate freestanding, flexible micrometer-thick films of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS), achieving a power factor of 204 μW m –1 K –2 , 4 orders of magnitude higher than pristine films. Furthermore, this improvement stems from polymer chain realignment and enhanced charge transport via solvent doping, coupled with PSS reduction during post-treatment, which also strengthens film mechanics. Crucially, the freestanding nature ensures transferability, making them ideal for versatile applications. Besides thermoelectrics, these highly conductive, robust, and flexible PEDOT:PSS films provide attractive solutions for organic solar cells, battery electrodes, and flexible electronics.

Conjugated Polymers↗

DOE OSTI2025

Cracking in polymer substrates for flexible electronic devices and its mitigation

Mechanical reliability plays a critical role in determining the durability of flexible electronic devices because of the significant mechanical stresses they experience during manufacturing and operation. Many such devices are built on sheets comprising stiff transparent-conducting oxide (TCO) electrode films on compliant polymer substrates, and it is generally assumed that the high-toughness polymer substrates do not crack. Contrary to this assumption, here we show extensive cracking in the polymer substrates during bending of a variety of TCO/polymer sheets, and a device example — flexible perovskite solar cells. Such substrate cracking, which compromises the overall mechanical integrity of the entire device, is driven by the amplified stress-intensity factor caused by the elastic mismatch at the film/substrate interface. To mitigate this substrate cracking, an interlayer-engineering approach is designed and experimentally demonstrated. This approach is potentially applicable to myriad flexible electronic devices, with stiff films on compliant substrates, for improving their durability and reliability.

42 ENGINEERING↗

DOE OSTI2025

MXene/graphitic carbon nitride-supported metal selenide for all-solid-state flexible supercapacitor and oxygen evolution reaction

We report a new type of combination of rare earth metal selenides (Ce 2 Se 3 and Er 2 Se 3 ) with a Ti 3 C 2 T x /S-doped graphitic carbon nitride heterostructure for bifunctional application in flexible supercapacitors and oxygen evolution reactions. The incorporation of S-doped graphitic carbon nitride in MXenes reduced the layer stacking tendency of both two-dimensional sheets and eliminated volume expansion by forming a heterostructure. Cerium and erbium rare earth metal centers induce reactive surface sites, whereas binary layers of Ti 3 C 2 T x /S-doped graphitic carbon nitride provide a conducting matrix for the homogeneous growth of the metal selenides. The assembled all-solid-state flexible asymmetric supercapacitor exhibited a high specific capacitance of 60 F g –1 , an energy density of 10.1 W h kg –1 (volumetric energy density: 0.9 mW h cm –3 ) at 2 A g –1 , and 100% capacitance retention after 10 000 charge–discharge cycles with good flexibility for real-time applications. Furthermore, the optimum nanohybrid showed a low overpotential of 280 mV and a Tafel slope of 99 mV dec –1 with durable electrocatalytic performance. Furthermore, this work is the first to investigate the bifunctional energy efficiency of rare earth metal selenides grown over MXene materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Freestanding SrNbO 3 membranes as flexible transparent conductors

Synthesizing flexible transparent conducting materials is important for applications in flexible optoelectronics. Metallic oxide membranes offer great promise due to their large elasticity and high transparency. Among them, SrNbO 3 , a correlated metal, stands out as a promise transparent conducting oxide. However, synthesizing freestanding SrNbO 3 membranes poses a challenge because it easily undergoes oxidation, resulting in degraded conductivity. To address this, we utilize epitaxial BaTiO 3 capping layers, which effectively prevents SrNbO 3 oxidation. We successfully fabricate millimeter-sized transparent conducting BaTiO 3 /SrNbO 3 /BaTiO 3 membranes using water-soluble sacrificial layers. The obtained SrNbO 3 (10 nm thick) membrane exhibits a room temperature sheet resistance (R S ) of 174 Ω/sq and a transmittance (T) of 92% at a wavelength of 550 nm. The figure of merit (T 10 /R S ) of this transparent conductor reaches 2.2 × 10 −3 Ω −1 in the visible regime, comparable to SrNbO 3 films on rigid substrates. These results open possibilities for applications as flexible transparent conductors.

Ko, Eun Kyo [SLAC National Accelerator Laboratory ↗

DOE OSTI2024

Inverter Intensive Hybrid Power Plant Modeling with Small-Signal Stability Augmentation through Flexible Operation Mode Transition

Hybrid power plants (HPPs) prompt the penetration of inverter-based renewable energy sources (RES) in transmission systems; however, given their low-inertia nature, HPPs are dominated by power electronic inverters, so there are inevitable challenges in system stability when increasing numbers of HPPs are integrated into the modern power grids. To boost the penetration level of HPPs without jeopardizing system stability, it is desirable to equip them with operational characteristics (i.e., grid-forming capabilities) that are comparable to those of conventional power plants dominated by synchronous generators (SGs). In this paper, a holistic model of inverter intensive HPP is derived and a bi-level hierarchical control is developed to allow HPPs to flexibly switch among the designed operation modes (i.e., P-Q, P-V, and isochronous modes). Compared to SGs, which have limited controllability, the operation mode of each HPP could vary as requested. Such flexible mode transitions could be integrated into the secondary plant-level control and be leveraged as an additional control degree to further augment system stability. Further, the system small-signal stability margin is quantified with varying HPP operation modes. More importantly, modal analysis is thereby conducted to quantify the impacts of mode transition on the system oscillatory modes. The effectiveness of the proposed HPP bi-level hierarchical control is verified using extensive case studies based on the simplified real-world island power grid, and the results validate that the system small-signal stability margin can be enhanced with the additional degree of control flexibility enabled by HPP operation mode transition. The real-time hardware-in-the-loop (HIL) results are also provided to verify the proposed method.

grid-forming control↗

DOE OSTI2025

GreenThrift: Optimizing Carbon and Cost for Flexible Residential Loads

Reducing buildings’ carbon emissions is an important sustainability challenge. While scheduling flexible building loads has been previously used for a variety of grid and energy optimizations, carbon footprint reduction using such flexible loads poses new challenges since such methods need to balance both energy and carbon costs while also reducing user inconvenience from delaying such loads. This paper highlights the potential conflict between electricity prices and carbon emissions and the resulting trade-offs in carbon-aware and cost-aware load scheduling. To address this trade-off, we propose GreenThrift, a home automation system that leverages the scheduling capabilities of smart appliances and knowledge of future carbon intensity and cost to reduce both the carbon emissions and costs of flexible energy loads. At the heart of GreenThrift is an optimization technique that automatically computes schedules based on user configurations and preferences. We evaluate the effectiveness of GreenThrift using real-world carbon intensity data, electricity prices, and load traces from multiple locations and across different scenarios and objectives. Our results show that GreenThrift can replicate the offline optimal and retains 97% of the savings when optimizing the carbon emissions. Moreover, we show how GreenThrift can balance the conflict between carbon and cost and retain 95.3% and 85.5% of the potential carbon and cost savings, respectively.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

HP-FLEX: Field demonstration of the semantics-driven configuration of a Model Predictive Control system to make heat pumps flexible

Model Predictive Control (MPC) has demonstrated significant potential for optimizing building operations and enabling demand flexibility. However, the widespread adoption of MPC is hindered by complex manual configuration and commissioning processes that must be conducted by control experts working alongside building operators. These challenges drive up costs and reduce scalability, particularly when technical human resources and building automation systems are limited, such as in small and medium commercial buildings (SMCBs). This paper demonstrates how semantic standards, specifically ASHRAE 223P, can accelerate the adoption of MPC applications for load flexibility in SMCBs. The authors present a replicable control framework, titled “HP-FLEX” that leverages a building’s semantic model to bootstrap the required data configuration for an MPC controller developed for optimizing heat pump systems as flexible grid resources. The semantic model helps streamline the deployment workflow, particularly for site setup, data/control commissioning, and model setup. This integration enhances portability, transferability, and scalability of the HP-FLEX MPC, which has been developed to support MPC-based supervisory HVAC controllers in SMCBs. Additionally, the paper details the required building and thermostat metadata information to enable the HP-FLEX MPC based on field demonstrations. The new workflow was tested in a small commercial building located in California, U.S., and demonstrated a load shifting performance of 9% based on a dynamic pricing signal that varies by the hour. This work provides a practical pathway for transitioning sophisticated building applications from custom to standardized semantic representations, supporting the broader adoption of advanced control strategies like MPC. The framework also establishes a foundation for evolving metadata requirements as applications mature while maintaining compatibility with industry standards.

Paul, Lazlo↗

DOE OSTI2025

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

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

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

HP-FLEX: Field Demonstration of the Semantics-Driven Configuration of a Model Predictive Control System to Make Heat Pumps Flexible

Paul, Lazlo↗

DOE OSTI2024

Fitness-for-Service Analysis of Reactor Components under Flexible Load-Following Operating Conditions

Conventional power-generation plants, including nuclear plants, have been traditionally designed to provide a steady baseload energy capacity, optimizing output efficiency while minimizing variable costs. However, the growing adoption of large-scale renewable energy-generation systems, which rely on intermittent sources such as solar and wind, has introduced more variability into the energy supply in interconnected electricity grids. As a result, the next generation of power plants needs to operate in what is known as the load-following mode, requiring flexible adjustments in electricity production to align with the energy demand on the grid. This transition from the steady baseload operation to load-following operating conditions can significantly increase the number of times various plant components are exposed to transient stresses. This increased thermo-mechanical cycling can lead to accelerated material degradation, thereby elevating the risk of premature failure of a component. It becomes imperative to conduct a comprehensive analysis of fatigue, creep-fatigue, and stress corrosion cracking life, to assess the resilience of the various engineering components under these flexible load-following operating conditions. This study aims to develop a comprehensive numerical model of a light-water reactor pressure vessel (RPV) to investigate its degradation under various operating scenarios. This coupled thermo-mechanical finite element analysis evaluated the stress response of the RPV caused by considering fluctuations in thermal and mechanical loads caused by the varying pressure and temperature occurring during the load-following operation. Critical locations on the RPV are subsequently identified based on the stress response. The stress intensity factors for the postulated flaws at those locations are then calculated, followed by an evaluation of the reactor's life in accordance with the ASME Boiler and Pressure Vessel Code Section XI. This comprehensive life assessment covers a number of transients expected during the flexible load-following operation, providing invaluable insights into the RPV's structural integrity. Moreover, the development methodology can be adapted to other reactor components, as well as components of conventional power stations that are affected by varying operating conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Assessing thermal comfort and participation in residential demand flexibility programs

Residential space-conditioning-based demand flexibility (DF) has become an increasingly sought-after method for demand-side load management to enhance grid reliability and facilitate integration of renewable energy generation. However, predicting the effectiveness and flexibility of residential DF resources is challenging due to the variability in household energy use behaviors. Current estimates show that only 50 % of projected savings from DF resources are actualized due to regulatory, technological, and social barriers. From a household perspective, concerns over thermal comfort during space conditioning-based DF events significantly impact participation decisions. Currently, there is a very limited understanding of how thermal comfort during space-conditioning-based DF events in real-world settings impacts household energy use behaviors and, consequently, the success of DF programs in achieving targeted savings. This paper proposes a method to comprehensively assess the thermal comfort implications of DF strategies and presents results of their impacts on DF event participation decisions and demand savings. Here, the proposed method was applied to a heat pump DF field study in Cordova, Alaska. The study’s key findings are: 1) DF event setpoint offsets that maintain indoor operative temperatures between 18 to 22 °C (65 to 71°F) may be preferred in Cordova, Alaska; 2) Household-level thermal comfort is more sensitive to the duration of the DF event than to the degree of temperature offset from baseline conditions; 3) The delayed impact of changes in indoor operative temperature in response to setpoint offsets, both during and after a DF event, influences occupants’ thermal comfort perceptions and willingness to persistently participate in events. The findings from application of the proposed method can help inform future larger-scale occupant-centric DF programs as it can capture information not readily available through utility and device-level energy use data. Thus, it can supplement these sources and help program administrators develop occupant-centric DF strategies, enabling more accurate predictions of participation rates and savings estimates for space-conditioning-based DF programs.

Demand side management↗

DOE OSTI2024

Green co-solvent-assisted one-pot synthesis of high-performance flexible lignin polyurethane foam

Although lignin is a promising candidate as a source of polyol for producing eco-friendly polyurethane foam (PUF), its direct application has limitations, primarily stemming from the brittleness of the resulting products and poor processibility at high lignin loadings. To address these technical challenges, we introduced an effective co-solvent for the lignin-based polyurethane foams (LPUFs) with up to 80wt% of lignin substitution for petroleum polyols. As a green co-solvent that involves carbon dioxide fixation during its production, propylene carbonate (PC), was blended with lignin and improved the distribution of lignin by decreasing the viscosity, providing a room-temperature reaction. The LPUFs demonstrated a comparable thermal insulation performance (R-values greater than 5 in -1 ) with commercially available PUF with a uniform size of closed-cell structure induced by the reduced viscosity of lignin-based polyol. LPUFs also showed enhanced fire retardancy and moisture resistance compared to the control PUFs, benefiting from lignin’s intrinsic fire-resistant and hydrophobic properties. To mitigate the brittleness issue at high lignin loadings, flexible polyethylene glycols (PEGs) with a high molecular weight (i.e., PEG-1000) were dissolved in PC at room temperature to further improve the mechanical strength of LPUFs. The compressive strength of LPUFs with 80 wt% lignin substitution content was remarkably improved to 226 kPa by the employment of co-solvent and PEG-1000 compared to the control PUF (<140 kPa). Moreover, the flexibility of the LPUFs was successfully controlled by simply adjusting the PEG-400/PEG-1000 ratio. In conclusion, the results of this study provide valuable insights for accelerating and broadening the utilization of lignin in sustainable materials and manufacturing areas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Bridging semantics, control specifications and assessment: A library for scalable demand flexibility controls

There is growing recognition that Demand Flexibility (DF) can play a major role in enhancing grid reliability, with building control applications emerging as key enablers for DF. However, the traditional approach to deploying new control applications in buildings, including those for DF, remains largely manual and tailored to individual buildings, making it difficult to scale. While research efforts have explored semantics-driven portability, DF controls specification, and assessment approaches, these initiatives are fragmented and limited in scope. This paper proposes a novel methodology, grounded in design science research, to integrate these elements and create a comprehensive DF controls library for both industry and academia. This approach is applied to develop the Demand FLEXibility controls LIBrary using Semantics (DFLEXLIBS), an extensible open-source library that provides DF controls for HVAC systems in Python. DFLEXLIBS enables portable, easy-to-deploy controls that abstract building-specific data points, facilitating assessment across diverse buildings. DFLEXLIBS features nine different control applications, and it is successfully implemented and tested across four virtual and two real buildings, bridging the gap between semantics-driven portability, DF controls specification, and rigorous performance assessment. Its benefits are measured by a reusability ratio greater than 90% and a functional overlap ratio of around 70% for the most common functions used in the library, significantly reducing time for deploying new controls.

Controls library↗

DOE OSTI2024

Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Achieving success with grid-interactive efficient buildings (GEBs) is closely tied to the utilization of flexible loads. A valuable strategy involves the implementation of precooling techniques before high-demand events, such as peak hours, by adjusting zone air temperature setpoints. This leads to a reduction in thermal loads and peak electricity demand during these times, as the building’s thermal mass stores and subsequently releases thermal energy. However, the effectiveness of the pre-cooling optimization is highly contingent on specific conditions such as building thermal properties, weather conditions, utility rate structure, HVAC equipment sizing, etc. Therefore, investigating the impacts of these condition-specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Here, the optimal thermostat schedule was parameterized using three optimization variables: the precooling start time, the precooling end time, and the precooling temperature setpoint. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. In addition, we investigated the impact of different influencing factors on the optimal precooling strategy. These factors include building thermal mass, outdoor air conditions, and energy price profiles. Using high-performance computing, we simulated a total of 225 scenarios, consisting of three levels of thermal mass, five typical outdoor air temperature profiles, and fifteen time-of-use price plans. The results demonstrate that optimal thermostat scheduling could save substantial energy cost in medium-sized office buildings with heavy thermal mass but with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. The study also highlights the need to account for zone diversity and recognize that a one-size-fits-all-zone setpoint schedule may not be suitable for all zones and can lead to unnecessary energy wastage. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. Although cost savings are comparable under certain conditions with the same cooling load, observed deviations in energy penalty indicate potential disparities in the efficiency of the HVAC system during the load-shifting process. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Flexible operation of nuclear hybrid energy systems for load following and water desalination

Nuclear hybrid energy systems (NHES) have the potential to provide dependable and emission-free electricity to the grid while also increasing the flexibility and reliability of the electrical grid. Molten salt reactor (MSR) technology can provide consistent, carbon-free electricity while also increasing efficiency, security, and sustainability and reducing nuclear waste. This study investigates the integration of Molten Salt Reactors (MSR) and conventional Pressurized Water Reactors (PWR) with desalination technologies: Direct Contact Membrane Distillation (DCMD), Multi-Stage Flash Distillation (MSFD), and Reverse Osmosis (RO). Dynamic first-principles models were developed and tested using real grid data from the New York Independent System Operator. The results demonstrate that nuclear power is capable of flexibly responding to changing grid demand while simultaneously producing clean water, particularly during periods of low electricity demand. The MSR-RO system was found to be the most efficient in electricity generation and water production, and all hybrid systems reduced CO2 emissions by 356,000 to 682,000 tons annually. Economic analysis reveals that nuclear desalination technologies are cost-competitive with conventional systems, especially when paired with RO. Finally, these findings confirm the technical feasibility and environmental benefits of nuclear hybrid systems for sustainable electricity and water production.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Optimizing Desalination Operations for Energy Flexibility

Despite the value of energy optimization in desalination processes, modeling dynamic operations for monthly billing periods has remained a computational challenge. This work proposes a framework for energy flexibility optimization, which includes new modeling features for independent operation of parallel skids, start-up delays associated with chemical stabilization, the consideration of industrial energy tariff structures, and inclusion of hourly electrical carbon intensities. This is done using a modular and computationally efficient formulation that guarantees a globally optimal solution with standard optimization solvers. In this study, the approach is demonstrated in two distinct case studies: a seawater desalination plant in Santa Barbara, CA, and an indirect potable reuse facility in San Jose, CA. Trends predicted from the model are validated against operational facility measurements from a demand response shutdown event. Preliminary results show that optimizing energy flexibility can result in 18.51% monthly cost savings over energy efficiency-optimized operation. The value extracted from a facility-wide shutdown during peak electricity price hours is hampered by start-up delays in post-treatment chemical stabilization. In cases in which a facility does not have much excess capacity, using a flow equalization tank or operating over a wide recovery range may be cost-effective.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Multi-Agent Hierarchical Deep Reinforcement Learning for HVAC Control With Flexible DERs

As electricity consumption in commercial and residential buildings continues to rise, reducing energy costs presents an increasing challenge. Heating, ventilating, and air-conditioning (HVAC) systems, which typically account for 40%-50% of a building's energy use, are prime targets for energy savings. Intelligent control of HVAC temperature through the exploitation of HVAC load flexibility brings significant potential to reduce energy consumption and electricity expenses. The nonlinear models of HVAC systems challenge traditional control methods, while the uncertainty introduced by HVAC load flexibility complicates distributed energy resource (DER) management using conventional optimal dispatch techniques. In response to these challenges, we propose a hierarchical multi-agent deep reinforcement learning (DRL) approach. The lower-level agents focus on balancing comfort and energy conservation, while the upper-level DRL agents optimize the use of DERs to reduce peak demand based on the control outcomes of the HVAC by the lower-level agents. Here, in the upper-level agents, we incorporate a multi-agent structure based on ensemble learning, which acts based on historical and current data without relying on precise load forecasting to address the delayed rewarding issue in DRL. This allows for the effective reduction of energy costs. The proposed method is tested using a real-world microgrid comprising 413 buildings in Southern California, and the results demonstrate that our approach can significantly reduce overall electricity bills while ensuring the comfort of consumers and residents.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Hardware-in-the-loop Laboratory Performance Verification of Flexible Building Equipment in a Typical Commercial Building

This project aims to develop high-resolution equipment performance and occupant data that quantifies demand flexibility in typical commercial buildings. The dataset documented in this report includes comprehensive time-series measurements from hardware-in-the-loop (HIL) experiments conducted across multiple testbeds designed to simulate realistic operational environments for HVAC systems. Specifically, it captures minute-by-minute high-resolution data on the performance of various typical HVAC systems, including a variable-air-volume (VAV) air handling unit (AHU) system with chillers and an ice tank in the Intelligent Building Agents Laboratory (IBAL) at the National Institute of Standards and Technology (NIST), a two-stage air-source heat pump (ASHP) at the NIST, and a water-source heat pump (WSHP) at Texas A&M University (TAMU). The data were generated under a range of controlled conditions reflecting different grid scenarios and climatic influences, as well as various control strategies, building types, occupancy patterns, and occupant behaviors. This dataset provides DE-EE0009153 Final Report 5 detailed insights into the demand flexibility of these systems, including their response to grid signals, occupant behaviors, energy consumption patterns, and operational efficiency under different conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗