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DOE OSTI2021

Platinum-complexed phosphorous-doped carbon nitride for electrocatalytic hydrogen evolution

Sustainable hydrogen gas production is critical for future fuel infrastructure. Here, a series of phosphorous-doped carbon nitride materials were synthesized by thermal annealing of urea and ammonium hexafluorophosphate, and platinum was atomically dispersed within the structural scaffold by thermal refluxing with Zeise's salt forming Pt–N/P/Cl coordination interactions, as manifested in X-ray photoelectron and absorption spectroscopic measurements. The resulting materials were found to exhibit markedly enhanced electrocatalytic activity towards the hydrogen evolution reaction (HER) in acidic media, as compared to the P-free counterpart. This was accounted for by P doping that led to a significantly improved charge carrier density within C 3 N 4 , and the sample with the optimal P content showed an overpotential of only –22 mV to reach the current density of 10 mA cm –2 , lower than that of commercial Pt/C (–26 mV), and a mass activity (7.1 mA μg –1 Pt at –70 mV vs. reversible hydrogen electrode) nearly triple that of the latter. Finally, results from the present study highlight the significance of P doping in the manipulation of the electronic structures of metal/carbon nitride nanocomposites for high-performance HER electrocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Data-Driven Pricing Strategy for Demand-Side Resource Aggregators

We consider a utility who seeks to coordinate the energy consumption of multiple demand-side flexible resource aggregators. For the purpose of privacy protection, the utility has no access to the detailed information of loads of resource aggregators. Instead, we assume that the utility can directly observe each aggregator's aggregate energy consumption outcomes. Furthermore, the utility can leverage resource aggregator energy consumption via time-varying electricity price profiles. Based on inverse optimization technique, we propose an estimation method for the utility to infer the energy requirement information of aggregators. Subsequently, we design a data-driven pricing scheme to help the utility achieve system-level control objectives (e.g., minimizing peak demand) by combining hybrid particle swarm optimizer with mutation algorithm and an iterative algorithm. Case studies have demonstrated the effectiveness of the proposed approach against two benchmark pricing strategies-a flat-rate scheme and a time-of-use scheme.

data-driven optimization↗

DOE OSTI2024

High- and Mid-Fidelity Modeling Comparison for a Floating Marine Turbine System

There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial-flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that are neglected for wind turbines. These include buoyancy, added mass and inertial loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbines at a speed comparable to real time. While efficient for large sets of load cases and design studies, mid-fidelity codes make simplifying assumptions that may impact their accuracy. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system was modeled both with OpenFAST and with the commercial CFD code STAR-CCM+. The CFD model used a three-dimensional unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modeled with a custom coupling of the CFD solver with the open-source code MoorDyn. This improves upon the existing quasi-static catenary solver in STAR-CCM+, which lacks seabed contact or line-to-line connections. Simulation results for a floating marine turbine are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.

CFD↗

DOE OSTI2023

Localization of Zn 2+ ions affects the structural folding and mechanics of Nereis virens Nvjp-1

Several biological organisms utilize metal-coordination bonds to produce remarkable materials, such as the jaw of the marine worm Nereis virens, where metal-coordination bonds yield remarkable hardness without mineralization. Though the structure of a major component of the jaw, the Nvjp-1 protein, has recently been resolved, a detailed nanostructural understanding of the role of metal ions on the structural and mechanical properties of the protein is missing, especially with respect to the localization of metal ions. In this work, atomistic replica exchange molecular dynamics with explicit water and Zn 2+ ions and steered molecular dynamics simulations were used to explore how the initial localization of the Zn 2+ ions impacts the structural folding and mechanical properties of Nvjp-1. We found that the initial distribution of metal ions for Nvjp-1, and likely for other proteins with high amounts of metal-coordination, has important effects on the resulting structure, with larger metal ion quantity resulting in a more compact structure. These structural compactness trends, however, are independent from the mechanical tensile strength of the protein, which increases with greater hydrogen bond content and uniform distribution of metal ions. Our results indicate that different physical principles underlie the structure or mechanics of Nvjp-1, with broader implications in the development optimized hardened bioinspired materials and the modeling of proteins with significant metal ion content.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

A Q-band frequency tunable Doppler backscattering (DBS) system for pedestal and scrape-off layer density fluctuation and flow measurements in the DIII-D tokamak

We present the design and laboratory tests for a new Q-band frequency tunable Doppler backscattering (DBS) system suitable for probing poloidal wavenumber kñ = 6–8 cm−1 density fluctuations and their flow velocities in the pedestal and scape-off layer (SOL) of the DIII-D tokamak. This system will provide new measurements in the increasingly important and under-diagnosed far pedestal and SOL plasma regions. These results are important for experimental transport studies and necessary for the validation of transport models, both of which are important to fusion energy research. The use of a single tunable frequency reduces the complexity and potential failure points as compared to a multichannel system. This new system utilizes a 33–50 GHz tunable source and will be integrated into the current V-band DBS in DIII-D using a broadband Q- and V-band multiplexer. A full-scale mockup of the quasi-optical system was used to test and optimize the performance. These tests include beam profile measurements at different distances (and angles) from a paraboloidal focusing and steering mirror. The measurements cover the full frequency range 33–75 GHz of the integrated/combined Q–V band DBS system and target a large radial coverage of the low-field side of the plasma from ρ = 1.1 to ρ = 0.5, where ρ is the normalized flux surface radial coordinate.

Instruments & Instrumentation↗

DOE OSTI2020

Gasoline Engine and Fuels Offering Reduced Fuel Consumption and Emissions: Vehicle Modeling Final Report

The Gasoline Engine and Fuels Offering Reduced Fuel Consumption and Emissions (GEFORCE) project was proposed in response to the U.S. Department of Energy’s Funding Opportunity Announcement 0991 by a team made up of the members of the Coordinating Research Council (CRC) and the research staff at Oak Ridge National Laboratory (ORNL.) The project focused on investigating the potential benefits that might be attained through synergistic use of specific engine technology together with fuels formulated to represent potential directions that high-octane fuels of the future might progress. A stated objective in the DOE FOA was to demonstrate a 25% reduction in petroleum consumption through optimization of the engine technologies together with a suitable fuel. An advanced engine was constructed and used with a matrix of research fuels to investigate potential avenues for efficiency improvement. The engine incorporated technologies expected to become mainstream for boosted engines in the next 10 to 20 years. These included increased compression ratio, a two-stage turbocharger, and cooled external exhaust gas recirculation (EGR). The fuel matrix was designed to investigate impacts from research octane number (RON), volumetric ethanol content, and the final boiling point of the fuel. The engine calibration was optimized for each fuel individually and data collected to enable vehicle system modelling that projected energy consumption, fuel economy, tailpipe CO₂ emissions, and impact on petroleum consumption for an industry-average mid-size sedan. The engine calibration and data collection were carried out at IAV in Michigan and is the subject of a separate report. IAV provided the engine data to Oak Ridge National Laboratory to support the vehicle modelling portion of the project. The vehicle modelling results show the following trends: Ethanol content does have a consistently strong influence on the fuel economy results for all cycles and all fuels. Among the fuels of a nominal RON level, increasing ethanol content consistently lowers fuel economy, with the 30% ethanol fuels always providing the lowest fuel economy for a given RON level. However, in some cases the energy consumption improvement allows the 30% ethanol fuels to match the fuel economy of the ethanol-free fuel P. These observations underscore the importance of both engine efficiency and fuel volumetric energy content on vehicle fuel economy.; There was no consistent trend in the projected energy consumption results for differences in fuel T90 for all fuels and cycles. Fuel economy projections did show a consistent trend, with the higher T90 fuel providing slightly greater fuel economy when compared to the low T90 fuel of the same ethanol content. The observed trends were consistent with differences in the heating value of the fuels.; The 102-RON fuels provided reduced energy consumption and greater fuel economy for the advanced engine on all drive cycles. The engine compression ratio of 11.5 was higher than would typically be used in a turbocharged engine when 92-RON fuel use is expected. Hence, the engine experiences more efficiency degradation from knock avoidance when using the 92-RON fuels. This degradation causes the fuel economy results for the 92-RON fuels to be lower than those for the 102-RON fuels.; Fuels E and F (92-RON, 30% ethanol) are projected to achieve 10% or greater reduction in petroleum consumption, with fuels K (102-RON, 30% ethanol) and O (97 RON, 30% ethanol) achieving greater than a 20% reduction. Fuel L (102-RON, 30% ethanol) achieves greater than 25% reduction, meeting the petroleum reduction target of the project. All of the fuels that achieve 10% or greater reduction in petroleum consumption are 30% ethanol blends.; Increasing final boiling point increased fuel economy at fixed ethanol content when the 102-RON fuels were used. This trend is a result of differences in the volumetric energy content of the fuels and the projected energy consumption values for the fuels. In the case of the 102-RON fuels, increasing final boiling point also resulted in an increase in the energy content of the fuel. There was not a consistent trend between the energy content and final boiling point for the 92-RON fuels at fixed ethanol content.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

CIRCLES: Congestion Impacts Reduction via CAV-in-the-loop Lagrangian Energy Smoothing

The energy efficiency of today’s vehicular mobility relies on the un-integrated combination of i) control via static assets (traffic lights, metering, variable speed limits, etc.); and ii) onboard vehicle automation (adaptive cruise control (ACC), ecodriving, etc.). These two families of control were not co-designed and are not engineered to work in coordination. Recent studies have shown i) limitations of controls, and even ii) negative impacts of ACC. This project focused on the technology development, implementation and prototyping, and validation of Mobile Traffic Control (MTC). MTC can be viewed as an extension of classical traffic control (in which static infrastructure actuates traffic flow). In the MTC paradigm, automated vehicles actuate the entire flow via their behavior, offering enhanced possibilities to optimize the energy footprint of traffic, if designed correctly. We set out to demonstrate for the first time that considerably reduced fuel consumption of all vehicles in traffic can be achieved via distributed control of a small proportion of CAVs. Compared to baseline vehicular technologies, our work offers a significant design departure: control algorithms for the CAVs consider the impact one vehicle can have on overall traffic, improving resulting overall fuel consumption. We focus on using a few vehicles (as traffic controllers via CAV technology) to improve the energy efficiency of traffic flow to further optimize energy efficiency. A live-traffic demonstration in November 2022 featured the deployment of 100 specially-equipped CAVs, constituting an approximate local penetration rate upwards of 2%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Actinium–DOTA coordination in water from hybrid ML/MM: Structure, free energies, and water-exchange pathways

Quantitative simulation of trivalent ƒ-block chelates in water remains challenging because bonded and non-bonded force-field models make different approximations for coordination structure, exchange dynamics, and ion–ligand interactions in highly charged systems. Here, we develop a hybrid machine-learning/molecular-mechanics (ML/MM) framework for Ac 3+ –DOTA in explicit solvent by training an E(3)-equivariant neural network potential (MACELES) on mechanically embedded QM/MM data for Ac aquo and Ac–DOTA species and coupling it to NAMD 2.14 with particle-mesh Ewald electrostatics. Nanosecond ML/MM trajectories remain numerically stable and preserve chelate integrity, yielding a compact DOTA inner shell with an inner-sphere water coordination number of CN Ac,O w ≈ 1.7 arising from a dynamic equilibrium between one- and two-water states (37.5% and 59.9% of frames; three waters 2.5%). A 5 ns potential of mean force shows two low-lying basins at CN Ac,O w ≈ 1 and CN Ac,O w ≈ 2. DFT end-state free energies are consistent with the ML/MM profile, and DFT minimum-energy paths provide a qualitative electronic-structure reference for the observed basin connectivity. State-resolved kinetics reveal picosecond water-exchange pathways that couple hydration changes to transient DOTA arm fluctuations, and training-set comparisons show that temperature-matched Ac–DOTA data optimize energy/force accuracy while more diverse solvated data improve charge prediction. Overall, the present hybrid ML/MM model provides a practical description of Ac 3+ –DOTA hydration thermodynamics and short-time exchange behavior in explicit water at MD-like cost.

Actinium↗

DOE OSTI2021

Real-time Optimal Dispatch of Behind-the-Meter DERs for Secondary Frequency Regulation

Active distribution networks (ADNs) can provide grid services such as peak load shaving, loss reduction, VoltNar control, congestion management, and frequency regulation. The fast response of inverter-based distributed energy resources (DERs) and battery storage systems enables them to provide ramping support and frequency control. This paper proposes a real-time optimization approach for behind-the-meter DERs to participate in the secondary frequency regulation. The proposed approach determines optimal set-points of output power of DERs to respond to requests from system operators (SOs) in realtime to maintain the frequency of the system at the nominal value. To satisfy the real-time requirement for the secondary frequency control, the nonlinear AC power flow model is linearized considering power losses in the system to achieve both high computational speed and acceptable accuracy. The optimization problem is rerun in a closed loop manner until the mismatch between the requested power by the system operators and actual delivered power at the substation reaches an acceptable tolerance. Furthermore, the proposed approach is validated using modified versions of the IEEE 33-bus and IEEE 69-bus distribution systems. Although the contribution of a single distribution system in the frequency regulation may not be significant, stacked and coordinated contributions from several distribution systems can provide frequency regulation and other grid services at scale.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

High- and Mid-Fidelity Modeling Comparison for a Floating Marine Turbine System: Preprint

There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory (NREL) has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that can be neglected for wind turbines. These include buoyant loads, added mass and inertia loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbine systems at a speed comparable to real time. While efficient for long simulations, large sets of load cases, and design studies, mid-fidelity codes cannot capture all of the potentially important physical phenomenon impacting marine turbine systems. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system designed by NREL was modeled both with OpenFAST and with the commercial CFD code, STARCCM+. The CFD model used a 3-D unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modelled with a custom coupling of the CFD solver with the open-source code, MoorDyn. This improves upon the existing quasi-static catenary solver in STARCCM+, which lacks seabed contact or line-to-line connections. Spatial and temporal convergence studies were conducted. The simulation results for a combined current and wave condition are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.

CFD↗

DOE OSTI2023

Effect of the Precursor Chemistry on the Crystallization of Triple Cation Mixed Halide Perovskites

Triple cation, mixed halide perovskite compositions have been reported to be more thermally stable, exhibit fewer phase impurities, and show higher power conversion efficiency and better reproducibility than single cation perovskites. In this work, we explain the formation of Cs0.05FA0.81MA0.14Pb(I0.85Br0.15)3 via a multimodal in situ study combining structural information from synchrotron grazing-incidence wide-angle X-ray scattering (GIWAXS) and optical properties from photoluminescence (PL) spectroscopy with density functional theory calculations (DFT). The focus here is on the effects of the solvent and antisolvent during crystallization. The predominantly used solvents N,N-dimethylformamide (DMF), dimethyl sulfoxide (DMSO), and the antisolvent chlorobenzene (CB) as well as the solvent-antisolvent-precursor interactions are investigated. Given the high elemental complexity and mutual interdependencies between solvent, antisolvent, and perovskite precursors, we found significant differences in the crystallization pathways. DMF-pure precursors show the formation of the DMF-containing intermediate phase and the nucleation of compositionally distinct perovskite phases, while when DMSO is added, only crystalline α- and δ-phases were found. In addition, the presence of DMSO helps the formation of α-perovskite. Coordination energy and bond order (BO) calculations support our experimental findings. Dripping of CB induces nucleation at room temperature, slows the α-phase formation rate, and appears to reduce the nucleation radius. These findings provide novel insights into solvent, antisolvent, and perovskite precursor interactions and their formation pathways. The complexity of interactions between solvents and reagents highlights the importance of understanding these effects to further improve the reproducibility and optimize processing conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Monitoring the Stability of Porous Coordination Cages during the Photoreduction of Porous Salt Thin Films

This study investigates the photochemical properties and stability of zirconium-based porous salts composed of coordination cages and redox-active polyoxometalates (POMs). While bulk porous salts demonstrated photoreduction confined to surface regions due to lim-ited light penetration and scattering effects, thin films of cage-POM assemblies were fabricated to address these challenges. These optically transparent films allowed access to the catalyst core, enabling enhanced photochemical characterization. Comparative studies revealed that the thin films exhibited superior photochemical activity and maintained porosity under optimized conditions, whereas bulk powders suffered from surface-limited photoreduction and cage decomposition. Furthermore, this work highlights the utility of thin films as a platform for studying and advancing the photochemical applications of porous salts.

Hoq, Jahidul [Indiana University, Bloomington, IN ↗

DOE OSTI2020

Pt-Ligand single-atom catalysts: tuning activity by oxide support defect density

The support–metal interaction is an important element of heterogeneous catalyst design and is particularly critical for the rapidly growing field of single-atom catalysts (SACs). In this work, we investigate the impact of varying the defect density of the titania support on metal–organic Pt SACs for hydrosilylation reactions. Pt SACs are decorated on the powder titania support, employing a metal–ligand interaction with a dipyridyl-tetrazine ligand (DPTZ). The single-atom nature of Pt is verified by X-ray absorption spectroscopy (XAS) on both pristine and defective titania surfaces. These Pt species have a +2 oxidation state and are stabilized by bonding with DPTZ, surface oxygen, and residual chloride from the metal precursor. The catalytic activity is evaluated for the alkene hydrosilylation reaction and it is discovered that the activity of Pt-ligand is positively correlated with the defect density of the titania support. The turn-over number (TON) is calculated to be 12 530 for Pt SACs on a defective surface, which is significantly higher than Pt SACs on a pristine titania surface (830) for the same reaction period (10 min) under the same conditions (70 °C). We ascribe the high activity of Pt SACs on defective titania surfaces to two aspects: the coordination of Pt with more chloride than on pristine titania surfaces, which shortens the induction period of the reaction, and the preferential dispersion of Pt–DPTZ units on defective regions of titania surfaces, allowing facile contact between Pt sites and reactants. The supported Pt–DPTZ SACs show high stability through multiple cycles of batch reactions. This work demonstrates an efficient approach to improve the activity and stability of SACs by optimizing the metal–support interaction, which can also be applied to other oxide surfaces to further develop next-generation heterogeneous single-atom catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Coordinated Control Strategy of a Battery Energy Storage System to Support a Wind Power Plant Providing Multi-Timescale Frequency Ancillary Services

With increasing penetrations of wind generation on electric grids, wind power plants (WPPs) are encouraged to provide frequency ancillary services (FAS); however, it is a challenge to ensure that variable wind generation can reliably provide these ancillary services. This paper proposes using a battery energy storage system (BESS) to ensure the WPPs' commitment to FAS. This method also focuses on reducing the BESS's size and extending its lifetime. In this paper, a state-machine-based coordinated control strategy is developed to utilize a BESS to support the obliged FAS of a WPP (including both primary and secondary frequency control). This method takes into account the operational constraints of the WPP (e.g., real-time reserve) and the BESS (e.g., state of charge [SOC], charge and discharge rate) to provide reliable FAS. Meanwhile, an adaptive SOC-feedback control is designed to maintain SOC at the optimal value as much as possible and thus reduce the size and extend the lifetime of the BESS. In conclusion, the effectiveness of the control strategy is validated with an innovative, multi-area, interconnected power system simulation platform that can mimic realistic power systems operation and control by simulating real-time economic dispatch, regulating reserve scheduling, multi-area automatic generation control, and generators' dynamic response.

25 ENERGY STORAGE↗

DOE OSTI2020

Agent-Based Coordination Scheme for PV Integration (ABC4PV)

Renewables and especially photovoltaics (PV) have benefitted significantly from a host of incentives and policies targeted toward enhanced integration and adoption of specific energy technologies. However, with the push to move forward into a subsidy-free market framework, behind-the-meter residential PV applications have generally struggled to retain their value (unlike utility scale and commercial projects) [1]. This project focused on developing control-theoretic solutions aimed at improving the integration and interaction of behind-the-meter residential PV with other distribution system assets (controllable and non-controllable) to enhance the integrated value of residential PV. To this end, a suite of decentralized control methodologies have been developed to enable effective coordination and control of behind-the-meter residential load customers’ PV, battery storage systems (BSS), controllable loads and other similar assets within a distribution feeder. This interaction aims at procuring energy savings and, thus, energy bill savings. The main source of savings is drawn from reducing the effect of demand charge pricing and is realized at the feeder level, assuming community level interaction and management among the aforementioned assets. Optimal control of the assets is implemented with a distributed optimization methodology, leveraging consensus-based algorithms. The results gathered from the optimal control simulations demonstrates that the savings can be duly achieved and the algorithm decision times (to dynamically control asset set points, for example) are fast. As for the overall efficiency of PV+BSS systems, to procure energy savings from curtailment of the demand charge pricing effects, the optimal control is set up so as to minimize the variance of the load for all customers, throughout a feeder and throughout time in a rolling horizon scheduling with model predictive control. The control takes into account inter-temporal electrochemical storage (battery) degradation costs: specifically, we have developed a long-term lifetime model for the BSS that weighs in the effect of the degradation factor in the dispatch formulations, thus, a considerable operating cost that affects energy decision making. The levelized cost of energy (LCOE – redefined for the purpose of quantifying asset integration effectiveness through the customers’ energy cost) is shown to be below the threshold set for the combined PV+BSS topology of $ 0.14/kWh for multiple cases of PV penetration all the way up to 50%, provided that a policy of shared ownership of and savings is in place. Further, the LCOE calculated for the case before the deployment PV+BSS systems is also achievable, i.e. the deployment of PV+BSS, if planned and scheduled optimally. will have no effect on customers’ energy costs. From the control methodology viewpoint, the developed consensus-based algorithms are shown to converge for a wide range of problem cases (spanning normal operating scenarios and contingencies), guaranteeing dispatch solutions under forecasting errors, communication break-downs and cyber-security attacks. The proposed control solutions are scalable and real-time implementable, with dispatch computations and device set-point updates converging in less than 2s in most practical instances of the above events.

14 SOLAR ENERGY↗

DOE OSTI2019

Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids

We propose a novel algorithm to solve optimal power flow (OPF) that aims at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to large distribution networks by utilizing an information structure based on networked autonomous grids (AGs). Specifically, each AG is a subtree of a large distribution network that has a tree topology. The topology and line parameters of each AG are known only to a regional coordinator (RC) that is responsible for communicating with and dispatching the DERs within this AG. The reduced network, where each AG is treated as a node, is managed by a central coordinator (CC), which knows the topology and line parameters of the reduced network only and communicates with all the RCs. We jointly explore this information structure and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primal-dual gradient algorithm that solves the OPF. The proposed implementation significantly reduces the computation burden compared to the centrally coordinated implementation of the primal-dual algorithm. Numerical results on a 4,521-node test feeder show that the proposed hierarchical distributed algorithm can achieve an improvement of more than tenfold in the speed of convergence compared to the centrally coordinated primal-dual algorithm.

Zhou, Xinyang↗

DOE OSTI2019

Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids: Preprint

We propose a novel algorithm to solve optimal power flow (OPF) that aims at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to large distribution networks by utilizing an information structure based on networked autonomous grids (AGs). Specifically, each AG is a subtree of a large distribution network that has a tree topology. The topology and line parameters of each AG are known only to a regional coordinator (RC) that is responsible for communicating with and dispatching the DERs within this AG. The reduced network, where each AG is treated as a node, is managed by a central coordinator (CC), which knows the topology and line parameters of the reduced network only and communicates with all the RCs. We jointly explore this information structure and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primal-dual gradient algorithm that solves OPF. The proposed implementation significantly reduces the computation burden compared to the centrally coordinated implementation of the primal-dual algorithm. Numerical results on a 4,521-node test feeder show that the proposed hierarchical distributed algorithm can achieve more than 10-fold improvement in the speed of convergence compared to the centrally coordinated primal-dual algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids

24 POWER TRANSMISSION AND DISTRIBUTION↗