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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 217 records · Page 12

Control and Optimization of Energy Storage System in Power Distribution System

The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate fast-charging infrastructure for long-distance trips. Extreme fast charging (XFC) technology can recharge EVs in less than 10 minutes for 200 miles range. Firstly, a novel robust optimization-based mixed integer linear programming model is proposed to size a battery energy storage system (BESS) and PV system in an XFCS. In this part, it is assumed that the sizing and location of the XFCS are known. Secondly, the aforesaid assumption is relaxed, and a strategic multi-period coordinated planning model is proposed to optimally site and size BESS-assisted charging stations in a highway transportation network and PV systems in a power distribution network by considering the coupling between both networks. Optimal operation and control of BESS-assisted EV charging stations are vital to alleviate the adverse impact of extreme fast charging of EVs on the host power network. A joint solution is proposed to mitigate the steady state and transient impact of extremefast charging of EVs and ensure grid-friendly integration of XFCSs with the host grid. Lastly, to make the operation of the XFCS cost-effective, a multi-layered energy management framework is proposed for the XFCS by considering forecast uncertainties, monthly demand charges reduction, and BESS degradation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Maximizing the Benefits of Volt/VAR Optimization in the Presence of Community Energy Storage

This paper reports on the need for coordinating smart grid volt/volt-ampere reactive (VAR) control (VVC) and community energy storage (CES) to maximize the benefits of both approaches. It addresses a key application of volt/VAR optimization (VVO): the conservation of voltage reduction (CVR). The lack of coordination among network controls, such as VVO, and asset controls at the community battery storage system can lead to detrimental effects on grid operation. A smart grid-enabled VVC uses the VVO to perform the CVR operation. VVO can perform numerous tasks for advanced distribution management systems with coordination of the system operator. To achieve the optimal VVC solution, we use a particle swarm optimization driven VVO method. The test system has been simulated for two scenarios-during light loading and high loading condition-with and without the CES system. In both scenarios, the operation of CVR and CES have been performed considering different case studies. The outcomes of the simulated results demonstrate that significant improvement in peak load-demand reduction is achieved by the proposed VVC and CES system with reduced system losses.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Swarm intelligence–based distributed stochastic model predictive control for transactive operation of networked building clusters

To maximize potential energy and cost savings, networked clusters of local buildings are formed for energy transactions. Both centralized and distributed decision approaches were explored in past decades as a way to enable efficient transactive operations. However, online distributed stochastic transactive operation has been overlooked in the literature. To bridge gaps in the research, a bi-level distributed stochastic model predictive control framework was proposed to study the transactive operations of building clusters where a system-level agent is employed to coordinate multiple building agents at the subsystem level. The energy transaction is optimized by a marginal price-based particle swarm optimizer at the system level. Given the energy transaction decisions, each building can independently solve a scenario-based two-stage stochastic model to optimally dispatch the electricity and ancillary services for optimal energy performance. The effectiveness of the proposed framework and coordination algorithm are demonstrated in deterministic, stochastic, and online operations and compared to centralized decisions using several sets of experiments. Additionally, the proposed approach can realize autonomous transactive operation and be extended to community-level building clusters in a plug-and-play way.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Chance-constrained Service Restoration for Distribution Networks with Renewables

Power systems operation is facing great challenges from natural disasters and cyber-attacks. It is critical but also difficult to enhance the reliability and resilience against extreme events. To better response to inevitable outages or blackouts, service restoration in distribution networks is important to minimize the disastrous impacts of catastrophic events. The increasing penetration of distributed energy resources (DERs) provides new opportunities to expedite the restoration process. However, the coordination with conventional distribution system control devices and the uncertainty and variability of intermittent renewable energy resources requires new operation and control strategies for distribution service restoration (DSR). This paper develops an optimal bottom-up DSR strategy by coordinating DERs with voltage regulators and capacitor banks. The chance-constrained (CC) programming approach is used to model the probabilistic output limit of solar radiation and PV generation. The Markov's inequality and Latin hypercube sampling techniques are applied to convert and incorporate the chance constraints into the DSR optimization problem. The CC-DSR problem is formulated as a mixed integer convex programming problem, considering various operational cost functions and bidirectional three-phase unbalanced load flow. Simulation results on the modified IEEE 13-node test feeder system demonstrate the effectiveness and flexibility of the bottom-up DSR strategy.

Chance constrained optimization, Distribution serv↗

Rational Design of a Catalyst for the Selective Monoborylation of Methane

Combined computational and experimental studies elucidate the mechanism and suggest rational design and optimization strategies of a bis(phosphine)-supported iridium-catalyst for methane monoborylation. The activation of the C–H bond in methane via oxidative addition using tris(boryl) iridium(III) complexes bearing bis-chelating supporting ligands is modeled computationally. This model shows that the use of the soft Lewis base ligand such as 1,2-bis(dimethylphosphino)ethane (dmpe) lowers the activation barrier of the rate-determining step as it facilitates polarization of the metal-center, lowering the barrier of the oxidative addition to afford a seven-coordinate iridium(V) intermediate. The experimental optimization of this reaction using high-throughput methods shows that up to 170 turnovers can be achieved at 150 °C (500 psi) within 16 h using bis(pinacolato)diboron, a well-defined homogeneous and monomeric catalyst (dmpe)Ir(COD)Cl that is readily available from commercial precursors, with selectivity for the monoborylation product. High-boiling cyclic aliphatic solvents decalin and cyclooctane also prove suitable for this reaction, while being inert toward borylation. In accordance with the lower calculated activation barrier, catalytic turnover is also observed at 120 °C with up to 50 turnovers over the course of 4 days in cyclohexane solvent. Here, it was found that the borylation of methane is only achieved via one catalytic cycle, and buildup of pinacolborane, a side-product from methane borylation with bis(pinacolato)diboron, inhibits catalytic activity.

computational molecular modeling↗

IDAES-PSE Software Tools for Optimizing Energy Systems and Market Interactions

Modern power grids coordinate electricity production and consumption via multi-scale wholesale energy markets. Historically, levelized cost metrics were the de facto standard for techno-eco-nomic analyses of energy systems and comparison of technology options. However, these metrics neglect the complexity of energy infrastructure including the time-varying value of electricity. An emerging alternative is multi-period optimization, which considers the locational marginal price of electricity as input data (parameters). In this work, we present a general interface for multi-period optimization with time-varying energy prices to facilitate rapid analysis and comparison of potential energy systems models. The PriceTakerModel class is written in the IDAES-PSE platform and allows users to generate a multi-period, price-taker model instance, as well as automatically generate common operational constraints for their model, such as start-up and shutdown. We show this interface successfully generates multi-period price-taker models, facilitates model discrimination, and aids in analyzing various technologies for deployment in unique energy markets.

Laky, Daniel↗

Distributed Rules-Based Deconfliction of ADMS Applications: Part 1: Requirements & Decomposition

This work introduces a rules-based deconfliction methodology for resolving conflicting device control commands issued by advanced power applications considering a range of technical, economic, environmental, and social objectives. The methodology is designed to serve as one of multiple alternative implementations (along with application cooperation and global optimization) for the numerical component of the Deconfliction Pipeline. Development of the methodology is divided into two parts. This first document introduces the requirements, context, and methods for decomposing the deconfliction problem using the Laminar Coordination Framework and Variable Grid Structures. The deconfliction problem is decomposed into a distributed optimization problem based on the concept of quasi-static grid segments, which form independent distributed areas for control and coordination. Selection of the optimal number of decompositions of the deconfliction problem should be made based on a tradeoff analysis between computational speed and global optimality. This second document will define an initial set of technical, economic, and environmental criteria, as well as thirty specific qualitative rules that are used as part of the deconfliction methodology to eliminate non-viable setpoint alternatives. The deconfliction optimization problem is converted into a ranking of individual discrete setpoints, which are scored by the extent to which they satisfy specific decision criteria. The ranking is determined through the concepts of deconfliction exclusivity, priority, and preference. Several multi-criteria decision-making frameworks are examined with the simple multi-attribute rating technique exploiting ranks (SMARTER) recommended as a simple implementation alternative that aligns with the steps of the rules-based deconfliction methodology.

97 MATHEMATICS AND COMPUTING↗

System Design of Dynamic Wireless Power Transfer for Automated Highways

Dynamic wireless power transfer (DWPT) has been proposed as a solution to power electric vehicles (EVs)on future electrified highways. However, there has been little consideration of how the coordination of electric connected and automated vehicles (CAVs) could impact DWPT system designs in future scenarios. In this paper, a DWPT system design is optimized for a future highway where CAVs travel in coordinated groups, with each CAV in the group powered by the same DWPT section. As the distribution of smaller light-duty vehicles (LDVs) and larger heavy-duty vehicles (HDVs) in each group is varied, the DWPT system power level, transmitter length, and the equivalent receiver loads are adjusted to minimize the infrastructure requirements and energy losses of the DWPT system. The outputs from this analysis are used to determine the optimal groupings of vehicles for a given DWPT system. The analysis suggests that CAV coordination could aid the deployment of DWPT systems and reduce the overall infrastructure and energy losses of DWPT systems.

Foote, Andrew↗

Origin of 6-fold coordinated aluminum at (010)-type pyrophyllite edges

To better understand the aqueous chemical reactivity of clay mineral edges we explored the relationships between hydration and the structure of (010)-type edges of pyrophyllite. In particular, we used density functional theory and the quantum theory of atoms in molecules to evaluate the stability of 6-fold coordinated hydrated aluminum at the edge in terms of the electron density distribution. Geometrical optimization revealed an intra-edge hydrogen bond network between aluminol hydroxyls and water ligands completing the aluminum coordination shell. From the electron density isosurfaces one water ligand is not covalently bonded to aluminum. Bader charge analysis revealed that there is a small charge transfer between this water ligand and the aluminum that stabilizes its location, but which derives from the formation of the hydrogen bond network and not from Al-OH 2 interaction per se. To clarify which edge species make the most significant hydrogen bond to this water ligand, we evaluate Bader charges in edge systems including 5-fold coordinated aluminums with and without geometrical optimization. From this comparison the charge transfer is a combined result of charge transfer from the aluminum to aluminol hydroxyls and then from aluminol hydroxyls to OH 2 ligands. This suggests that the weakly bound water ligand in question, and more generally 6-fold hydrated edge Al coordination, is stabilized primarily by the hydrogen bond network which in turn leads to weak ionic attraction to the aluminum center itself. The finding highlights the importance of cooperative effects between solvent structure and the coordination of metal cations exposed at clay mineral edges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of Aggregated EV Flexibility With TSO-DSO Coordination

Electric vehicles (EVs) are becoming a promising source of grid ancillary services due to the temporal and spatial charging flexibility, quick response and storage capability. Such advantages are increasing with government policy promotion and technology improvement. However, the exploration of EV flexibility requires the coordination of both transmission system operators (TSOs) and distribution system operators (DSOs), to ensure the safe and reliable operation of power network. In this paper, we propose a coordinated evaluation method that determines the optimal utilization of EV temporal flexibility without compromising EV owners’ usage. At the distribution level, DSOs first evaluate EV aggregators’ operational boundaries to exploit distribution level services. At the transmission level, TSOs then determine EV charging schedules and ancillary service capacity simultaneously, taking into account the requirement from DSOs. Here, we validate the model in a case study using the IEEE 123 node test feeder and EV charging sessions obtained from a transportation simulation tool that uses real-world data.

33 ADVANCED PROPULSION SYSTEMS↗

Metal–Nitrogen–Carbon Cluster–Decorated Titanium Carbide is a Durable and Inexpensive Oxygen Reduction Reaction Electrocatalyst

Clusters of nitrogen- and carbon-coordinated transition metals dispersed in a carbon matrix (e. g., Fe-N-C) have emerged as an inexpensive class of electrocatalysts for the oxygen reduction reaction (ORR). In this work, it was shown that optimizing the interaction between the nitrogen-coordinated transition metal clusters embedded in a more stable and corrosion-resistant carbide matrix yielded an ORR electrocatalyst with enhanced activity and stability compared to Fe-N-C catalysts. Utilizing first-principles calculations, an electrostatics-based descriptor of catalytic activity was identified, and nitrogen-coordinated iron (FeN 4 ) clusters embedded in a TiC matrix were predicted to be an efficient platinum-group metal (PGM)-free ORR electrocatalyst. Guided by theory, selected catalyst formulations were synthesized, and it was demonstrated that the experimentally observed trends in activity fell exactly in line with the descriptor-derived theoretical predictions. The Fe-N-TiC catalyst exhibited enhanced activity (20 %) and durability (3.5-fold improvement) compared to a traditional Fe-N-C catalyst. It was posited that the electrostatics-based descriptor provides a powerful platform for the design of active and stable PGM-free electrocatalysts and heterogenous single-atom catalysts for other electrochemical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advanced Laboratory and Field Arrays: Technical Report for Performance Enhancement for Marine Energy Converter (MEC) Arrays (Task 5)

Task 5 consisted of two parts, wave energy converter (WEC) arrays and current energy converter (CEC) arrays. The two parts of the project were executed independently, and this report covers only the work on WECs. In this part of the task, the team characterized the behavior of and developed control schemes for wave energy converter (WEC) arrays that improved performance (i.e., maximized aggregate power generation and reduced the levelized cost of energy) over baseline, non-coordinated control approaches. Specifically, for WEC arrays: the team developed optimal layouts of arrays that considered the effect of WEC placement within an array on coordinated array control with real-time estimation schemes. The numerical codes developed through this task were made available to users for array design. These tools utilized existing commercial software as well as software developed within the project team.

13 HYDRO ENERGY↗

Coordinated PEV Charging for Distribution System Management

Plug-in electric vehicles (PEVs) can help to reduce worldwide dependence on petroleum and carbon emissions. In the past a few years, PEVs have received considerable attention as an eco-friendly and cost-effective alternative to conventional gasoline vehicles. PEVs consume higher power from the grid during charging compared to conventional residential loads. Therefore, the emerging fleet of PEVs will introduce a considerable amount of additional load on power system. On the other hand, majority of PEVs are parked for more than 90% of the time, making them ideal for providing various services through Electric Vehicle Supply Equipment (EVSE), a.k.a. charging stations which are PEVs’ connection points to the power system. In this project, coordinated PEV charging are developed to provide distribution system services, considering PEV characteristics, realistic travel pattern, charging behaviors, and EVSE power rating and availability. The main efforts and contributions are summarized as follows. • Mobility models and EVSE charging capability/availability are indispensable for evaluating PEV charging coordination strategies and developing PEV charging control. Many existing studies utilize simplified mobility models assuming that the entire vehicle fleet returns home in the evening and is parked at home until the next morning. Some other PEV models better represent diversified home arrival and departure time, but cannot capture varying charging flexibility and capability at different locations, and therefore are not appropriate to study the impacts of public EVSE on PEV load and utilization. In this work, a mobility and charging flexibility model is proposed to better represent the temporal availability and varying charging capability from PEV onboard charger and EVSE. • Based on the mobility model, a generalized optimization method is proposed to evaluate different PEV charging coordination strategies. In existing literature, different algorithms and methods need to be designed to evaluate each charging strategy from both vehicle owners’ and system’s perspective. With the optimization method proposed in this work, different charging control strategies can be studied and compared by only updating objective functions. Moreover, optimization tricks are provided to convert the optimization problems to equivalent linear programming problems, which can be efficiently solved with existing solvers. • An innovative scheduling and control framework is proposed to enable smart PEV charging for grid services while meeting PEV owners’ travel needs. In the proposed framework, each set of EVSE is equipped with a controller that estimates charging power and energy flexibility based on vehicle characteristics, EVSE power rating, battery energy state, and upcoming trip information. With the simplified charging flexibility model received from each EVSE controller, the central coordinator determines the optimal power allocation for a look-ahead time window for the given grid services. The proposed charging control can help reduce the computational complexity and communication requirement compared with existing methods. It is also scalable to the expanding PEV fleet and robust to uncertainties in upcoming vehicle trips and future system condition. • The proposed charging strategy evaluation and smart charging control methods are applied to one of the prototypical feeders developed by the Pacific Northwest National Laboratory (PNNL) for case studies. Detailed trip information extracted from the National Household Travel Survey (NHTS) is used to represent travel and parking patterns. Different scenarios are simulated to evaluate the performance of the proposed methods and understand how PEV mobility and public EVSE availability affect PEV load and potential grid services.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optimization Methods for Evaluating PEV Charging Considering Customer Behavior

Plug-in electric vehicles (PEVs) can be connected to grid through electrical vehicle supply equipment (EVSE) to provide various grid services in addition to battery charging. This paper evaluates loading condition of a distribution system with a medium penetration of PEVs considering different charging strategies and public EVSE availability. A mobility and charging flexibility model is proposed to capture PEVs’ temporal availability and varying charging capability at different parking locations. Detailed trip information extracted from the National Household Travel Survey is used to represent travel and parking patterns. An optimization method is then proposed to coordinate PEV charging to effectively shift load from peak to off-peak hours. One of the prototypical feeders developed by the Pacific Northwest National Laboratory is studied in different scenarios.

Wu, Di↗

A Hierarchical Volt-var Optimization with Discrete Variables in Unbalanced Distribution Systems

This paper proposes a framework to determine the optimal active and reactive power dispatch of distributed photovoltaic (PV) generation, switched capacitors, and voltage regulators in multi-phase unbalanced distribution systems. The objectives of the optimal dispatch are minimization of the energy loss, PV real power curtailment, and switching operations of capacitors and voltage regulators, in addition to elimination of voltage violation and reverse power flow. The optimization problem is formulated in rectangular coordinates as a nonlinear, nonconvex problem with discrete variables. A hierarchical twostage framework is proposed to effectively handle those discrete variables and reduce the computational time compared to the unified approach in which all variables are solved simultaneously. The efficacy of the proposed approach and the accuracy of the obtained numerical solution is validated using the unbalanced multi-phase IEEE 34-bus with 15-minute load and PV data.

Nguyen, Quan H.↗

Distributed Load Shedding Application Architecture and Bi-Level Predictive Estimator Algorithm

Increasing penetrations of distributed renewables are decreasing the effectiveness of traditional decentralized under-frequency load shedding (UFLS) schemes. As more distribution circuits begin to back-feed the transmission system, operation of traditional UFLS may exacerbate frequency instability. This paper presents the conceptual framework for a data-rich environment to coordinate UFLS across multiple distribution providers based on the laminar coordination framework in order to ensure optimal adaptive setting of UFLS relays. Communication and control are enabled through a distributed implementation of the IEC 61968-1 Common Information Model message bus structure. In addition to the proposed architecture, a novel adaptive UFLS scheme informed by a bi-level state estimator to create optimal relay setpoints is introduced. Initial simulation results are presented for the IEEE 14-bus test system on scenarios leading to mis-operation of traditional UFLS.

Anderson, Alexander A.↗

Disruption of starch biosynthesis and triacylglycerol degradation impairs growth but improves photosynthesis in Arabidopsis

Enhancing lipid accumulation by redirecting carbon from starch to triacylglycerol (TAG) in vegetative tissues is a promising strategy for developing high-energy-density crops for bioenergy production. However, our understanding of how starch and TAG metabolism interact and how this interaction affects growth and photosynthesis is incomplete. Here, we investigated the metabolic and physiological consequences of disrupting starch biosynthesis and TAG turnover in Arabidopsis thaliana by generating single, double, and triple mutants involving ADG1 (starch biosynthesis), TGD1 (lipid trafficking), and SDP1\\\\\\\\r\\\\\\\\n(TAG lipase). Unexpectedly, elimination of starch biosynthesis lowered TAG levels in the high-TAG-accumulating tgd1 mutant, primarily through enhanced TAG breakdown. This decline was completely reversed by sucrose supplementation, suggesting that TAG degradation was induced by carbon limitation.\\\\\\\\r\\\\\\\\nGenetic suppression of TAG turnover via SDP1 disruption in the starchless tgd1 adg1-1 background led to a nine-fold rise in leaf TAG accumulation in the tgd1 sdp1 adg1-1 triple mutant, together with enhanced photosynthetic performance. However, this metabolic reprogramming incurred growth penalties.\\\\\\\\r\\\\\\\\nOur results highlight the role of dynamic TAG turnover in maintaining metabolic balance and photosynthesis in starch-deficient backgrounds. These findings underscore the need for refined metabolic engineering strategies that coordinate TAG biosynthesis and degradation to optimize lipid accumulation in bioenergy crops.

59 BASIC BIOLOGICAL SCIENCES↗