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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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

An analytical method for identifying synergies between behind-the-meter battery and thermal energy storage

Electric utilities build generation capacity to meet the highest demand period, and they often pass on the costs associated with these peaking generators to building owners through demand charges. Building owners can minimize these demand charges by shifting energy use away from peak periods with behind-the-meter storage. This storage can include batteries, which can directly shift the metered load, or thermal energy storage, which can shift thermal-driven electric loads like air conditioning. However, there is a lack of research on how best to combine battery and thermal energy storage. In this study, we develop an analytical sizing method to calculate the potential demand reduction and annualized cost savings for different combinations of thermal and battery energy storage sizes. We show that adding batteries to a thermal energy storage system can increase the total system's load shaving potential. This is particularly true when the building has onsite photovoltaic generation or electric vehicle charging, which add significant variability to the load shape. We also show that for a given total storage size, selecting a higher fraction of thermal energy storage can significantly lower the cycling of the battery, and therefore extend the battery life. This, combined with the expected lower first cost of thermal energy storage materials compared to batteries, shows that hybrid energy storage systems can outperform a standalone battery or standalone thermal storage system. Assuming the thermal storage has a capital cost 6x lower than the battery, our analysis shows that the optimal system is 71% thermal energy storage and 29% battery energy storage for a scenario with electric vehicle charging. The annualized cost savings for this system are $48.6 k/yr, whereas an equivalently sized standalone thermal energy storage system would provide annualized cost savings of $28.5 k/yr and a standalone battery would lead to savings of $8.72 k/yr. The hybrid system also reduces battery cycling by 52% compared to a standalone battery, extending battery lifetime.

25 ENERGY STORAGE↗
DOE OSTI2023

A “Master Curve” Describing Reaction Inhomogeneity and Plating Onset during Fast-Charging of Graphite Electrodes

Lithium plating in porous graphite electrodes is a major limitation for fast charging. Theoretical evidence suggests plating during fast charging is largely due to inhomogeneous intercalation through the electrode thickness (caused by ionic/mass transfer limitations and inherent thermodynamic properties of the graphite material). Numerical and analytical predictions of plating onset during fast charging have been proposed but not compared directly with experiments. This work validates these model predictions against plating onset measurements via the “dOCV” method in graphite half-cells, for various electrode thicknesses and C-rates. Remarkably, it is shown that experimental and theoretical trends in plating onset (vs C-rate and electrode thickness) collapse to a single “master curve” using a nondimensional “reaction inhomogeneity” parameter. This observation supports the hypothesized reaction inhomogeneity mechanism for accelerating plating onset and provides practical guidance for electrode design. Furthermore, this work develops theory to quantify reaction inhomogeneity in situ directly from voltage V vs capacity Q data, using dQ / dV analysis. Here again, experiments and numerical predictions show good agreement, where peaks that correspond to LiC 6 correlate with plating onset. This work provides experimental validation of theoretical tools that can predict plating onset, aid electrode design, and give insight for plating onset mechanisms during fast charging.

25 ENERGY STORAGE↗
DOE OSTI2025

DOE Zero Energy Ready Manufactured Housing: Subject Matter Expert Technical Assistance Summary

Manufactured homes offer American consumers an affordable option for decent single-family detached housing. For working-class American families in many U.S. markets, manufactured homes are the first step toward home ownership. They now make up 10% of all new homes constructed in the United States, with higher percentages in the south and in rural communities. To help encourage the production of homes that are more durable, healthy, efficient, and disaster resistant, the U.S. Department of Energy is bringing its building science research to the manufactured housing industry through DOE’s Zero Energy Ready Manufactured Home (ZER-MH) program, which provides technical assistance and voluntary guidelines to manufactured home builders. Homes built to these guidelines are better able to handle power outages and less likely to experience moisture issues, offering a better product option for American families. This higher quality is evidenced by energy modeling which shows homes manufactured to these voluntary guidelines will typically use half the energy of manufactured homes built to the current minimum requirements of the U.S. Department of Housing and Urban Development (HUD)’s Manufactured Housing and Construction Safety Standard (MHCSS). These homes can also reduce critical energy demand during the busiest hours of the day, typically late afternoon and early evening in the summer when air conditioning demand is highest and mornings in the winter when furnaces and heaters are heating up. Reducing electricity demand during these peak periods when electricity rates are at their highest reduces costs for American families while freeing up capacity on overburdened energy distribution networks. Builders participating in the DOE ZER-MH program are eligible for a tax incentive via the 45L tax credit, which helps to offset the costs of ZER-MH upgrades, enabling builders to offer these certified homes at no additional cost. Together these factors enable manufactured homes to offer home buyers a housing option that is both affordable to finance and affordable to operate, with lower monthly mortgage payments and lower monthly energy bills.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A Framework to Analyze the Requirements of a Multiport Megawatt-Level Charging Station for Heavy-Duty Electric Vehicles

Widespread adoption of heavy-duty (HD) electric vehicles (EVs) will soon necessitate the use of megawatt (MW)-scale charging stations to charge high-capacity HD EV battery packs. Such a station design needs to anticipate possible station traffic, average and peak power demand, and charging/wait time targets to improve throughput and maximize revenue-generating operations. High-power direct current charging is an attractive candidate for MW-scale charging stations at the time of this study, but there are no precedents for such a station design for HD vehicles. We present a modeling and data analysis framework to elucidate the dependencies of a MW-scale station operation on vehicle traffic data and station design parameters and how that impacts vehicle electrification. This framework integrates an agent-based charging station model with vehicle schedules obtained through real-world vehicle telemetry data analysis to explore the station design and operation space. A case study applies this framework to a Class 8 vehicle telemetry dataset and uses Monte Carlo simulations to explore various design considerations for MW-scale charging stations and EV battery technologies. The results show a direct correlation between optimal charging station placement and major traffic corridors such as cities with ports, e.g., Los Angeles and Oakland. Corresponding parametric sweeps reveal that while good quality of service can be achieved with a mix of 1.2-megawatt and 100-kilowatt chargers, the resultant fast charging time of 35–40 min will need higher charging power to reach parity with refueling times.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

An Analysis of PNM's Renewable Reserve Requirements to Meet New Mexico's Decarbonization Goals

Over the next three years, the Public Service Company of New Mexico (PNM) plans to increase utility-scale solar photovoltaic (PV) capacity from today’s roughly 330MW to about 1600MW. This massive increase in variable generation—from about 15% to 75% of peak load—will require changes in how PNM operates their system. We characterize the 5 and 30-minute solar and wind forecast errors that the system is likely to experience in order to determine the level of reserves needed to counteract such events. Our focus in this study is on negative forecast error (in other words, shortfalls relative to forecast) – whereas excess variable generation can be curtailed if needed, a shortfall must be compensated for to avoid loss of load. Calculating forecast error requires the use of the same forecasting methods that PNM uses or a reasonable approximation thereof. For wind, we use a persistence forecast on actual 5-minute 2019 wind output data (scaled up to reflect the amount of wind capacity planned for 2025). For solar, we use a formula incorporating the clear sky index (CSI) for the forecast. As the solar on the grid now is a small fraction of what is planned for 2025, we generated 5-minute solar data using 2019 weather inputs. We find that to handle 99.9% of the 5-minute negative forecast errors, a maximum of 275MW of variable generation reserve during daylight hours, and a maximum of 75MW during non-daylight hours, should be sufficient. Note that this variable generation reserve is an additional reserve category that specifies reserves over and above what are currently carried for contingency reserve. This would require a significant increase in reserve relative to what PNM currently carries or can call upon from other utilities per reserve sharing agreements. This variable generation reserve specification may overestimate the actual level needed to deal with PNM’s planned variable generation in 2025. The forecasting methodologies used in this study likely underperform PNM’s forecasting – and better forecasting allows for less reserve. To obtain more precise estimates, it is necessary to consider load and use the same forecasting inputs and methods used by PNM.

14 SOLAR ENERGY↗
DOE OSTI2026

Estimating the impact of tariff-driven behind-the-meter storage operation on distribution grid investments

Increasing growth of distributed solar photovoltaics (PV) and electric vehicles (EV) can strain local distribution networks and require costly upgrades. Distributed battery storage, often deployed alongside PV, can be used to mitigate those costs, depending on how batteries are operated. This study evaluates the potential deferral value of distributed battery storage across a range of tariff structures, focusing on the rate structures most commonly available to residential customers today and related variants. Deferrals are evaluated with a least-cost distribution grid expansion optimization model to identify requirements on line reconductoring, transformer upgrades, and voltage regulator installations under each tariff. Results show that TOU rates and net billing tariffs can yield meaningful deferral value, depending on specific tariff structure features. Under the best performing tariff structure tested, storage produced a median annualized deferral value of $7.18 per kW of storage capacity ( kW S ) across all feeders in the sample, though deferral values were considerably larger for feeders with peak loads that coincide with utility system peak, i.e., timing of TOU peak period. In contrast, under an unrestricted TOU design with no restrictions on grid charging or discharging, the median deferral value was $0/ kW S illustrating the critical importance of tariff structure details.

Rodriguez-Garcia, Luis↗
DOE OSTI2024

Investigation of precooling unit design options in hydrogen refueling station for heavy-duty fuel-cell electric vehicles

Precooling gaseous hydrogen fuel to a cold temperature before refueling a heavy-duty (HD) hydrogen fuel cell electric vehicle (HFCEV) is essential to avoid overheating the vehicle tank, as well as achieving a high state of charge (SOC). Because a large volume of hydrogen is dispensed during each fill, the need for a shorter fill time amplifies the need to precool each load for refueling a HFCEV. Thus, the design and operation of a precooling unit (PCU), as well as the associated capital and operating costs, plays a pivotal role in any plans for heavy-duty hydrogen refueling stations. Here, in this paper, we present a thermodynamic and technoeconomic analysis of a PCU in a gaseous hydrogen refueling station (HRS) for HD HFCEVs. By employing Argonne National Laboratory's hydrogen station cost optimization and performance evaluation (H2SCOPE) model, the refueling of 50 kg of hydrogen on-board type IV tank at ambient temperatures of 15–45 °C and varying fill rates is simulated. The required degree of precooling temperature to obtain either 100% or the maximum possible SOC is obtained from the simulation. Additionally, the simulation results demonstrate that the average flow rate of hydrogen is approximately 40% lower than the maximum flow rate during a typical fill; which motivates further evaluation of the instantaneous hydrogen mass flow rate profile and suggests the scope of improving precooling unit design. Accordingly, a hybrid strategy of precooling hydrogen has been proposed to address the cooling load by sizing the refrigeration unit for the average flow rate of hydrogen, while supplementing the above average peak hydrogen flow cooling load through thermal buffering. The combined technique enables the downsizing of the original PCU capacity by 25–40% and demonstrates a potential cost reduction of the PCU by approximately 30%, which translates to an installed cost reduction of ∼$125,000 per dispenser.

25 ENERGY STORAGE↗
DOE OSTI2025

A strategy for automated core design to increase economic viability and minimize fuel fragmentation, relocation, and dispersal susceptibility in high-burnup cores

The nuclear industry aims to increase the cycle length of pressurized water reactors from 18 to 24 months to increase power plant capacity factors and economic viability. These cycle length extensions will inherently require fuel rods to exceed the current peak rod average burnup limit of 62 GWd/MTU. A chief concern of operating beyond the current burnup limit is the fuel fragmentation, relocation, and dispersal (FFRD) phenomenon in which pulverized fuel fragments can axially relocate and escape through a burst in the cladding formed during a loss-of-coolant accident. In this work, we demonstrate an approach for automating core design employing an optimization tool based on a penalty-free, parallel simulated annealing algorithm to produce pressurized water reactor core designs with two different optimization objectives. The two objectives were to produce core designs with (1) mitigated FFRD susceptibility while achieving 24-month cycle lengths (2) maximum cycle length with no regard for the likelihood of FFRD. Batch size was considered in tandem with both cases to maximize economic viability. The PARCS nodal model was the primary reactor physics tool used in the optimizations and used nuclear cross sections calculated with 2D Polaris lattice physics models. Reactor performance and safety characteristics of the optimized cores were verified using high-fidelity Virtual Environment for Reactor Applications models. The core designs produced by the optimization tool are compared with each other and to a high-burnup core design produced and analyzed in previous works to highlight the fuel management strategies that may enhance high-burnup reactor safety and economic viability. The optimized cores satisfied their respective objective functions, producing a maximum cycle length of 720 effective full-power days in one core design and one that may reduce FFRD susceptibility by up to 50% based on the first-order approximation to FFRD risk formulated in this work. The optimized cores met most constraints but exceeded the hot channel factor limit, especially in FFRD cases where fresh fuel carried more power. Furthermore, this highlights the need for future lattice-level optimizations and broader assembly options.

Cycle length↗
DOE OSTI2020

Anomalous thermodynamic properties of quantum critical superconductors

Recent high-precision measurements employing different experimental techniques have unveiled an anomalous peak in the doping dependence of the London penetration depth which is accompanied by anomalies in the heat capacity in iron-pnictide superconductors at the optimal composition associated with the hidden antiferromagnetic quantum critical point. Here, we argue that finite temperature effects can be a cause of observed features. Specifically we show that quantum critical magnetic fluctuations under superconducting dome can give rise to a nodal-like temperature dependence of both specific heat and magnetic penetration depth in a fully gapped superconductor. In the presence of line nodes in the superconducting gap fluctuations can lead to the significant renormalization of the relative slope of T-linear penetration depth which is steepest at the quantum critical point. The results we obtain are general and can be applied beyond the model we use.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

High Density Thermal Energy Storage by Highly Stable Glauber’s Salt Composites with Low Supercooling for Building-Scale Application

Phase change materials (PCM) are a promising candidate for thermal energy storage in building infrastructure, enabling grid-integrated peak load shaving by utilizing energy production in off-peak hours. Glauber’s salt (Na2SO4.10H2O, Sodium sulfate hydrate) are highly attractive due to their high energy storage capacity and low cost but Glauber’s salt suffers from long-standing challenges including high supercooling ( > 15oC) and low thermal cyclic stability, which is a major setback for practical building-scale energy storage applications. Here, we developed a unique ionic molecular nucleating agent for Glauber’s salt which reduced the supercooling temperature to less than 5oC. By combining this nucleated SSD with a polymer, phase segregation of salt hydrate for over 100 thermal cycles without degradation was achieved. Key was that the polymer confined the SSD crystals, preventing phase separation. In addition, we applied our stable Glauber’s salt composite in a miniatured building model and demonstrate that our PCM composite can be utilized for real-world building infrastructure.

additives↗
DOE OSTI2026

Storing Affordability: Battery Storage as an Asset to Reduce Data Center Cost Shifts

This report examines how battery energy storage systems (BESS) can help utilities accommodate large load growth while protecting affordability for existing ratepayers. Rapid growth in electricity demand from artificial intelligence (AI) data centers is straining the U.S. grid. Furthermore, many new data centers are entering rural markets, which could offer economic benefits but may also pose implementation challenges for smaller utilities. At the same time, retail electricity prices are increasing faster than inflation, elevating customer affordability as a key challenge. While data centers have not been the primary driver of increases in residential prices to date, they have pushed wholesale energy and capacity prices higher in several markets. Fundamental utility cost-allocation principles show that data center growth can be rate-positive for existing customers only if new peak demand grows faster than the costs a utility must incur to serve it. Several factors, including a utility’s degree of wholesale market exposure, forecast uncertainty and stranded-asset risk, and tariff design can determine the outcome of load growth on retail rates. Energy storage can make several affordability contributions in the face of this landscape of uncertainty and market volatility, including deferral of higher-cost grid investments through improved utilization of existing assets and flexibility of new large loads, insulation from volatile wholesale prices through peak shaving, and reliability support to address grid risks stemming from the behavior of AI data center loads. Different potential BESS deployment pathways—utility-scale front-of-the-meter systems, aggregated small-scale storage installations, and data center-sited behind-the-meter storage—are compared against each other and against conventional capacity alternatives. This framework is intended as a conceptual resource to utilities, particularly smaller public utilities with rural service territories, who may be considering the role that energy storage can play in insulating existing ratepayers from data center cost shifts.

25 ENERGY STORAGE↗
DOE OSTI2026

Local Air Quality Impacts of a Peak-Shaving Diesel Generator Unit in Waynesville, North Carolina

The Waynesville Electric Department in Waynesville, North Carolina, operates a 2,000-kW diesel generator with a 4% capacity factor, emitting less than 1 ton annually of PM2.5, VOCs, carbon monoxide (CO), and sulfur dioxide (SO2), and approximately 1.8 tons of NO. The National Laboratory of the Rockies (NLR) conducted high-resolution, near-source air-quality modeling to evaluate the generator's impacts. Results indicate minimal effects on ambient pollutant concentrations: annual PM2.5 increases are below 0.0004 microgrm/m3 for local census tracts, while CO and SO2 levels increase by less than 0.00004 ppm and 0.0002 ppb, respectively. Estimated annual premature mortality attributable to PM2.5 exposure is less than 0.001 cases across Haywood County, with an associated economic impact of approximately $12,000. This report complements a separate technoeconomic analysis to inform Waynesville's investment strategies for demand reduction.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Optimization of Operating Profit for the FEED of the PZAS Process for CO 2 Capture on a 460 MW NGCC

A rating model of PZAS (Piperazine with the Advanced Stripper) for a 460 MW natural gas combined cycle was developed from vendor-provided equipment performance data. Surrogate rating models were built and used to optimize variable profit of the system subject to natural gas and electricity price at a fixed value for CO 2 of $\$80$/tonne. Several process constraints were considered between ambient temperatures of 4.4 and 40.5 °C. Lower lean loading resulted in lower reboiler heat duty of about 2.2 GJ/tonne. Lean loading at 0.2 mol/equiv N was sufficient at an ambient temperature of 4.4 °C to maximize variable profit. Solvent precipitation was avoided even at low lean loading (0.18 mol/mol) in the absence of a trim cooler for the lean solvent between the absorber and the cold cross exchanger. Optimal CO 2 removal was always higher than the design case removal of 90% and achieved a peak of 93.6% for 4.4 ºC ambient temperature. Lean solvent rate was a significant driver of profitability. The maximum capacity of the compressor was a significant constraint on profitability. Increasing compressor capacity by 20–30% could increase variable profit by about 21% in the case of 0.18 lean loading at 4.4 °C ambient temperature. Furthermore, this increase in profit was lower at higher ambient temperature and higher lean loading. The breakeven gas price was $\$4.6$/MMBtu at high lean loading of 0.22 mol/mol. Below this value, profit was maximized by increasing the boiler heat rate. Above this value, profit could not be increased by burning additional natural gas, requiring a reduction in boiler heat rate and consequently, specific heat duty. At lower lean loading (0.2, 0.18 mol/mol), this transition in heat duty was not observed due to the lower heat duty. As the ambient temperature increased, a similar trend in heat duty was observed at 0.22 lean loading, but the transition to lower heat duty occurred earlier at $\$4$/MMBtu. This was because of the lower CO 2 production at higher ambient temperature, making the process unprofitable at a gas price higher than $\$3$/MMBtu unless the heat duty of the stripper and natural gas boiler is steeply decreased.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Improved internal short circuit models for thermal runaway simulations in lithium-ion batteries

Thermal runaway (TR) modeling is one of the primary tools that can be used to overcome challenges associated with lithium-ion battery (LIB) safety. Among all LIB accidents that have occurred over the past decade, Internal Short Circuit (ISC) remains the most common trigger mechanism. Many available models in the literature either use a simplified approach to simulate ISC or completely ignore its contribution. The aim of this study is to understand the nature of the heat released for different types of ISC scenarios, including aluminum-anode, anode–cathode, and copper-cathode ISC. We study ISC behavior using a coupled electrochemical–thermal model with an integrated TR chemical kinetics solver built in the COMSOL Multiphysics framework. The time duration of heat release and the magnitude of the peak ISC current are studied as functions of parameters such as the size of the penetrating filament and the capacity of the cell. The numerical results are used to build an empirical model validated against the published experimental TR propagation data. Our model can be successfully used as a viable low-cost substitute in lower order (lumped) TR simulations to enable TR prevention and mitigation.

Singh, Bakhshish Preet (ORCID:0000000264751992)↗
DOE OSTI2022

Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary production

Gross primary production (GPP) models driven by fine resolution remote sensing data characterize the spatial and temporal heterogeneities in plant photosynthesis, which is largely dependent on biome-specific maximum photosynthetic capacity. The red-edge reflectance, sensitive to leaf chlorophyll content, is a good proxy of maximum photosynthetic capacity. More importantly, studies show that the red-edge reflectance-related chlorophyll content index (CIr) multiplied by the incident photosynthetic active radiation (PAR in ) strongly correlates to GPP estimated at carbon flux towers (GPP flux ). Yet, to the best of our knowledge, there is no systematic study investigating the general relationship between fine spatial resolution CIr and GPP among biomes and the relationship between CIr and maximum photosynthetic capacity in GPP models. To provide an overview on incorporating space-borne CIr into a GPP model, we applied fine resolution Sentinel-2-derived CIr and GPP flux over 57 flux sites representative of 10 biomes. We investigated the relationship between CIr and GPP flux , and the spatio-temporal relationship between CIr and ecosystem maximum photosynthetic capacity indicated by the potential ecosystem light use efficiency (LUE pot ). We also evaluated the relationship between other five vegetation indices (VIs) and GPP flux . Results showed that the CIr multiplied by PARin has a higher agreement (R 2 > 0.5) with GPP than other VIs. A universal relationship exists between the CIr multiplied by PARin and GPP, except for forest biomes. The CIr also strongly (R 2 > 0.5) relates to the LUE pot during the peak of the growing season. The CIr has a low spatial variance (CV = 0.25) among biomes, highlighting that CIr can be a proxy of maximum photosynthetic capacity in GPP models that do not require biome-dependent coefficients. This study provides insight for incorporating CIr into GPP models and better quantifying global terrestrial photosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Project Phase 1 Report: Reducing Data Center Peak Cooling Demand and Energy Costs With Cold Underground Thermal Energy Storage (Cold UTES)

Cold Underground Thermal Energy Storage (Cold UTES) is an ultra-long duration grid energy storage technology. With Cold-UTES, low-cost grid power is converted to cold thermal energy and stored in the native subsurface rock at the point of use. Cold UTES is one approach within the general category of engineered geothermal systems. Cold UTES for peak-hour cooling of data centers (DCs) was studied for deployment in Maricopa County, Arizona and Loudoun County, Virgina using thermal storage capacities from 4 GWh-th to over 1,000 GWh-th (>1 Terawatt-hour). The two sites have different power and transmission systems, available grid energy resources, daily and seasonal load profiles, weather conditions, and grid regulatory requirements. The study results indicate high value for both locations and because of this, likely indicates value across most of the US and the world. The basis of the study was a 1,000 MW-e hourly electric use of DC computing and auxiliary loads, which was modeled as 1 GW-th of thermal load to a dry cooled heat rejection system - i.e. a cooling system that does not consume water. The electric power required for cooling the DC varies as the air temperature changes. In cold weather only the dry-coolers are used, with an electrical load for cooling load as low as 10 MW-e. In hot summer hours, chillers and dry- coolers are required, which raises the electrical load for cooling load to as much as 300 MW-e. The continuous and peak cooling electrical loads result in a grid interconnection requirement of no less than 1,300 MW-e. From both a grid and thermal design modeling perspective the 1.3 GW-e could either be a single facility or result from the total load at multiple sites.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Advanced Materials and Additive Manufacturing for Phase Change Thermal Energy Storage and Management: A Review

Abstract Phase change materials (PCMs) can enhance the performance of energy systems by time shifting or reducing peak thermal loads. The effectiveness of a PCM is defined by its energy and power density—the total available storage capacity (kWh m −3 ) and how fast it can be accessed (kW m −3 ). These are influenced by both material properties as well as geometry of the energy systems; however, prior efforts have primarily focused on improving material properties, namely, maximizing latent heat of fusion and increasing thermal conductivity. The latter is often at the expense of the former. Advanced manufacturing techniques hold tremendous potential to enable co‐optimization of material properties and device geometry, while potentially reducing material waste and manufacturing time. There is an emerging body of research focused on additive manufacturing of PCM composites and devices for thermal energy storage (TES) and thermal management. In this article, the fundamentals and applications of PCMs are reviewed and recent additive manufacturing advances in latent heat TES for both the PCM composite and associated heat exchanger are discussed. A forward‐looking perspective on the future and potential of PCM additive manufacturing for TES and thermal management is provided.

25 ENERGY STORAGE↗
DOE OSTI2022

MPC solution for optimal load shifting for buildings with ON/OFF staged packaged units: Experimental demonstration, and lessons learned

Small and medium-sized commercial buildings (SMCB) are significant demand response resources, and it is important to develop grid-responsive control algorithms that exploit those resources and create financial benefits for building owners and HVAC service providers. Furthermore, unlike large-sized commercial buildings, there is an opportunity to have universally applicable control solutions for many SMCBs since those buildings have a consistent HVAC system configuration: SMCBs are commonly served by multiple-staged air conditioning units controlled by their own thermostats. Despite the demand response potential and scalability, however, very few control solutions are available for SMCBs. Typical model predictive control (MPC) and heuristic control approaches for cooling load shifting that lower thermostat setpoints before an electric price jump are suitable mainly for large-sized commercial buildings where a continuous capacity modulation is possible, e.g., via dampers in variable air volume terminal units. However, those approaches can cause undesired, high peaks for SMCBs due to the nature of ON/OFF unit staging and narrow thermostat deadbands. This could discourage the use of advanced grid-responsive controls for SMCBs due to the concern of high demand charges, and has to be resolved. This paper presents a MPC solution that overcomes this challenge. It has a hierarchical MPC structure where an upper level MPC is responsible for electrical load shifting in response to an electric price signal while a lower level MPC is responsible for coordinating compressor stages to eliminate unnecessary peaks and follows the setpoints determined by the upper level MPC. In this work, two one-month, comprehensive laboratory tests have been carried out to demonstrate load shifting and cost savings for the algorithm. Interesting trade-offs between energy efficiency and load flexibility were observed and are discussed, and lessons learned for applying MPCs for SMCBs are also presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗