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At least 1,135 records · Page 63

Bill Savings vs. Backup Power: Evaluating operational tradeoffs for home solar+storage systems [Slides]

Adoption of residential solar photovoltaic+energy storage systems (PVESS) is driven by both bill savings opportunities and customer demand for backup power. Prior work by this team (Gorman et al., 2022; Gorman et al., 2023) explored PVESS backup power capabilities during long-duration power interruptions (e.g., due to severe weather events), when customers are assumed to be able to anticipate the event and charge their batteries in advance. In many cases, however, power interruptions are unpredictable (and often relatively short); for those types of events, a customer will typically set its battery to maintain some minimum capacity in reserve in case of an interruption, which reduces the capacity available for managing utility bills. This study evaluates this operational tradeoff to help customers and installers configure backup reserve settings, and to inform decision-making more generally about the customer value of backup power services compared to utility bill savings. This study utilizes Berkeley Lab’s PRESTO tool to produce stochastic simulations of (predominantly short-duration) power interruption events, and builds on an earlier case-study demonstrating PVESS backup performance during short-duration interruptions (Baik et al., 2023).

14 SOLAR ENERGY↗

Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency

Behind-the-meter distributed energy resources (DERs), including building solar photovoltaic (PV) technology and electric battery storage, are increasingly being considered as solutions to support carbon reduction goals and increase grid reliability and resiliency. However, dynamic control of these resources in concert with traditional building loads, to effect efficiency and demand flexibility, is not yet commonplace in commercial control products. Traditional rule-based control algorithms do not offer integrated closed-loop control to optimize across systems, and most often, PV and battery systems are operated for energy arbitrage and demand charge management, and not for the provision of grid services. More advanced control approaches, such as MPC control have not been widely adopted in industry because they require significant expertise to develop and deploy. Recent advances in deep reinforcement learning (DRL) offer a promising option to optimize the operation of DER systems and building loads with reduced setup effort. However, there are limited studies that evaluate the efficacy of these methods to control multiple building subsystems simultaneously. Additionally, most of the research has been conducted in simulated environments as opposed to real buildings. This paper proposes a DRL approach that uses a deep deterministic policy gradient algorithm for integrated control of HVAC and electric battery storage systems in the presence of on-site PV generation. The DRL algorithm, trained on synthetic data, was deployed in a physical test building and evaluated against a baseline that uses the current best-in-class rule-based control strategies. Performance in delivering energy efficiency, load shift, and load shed was tested using price-based signals. The results showed that the DRL-based controller can produce cost savings of up to 39.6% as compared to the baseline controller, while maintaining similar thermal comfort in the building. The project team has also integrated the simulation components developed during this work as an OpenAIGym environment and made it publicly available so that prospective DRL researchers can leverage this environment to evaluate alternate DRL algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A decade of insights: Delving into calendar aging trends and implications

Lithium-ion batteries remain at rest for extended periods and experience calendar aging. Although lithium-ion batteries are expected to perform for over 10 years at room temperature, long-term calendar aging data are seldom reported over such timescales. We present a dataset from 232 commercial cells across eight cell types and five manufacturers that underwent calendar aging across various temperatures and states of charge (SOCs) for up to 13 years. We analyze calendar aging across these conditions by tracking capacity loss and resistance growth as the cells degrade. This dataset is used to validate simple models, primarily the Arrhenius law and the power law, which explain the temperature and storage time on calendar aging. Certain applications of Arrhenius and power law fail to describe the dependence of capacity loss on temperature and resistance growth on storage time. Through this dataset, we demonstrate the complexity of calendar aging and the challenges in reducing trends into phenomenological models.

25 ENERGY STORAGE↗

Interaction energy and isosteric heat of adsorption between hydrogen and magnesium diboride

Hydrogen storage materials form a crucial research topic for future energy utilization employing hydrogen and among those of interest magnesium diboride (MgB 2 ) has shown its prevalence. In this study, a first-principles analytical adsorption model of one hydrogen molecule in the vicinity of various magnesium diboride crystal surfaces was developed in order to obtain surface thermodynamic properties as a function of molecular and lattice properties. Henry's law constant (K H ) and isosteric heat of adsorption (ΔH ads ) indicators of the affinity between a gaseous molecule and a solid surface are thus calculated. The results in this paper not only address questions pertaining to the first stage of hydrogen storage processes but also advance the understanding of physisorption thermodynamics of a neutral molecule (H 2 ) coming in contact with a layered metallic-like surface (MgB 2 ). Although the model is built from a framework of classical calculations, quantum effects are incorporated as the fractional charge of the ions on the free surfaces, which is essential for the calculation of analytic thermodynamic values that approximate calculations from other methods. To benchmark our theoretical models, periodic density functional calculations were performed to determine the interactions between H 2 and different MgB 2 surfaces from first-principles. By considering both the top and sublayers of MgB 2 in calculating interaction energy, we have analytically and computationally calculated the interaction energies of H 2 molecules and MgB 2 's terminated planes, and witnessed the strong dependence of interaction energies on surface charges. We have also observed a dipole flipping phenomenon which explains the discontinuity seen in the interaction energy graph of Mg(0001). Both analytical and computational results showed heat of adsorption at zero coverage varying at a very low range (<7 kJ mol -1 ).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development and Demonstration of Medium-Heavy Duty PHEV Work Trucks

The heavy-duty vehicle market (Class 6-8) has been a difficult segment for the introduction of plug-in vehicles due to the large energy storage requirement (with corresponding cost), challenging duty cycles, and the diversity of vehicle configurations. The Work Truck market represents a significant opportunity for Heavy-Duty PHEV adoption. (1) The usage cycle includes driving and stationary/worksite power requirements, ensuring full daily usage of the grid-charged battery (battery size: 15-30kWhr). Though daily driving can often be short (an average of 26 miles per day), worksite power includes substantial demand (hydraulics, exportable 110/220V power, 12V support, HVAC). (2) Worksite power demands for conventional vehicles require continuous loaded engine operation, resulting in significant emissions, fuel consumption and noise impacts. (3) These trucks serve an industry that is highly diverse in final vehicle duty cycle, configuration, and jobsite power demands resulting in the need for a modular, configurable hybrid solution. Through this program, Odyne has developed and demonstrated a medium/heavy duty plug-in hybrid solution capable of meeting the needs of the work truck market while delivering fuel and emissions reductions of 50% or greater when evaluated against the full-day work truck duty cycle. The Odyne system developed in this project was released for commercial sale as the G2V7 Odyne Plug-in Hybrid and ePTO systems. The testing and field demonstration proved that the Odyne hybrid system is capable of reducing work truck fuel use and emissions by over 50% while subsequent commercial sales demonstrate the flexibility of the modular design and the capability to support electric systems of 12 – 30 kW and hydraulic based systems of 60 kW (80 HP) or greater. Odyne is continuing to work with suppliers on reducing component costs and working with supporting agencies to initiate projects to increase the driving and full day fuel and emissions savings in order to continue to improve the customer value and return on investment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Integrated Transportation-Energy Systems Modeling

Transportation is currently the least-diversified energy demand sector, with over 90% of global transportation energy use coming from petroleum product. After over a century of petroleum dominance, however, many leading experts anticipate major electrification trends that could disrupt the transportation energy demand landscape. These changes in electricity demand complement profound changes happening within electric power supply systems, including integration of variable renewables, distributed generation and storage, and greater participation in power system planning and operations from traditionally passive consumers. This broader context underscores the importance of understanding how transportation electrification will impact electricity demand, including changes in the load shapes that characterize the system and the opportunity to leverage flexible EV charging to more cost-effectively balance demand and supply. This talk provides an overview of recent findings on infrastructure requirements to support EV adoption, integration challenges and the impact of EV on power systems, and opportunities to leverage flexible (or smart) EV charging to support power system planning and operations.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

A Segregated Approach for Modeling the Electrochemistry in the 3-D Microstructure of Li-Ion Batteries and Its Acceleration Using Block Preconditioners

Abstract Battery performance is strongly correlated with electrode microstructure. Electrode materials for lithium-ion batteries have complex microstructure geometries that require millions of degrees of freedom to solve the electrochemical system at the microstructure scale. A fast-iterative solver with an appropriate preconditioner is then required to simulate large representative volume in a reasonable time. In this work, a finite element electrochemical model is developed to resolve the concentration and potential within the electrode active materials and the electrolyte domains at the microstructure scale, with an emphasis on numerical stability and scaling performances. The block Gauss-Seidel (BGS) numerical method is implemented because the system of equations within the electrodes is coupled only through the nonlinear Butler–Volmer equation, which governs the electrochemical reaction at the interface between the domains. The best solution strategy found in this work consists of splitting the system into two blocks—one for the concentration and one for the potential field—and then performing block generalized minimal residual preconditioned with algebraic multigrid, using the FEniCS and the Portable, Extensible Toolkit for Scientific Computation libraries. Significant improvements in terms of time to solution (six times faster) and memory usage (halving) are achieved compared with the MUltifrontal Massively Parallel sparse direct Solver. Additionally, BGS experiences decent strong parallel scaling within the electrode domains. Last, the system of equations is modified to specifically address numerical instability induced by electrolyte depletion, which is particularly valuable for simulating fast-charge scenarios relevant for automotive application.

25 ENERGY STORAGE↗

An overview of cobalt-free, nickel-containing cathodes for Li-ion batteries

The need for high-energy, low-cost batteries is projected to grow dramatically in the next decade due to electrification of the transportation market. Such demands are straining Li-ion supply chains for critical materials including lithium, nickel, and cobalt. Price instability, environment toxicity, and limits in the absolute supply lead to great concern for the continued use of cobalt. Similar to cobalt, the required grade of nickel for batteries, known as Class 1 nickel, has also been declining due to geological scarcity and low incentive prices. Herein, this review summarizes alternative cathode chemistries with no cobalt and reduced nickel content for high-energy Li-ion batteries targeting sustainable growth in the electric vehicle market. Further, the primary challenges associated with each material system are generally classified as being related to four common categories: (1) ion instability during charging, (2) poor electronic conductivity, (3) poor ionic conductivity, and (4) poor thermal stability.

25 ENERGY STORAGE↗

A Propane Hydronic Heat Pump with Energy Storage

Propane is an environment-friendly refrigerant, having a 20-year GWP (global warming potential) of 0.072 and a 100-year GWP of 0.02, as compared to R-410A having a GWP > 2000. It has superior thermodynamic cycle performance and heat transfer characteristics. However, propane is classified as a A3 refrigerant, which is highly flammable, and not allowed to be used indoor if the system charge is higher than 150 grams. It is a challenge to use propane in residential applications requiring a rated capacity larger than 10 k Watts. A hydronic heat pump, i.e., containing propane in an outdoor unit and distributing the cooling and heating capacity through a hydronic coil to the indoor space addresses the flammability issue, while maintaining a high efficiency. We developed a hydronic heat pump with propane, it uses a two-stage compressor, a brazed plate indoor heat exchanger, and a microchannel outdoor heat exchanger. It achieves a rated cooling capacity larger than 10 k Watts, and a cooling SEER (cooling seasonal energy efficiency rating) > 16.0 (cooling seasonal COP > 4.7) and a heating HSPF (heating seasonal performance factor) > 9.5 (heating seasonal COP > 2.78), while requiring a system charge < 1200 grams. Additionally, the hydronic heat pump was evaluated in a laboratory water heating loop to heat a 50-gallon water tank in a full condensing mode. Experiments of heating the tank water from 58F(14.4°C) to 150F(65.6°C) were conducted under ambient temperatures from 17F(-8.3°C) to 75F(23.9°C), at the compressor high and low stages.

Shen, Bo↗

A Novel Modular, Reconfigurable Battery Energy Storage System: Design, Control, and Experimentation

This paper presents a novel modular, reconfigurable battery energy storage system. The proposed design is characterized by a tight integration of reconfigurable power switches and DC/DC converters. This characteristic enables isolation of faulty cells from the system and allows fine power control for individual cells toward optimal system-level performance. An optimal power management approach is developed to extensively exploit the merits of the proposed design. Based on receding-horizon convex optimization, this approach aims to minimize the total power losses in charging/discharging while allocating the power in line with each cell’s condition to achieve state of-charge (SoC) and temperature balancing. By appropriate design, the approach manages to regulate the power of a cell across its full SoC range and guarantee the feasibility of the optimization problem. Here, we perform extensive simulations and further develop a lab-scale prototype to validate the proposed system design and power management approach.

25 ENERGY STORAGE↗

Minimizing Inter‐Lattice Strain to Stabilize Li‐Rich Cathode by Order–Disorder Control

Li-rich Mn-based layered (LMR) cathodes with anionic redox chemistry show great potential for next-generation sustainable Li-ion battery (LIB) applications due to the low cost and high energy density. However, the asynchronous structural evolutions with cycling in the heterogeneous composite structure of LMR lead to serious lattice strain and thus fast electrochemical decay, which hinders the commercialization of LMR cathodes. Here, in this study, an order–disorder coherent LMR cathode is demonstrated that exhibits a higher average voltage (by 0.25 V), negligible voltage decay (97.6% voltage retention after 100 cycles at 100 mA g −1 ), and enhanced cycling stability (98% capacity retention after 200 cycles at 100 mA g −1 ) compared to its layered oxide counterparts. It is proposed that this order–disorder coherent structure design can promote a more synchronous and homogeneous structure evolution during charge and discharge, thus minimizing lattice strain, which significantly prevents layer collapse and collective degradation at high voltage, improving the electrochemical stability. The study displays the feasibility of optimizing the performance of Li-rich cathode materials through a dedicated order–disorder structure control for sustainable energy storage.

Xu, Shenyang [Peking University, Shenzhen (China)]↗

Battery asset management with cycle life prognosis

We report Battery Asset Management problem determines the minimum cost replacement schedules for each individual asset in a group of battery assets that operate in parallel. Battery cycle life varies under different operating conditions including temperature, depth of discharge (DOD), charge rate, etc., and a battery deteriorates due to usage, which cannot be handled by current asset management models. This paper presents a new battery asset management methodology where battery cycle life prognosis is integrated with parallel asset management to reduce lifecycle cost of the Battery Energy Storage Systems (BESS). For the battery failure time prognosis, a nonlinear physics-based battery capacity fade model is developed and incorporated in parallel asset management model to update battery capacity over time. Experiment results have shown that the developed battery asset management methodology can be conveniently used to facilitate BESS asset management decision making thereby decreasing asset lifecycle costs.

25 ENERGY STORAGE↗

Template-Assisted Growth of High-Quality α-Phase FAPbI 3 Crystals in Perovskite Solar Cells Using Thiol-Functionalized MoS 2 Nanosheets

Formamidinium lead iodide (FAPI) has gained attention for hybrid perovskite solar cell (PSC) applications due to its enhanced stability and narrow bandgap. However, a significant challenge remains in inducing and stabilizing the elusive perovskite “black phase”—photoactive cubic α-FAPI—as the relatively bulky FA + cations tend to favor the thermodynamically stable nonphotoactive “yellow phase”. Here, in this study, we present a templated growth strategy employing thiol-functionalized MoS 2 nanosheets as templates. By introduction of 3-mercaptopropionic acid (MPA)-functionalized MoS 2 as a growth template, precise control over crystal formation was achieved, favoring the growth of high-quality α-FAPI films. These advanced templated films exhibited substantial improvements in charge transport properties, efficient light absorption, and enhanced charge extraction. As a result, the PSCs achieved a significantly enhanced power conversion efficiency (PCE) compared to the nontemplated control device, increasing from 20.6 to 22.5%. The MoS 2 -incorporated device also demonstrated excellent shelf stability, maintaining 91% of the initial PCE even after 1600 h of storage without device encapsulation.

36 MATERIALS SCIENCE↗

Numerical Study and Validation of Melting and Solidification in PCM Embedded Heat Exchangers with Straight Tube

Latent heat thermal energy storage (LHTES) systems have shown great potential to enable reliable use of renewable energy and load shifting. LHTES offer high storage density and release energy at near constant temperature because of its use of phase change materials (PCMs). The cylindrical PCM heat exchangers (PCMHX) are one of the most used technologies due to their simplicity. Numerical models for such PCMHX enable engineers to estimate their performance for different design parameters and operating conditions without having to test them all. However, modeling the phase change phenomena can be challenging. To better understand the difficulties involving accurate modeling of PCMHX, a cylindrical latent storage unit filled with PCM and water as in-tube heat transfer fluid (HTF) is numerically investigated. This paper presents a study based on a 2D-axisymmetric model of a straight tube embedded in PCM in a cylindrical container. CFD is used to study the charging (melting) and discharging (solidification) phenomena. The models are validated against experimental and numerical data from the literature. The predicted local PCM temperature profile over time agrees within 2K compared to the experimental values. The paper also presents a simple method to estimate the melting and solidification phase change temperature range from limited data provided by PCM manufacturers.

PCM, melting, solidification, CFD, heat exchanger↗

Active Learning Guided Computational Discovery of Plant-Based Redoxmers for Organic Nonaqueous Redox Flow Batteries

Organic nonaqueous redox flow batteries (ONRFBs) are promising energy storage devices due to their scalability and reliance on sourceable materials. However, finding suitable redox-active organic molecules (redoxmers) for these batteries remains a challenge. Using plant-based compounds as precursors for these redoxmers can decrease their costs and environmental toxicity. In this computational study, flavonoid molecules have been examined as potential redoxmers for ONRFBs. Flavone and isoflavone derivatives were selected as catholyte (positive charge carrier) and anolyte (negative charge carrier) molecules, respectively. To drive their redox potentials to the opposite extremes, in silico derivatization was performed using a novel algorithm to generate a library of > 40000 candidate molecules that penalizes overly complex structures. A multiobjective Bayesian optimization based active learning algorithm was then used to identify best redoxmer candidates in these search spaces. Furthermore, our study provides methodologies for molecular design and optimization of natural scaffolds and highlights the need of incorporating expert chemistry awareness of the natural products and the basic rules of synthetic chemistry in machine learning.

25 ENERGY STORAGE↗

Designing lithium halide solid electrolytes

All-solid-state lithium batteries have attracted widespread attention for next-generation energy storage, potentially providing enhanced safety and cycling stability. The performance of such batteries relies on solid electrolyte materials; hence many structures/phases are being investigated with increasing compositional complexity. Among the various solid electrolytes, lithium halides show promising ionic conductivity and cathode compatibility, however, there are no effective guidelines when moving toward complex compositions that go beyond ab -initio modeling. Here, we show that ionic potential, the ratio of charge number and ion radius, can effectively capture the key interactions within halide materials, making it possible to guide the design of the representative crystal structures. This is demonstrated by the preparation of a family of complex layered halides that combine an enhanced conductivity with a favorable isometric morphology, induced by the high configurational entropy. This work provides insights into the characteristics of complex halide phases and presents a methodology for designing solid materials.

25 ENERGY STORAGE↗

Performance of a Hybrid HVAC-Integrated Thermal Storage Device

Thermal equipment in buildings is a primary contributor to peak loads on the electrical grid. Thermal energy storage is a cost-effective strategy to decouple electric use from thermal loads, thus reducing grid peak costs for building owners. One method for storing thermal energy in a building is to integrate a phase change material (PCM) directly into the heating, ventilation, and air conditioning system. These systems often require additional glycol loops, pumps, valves, and heat exchangers to couple the storage to the cooling system and building space, which increases the complexity and cost. This work will discuss an alternate approach where the storage is added directly into the heat pump evaporator. A detailed two-dimensional finite difference heat transfer model of a PCM-refrigerant-glycol heat exchanger was developed to simulate the performance of this component. The fluid stream was discretized along the flow direction to capture changes in the fluid properties and local heat transfer rates, and the phase change material was discretized in both the x and y directions to capture the movement of the melt front. The model was used to understand the impact of different material and geometric properties on the charge and discharge characteristics of the device. Finally, a Ragone framework analogous to that used for electrochemical batteries was used to maximize the energy density and round-trip efficiency of the device while supplying loads appropriate for space cooling in buildings.

buildings↗

Feasibility study of Mg storage in a bilayer silicene anode via application of an external electric field

With the goal of developing a Si-based anode for Mg-ion batteries (MIBs) that is both efficient and compatible with the current semiconductor industry, the current research utilized classical Molecular Dynamics (MD) simulation in investigating the intercalation of a Mg 2+ ion under an external electric field (E-field) in a 2D bilayer silicene anode (BSA). First principles density functional theory calculations were used to validate the implemented EDIP potentials. Our simulation shows that there exists an optimum E-field value in the range of 0.2–0.4 V Å –1 for Mg 2+ intercalation in BSA. To study the effect of the E-field on Mg 2+ ions, an exhaustive spread of investigations was carried out under different boundary conditions, including calculations of mean square displacement (MSD), interaction energy, radial distribution function (RDF), and trajectory of ions. Our results show that the Mg 2+ ions form a stable bond with Si in BSA. The effects of E-field direction and operating temperature were also investigated. In the X–Y plane in the 0°–45° range, 15° from the X-direction was found to be the optimum direction for intercalation. The results of this work also suggest that BSA does not undergo drastic structural changes during the charging cycles with the highest operating temperature being ~300 K

25 ENERGY STORAGE↗