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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Sensing Electrical Networks Securely & Economically (SENSE)

The growing adoption of distributed energy resources (DERs) like battery energy storage systems and roof top solar/PV and the rapid penetration of electric vehicles (EVs), the electric grid is undergoing a major transformation with elevated stress on legacy grid assets. Despite a lot of expenditure to address these challenges, both in dollars and manpower, utilities have not been able to receive the value that was promised. The gains have been most visible at the transmission and substation level, especially where the main objective was improving operational and economic efficiency for the utility. Improving visibility and control at a few select points enhances the existing and established paradigm of centralized command and control. With changing load patterns, load types and the overall transition to an “active grid”, the centralized control and coordination paradigm gets challenged. To address the challenges, a new architecture and mechanism is needed, one that supports decentralized control and decision making, extracting value streams at the grid edge, particularly as the changes are fueled by transitions occurring in the distribution system. To address this, a communications and data processing platform, “GAMMA” was developed and demonstrated through the project. At the heart of the platform, are distributed, intelligent edge nodes with sensing and compute capabilities, that can record and analyze information locally. They are embedded in sensors and actuators specific to different distribution system applications. Phase 1 of the project focused on developing novel sensor technology that can be used for monitoring utility pole top distribution transformers. The sensors were designed with the objective of being low-cost, communicating with the GAMMA cloud using novel “delay-tolerant” networking using Bluetooth and a secure mobile application. They were non-intrusive in nature so that they can be installed quickly in the field, resulting in overall low cost of deployment and operations. Following the successful completion of Phase 1, the team manufactured 100 units for a field demonstration in Phase 2. The field demonstration was carried out on two real feeder systems with the local utility partner. In total, 100 sensors were installed and operated over a period of 6 months in the state of Georgia. The platform is operational end to end, with the cloud infrastructure deployed on a distributed, serverless environment that can serve multiple data streams, an analytics engine and a portal to securely view the data from multiple assets. The data collected through the GAMMA Mobile Phone app showcased the viability of the novel delay tolerant networking architecture, and the data processing algorithms developed through the course of the project, were successful in extracting important information about the overall network, improving the utility’s visibility and situational awareness in the distribution feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Safe and Private Forward-trading Platform for Transactive Microgrids

Power grids are evolving at an unprecedented pace due to the rapid growth of distributed energy resources (DER) in communities. These resources are very different from traditional power sources, as they are located closer to loads and thus can significantly reduce transmission losses and carbon emissions. However, their intermittent and variable nature often results in spikes in the overall demand on distribution system operators (DSO). To manage these challenges, there has been a surge of interest in building decentralized control schemes, where a pool of DERs combined with energy storage devices can exchange energy locally to smooth fluctuations in net demand. Building a decentralized market for transactive microgrids is challenging, because even though a decentralized system provides resilience, it also must satisfy requirements such as privacy, efficiency, safety, and security, which are often in conflict with each other. As such, existing implementations of decentralized markets often focus on resilience and safety but compromise on privacy. In this article, we describe our platform, called TRANSAX, which enables participants to trade in an energy futures market, which improves efficiency by finding feasible matches for energy trades, enabling DSOs to plan their energy needs better. TRANSAX provides privacy to participants by anonymizing their trading activity using a distributed mixing service, while also enforcing constraints that limit trading activity based on safety requirements, such as keeping planned energy flow below line capacity. We show that TRANSAX can satisfy the seemingly conflicting requirements of efficiency, safety, and privacy. We also provide an analysis of how much trading efficiency is lost. Trading efficiency is improved through the problem formulation, which accounts for temporal flexibility, and system efficiency is improved using a hybrid-solver architecture. Lastly, we describe a testbed to run experiments and demonstrate its performance using simulation results.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Dynamic Simulation Modeling and Control of a Desiccant Assisted Direct-expansion Air Handling Unit

Desirable built environments demand simultaneous regulation of thermal comfort and indoor air quality (IAQ) with energy-efficient operation of heating, ventilation and air conditioning (HV AC) systems, which involves controls of temperature, humidity and airborne contaminants simultaneously. This paper presents the efforts of dynamic modeling and initial development control strategy for a desiccant-assisted multi-functional air handling unit (AHU) coupled with a direct-expansion rooftop unit (RTU) system, which aims to achieve multiple functions for indoor environment conditioning with energy efficient control. The RTU-AHU system includes a desiccant wheel for dehumidification and a conceptual direct air capture (DAC) filtering device for CO2 regulation. A Modelica-based dynamic model is developed for this conceptual system, and a simple decentralized control strategy is designed, which combines a differential-enthalpy based AHU return-air ratio control, a demand-controlled ventilation, and supply-air temperature humidity control via the RTU and DW controls. The proposed control method is evaluated with the Modelica simulation model for a selected set of scenarios

Pan, Chao↗
DOE OSTI2024

Transient Optimization of the Cryogenic Moderator System Controller at the Spallation Neutron Source for Improved Performance

The high-energy neutron beam generated at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory is moderated to use cold (slow) neutrons for scientific discoveries. The Cryogenic Moderator System (CMS) removes heat from the neutron beam using cryogenic hydrogen (H 2 ) moderators connected via heat exchangers to a helium (He) refrigeration loop that dissipates heat using a compressor-brake system. However, the CMS is affected by sporadic losses in beam power, referred to as "beam trips," as these events generate significant disturbances in cooling requirements. To accommodate the heat load transients during beam trips, the CMS uses a decentralized control strategy consisting of four flow valves and one electric heater adjusted by independent proportional-integral (PI) controllers. During the CMS’s initial commissioning, the PI gains were calibrated based only on tracking performance, overlooking their effectiveness in disturbance rejection. A data-driven, control-oriented closed-loop model was developed to recalibrate the PI gains and minimize the transient disturbances caused by beam trips. The model consists of three main components: (1) a physics-based model of the He refrigeration loop, (2) a machine-learning model of the cryogenic H 2 cooling trains, and (3) the control logic used for feedback set-point tracking. Experimental results showed that the recalibrated gains obtained in this study improved the CMS’s transient response during beam trips.

Maldonado Puente, Bryan↗
DOE OSTI2025

Design, Control, and Protection of a 13.2 kV, 1 MVA Solid State Transformer for Electric Vehicle Extreme Fast Charging Station

In this article, a medium-voltage (MV) ac-dc solid state transformer (SST) for electric vehicle (EV) extreme fast charging (XFC) station is proposed. The SST adopts a cascaded H-bridge (CHB)-based structure where the active front end (AFE) power stages are connected in input-series followed by dual active bridge (DAB) converters connected in an output-parallel configuration providing galvanic isolation through a high-frequency transformer (HFT). The SST is rated for 1 MVA and connects directly to a three-phase 13.2 kV MV ac grid through ac switchgear and outputs 750-V dc. At the dc bus, several dc/dc converters are connected, each of which can charge an EV based on its battery capacity. A novel decentralized control architecture of the SST is adopted in this work which simplifies the MV dc link voltage and module-level power balancing. In addition, the local and central protection designs of the SST are presented which identify and respond to the internal fault of the system. Finally, the experimental validations of the SST hardware prototype are presented up to the rated voltage. Furthermore, this article details the design and implementation of the MV SST addressing the challenges of an isolated MV class power converter for connecting directly to the MV ac grid with unique controller architecture, distributed protection framework, and SST constructional features.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Infrastructure first principles for the Anthropocene

Abstract There appears to be a growing decoupling between the conditions that infrastructures were designed for and today’s rapidly changing environments. Infrastructures today are largely predicated on the technologies, goals, and governance structures from a century ago. While infrastructures continue to deliver untold value, there is growing evidence that these critical, basic, and lifeline systems appear ill-equipped to confront the volatility, uncertainty, accelerating conditions, and complexity that define them and their changing environments. Innovative and disruptive first principles are needed to guide infrastructures in the Anthropocene. Drawing from emerging infrastructure research and disciplines that appear better able to confront disruption and change, a novel set of first principles are identified: (1) Plan for complex conditions and surprise; (2) Recouple with agility and flexibility; (3) Govern for exploration and instability; (4) Build consensus as control decentralizes; (5) Restructure to engage with porous boundaries; and, (6) Cyberthreat planning is now mission critical. These principles should guide infrastructure planning recognizing the changing nature and increasingly obsolete boundaries that have defined engineered systems in the modern era.

Chester, Mikhail (ORCID:0000000293542102)↗
DOE OSTI2023

Medium Voltage Solid State Transformer for Extreme Fast Charging Applications

A modular and scalable solid state transformer (SST) with direct medium voltage (MV) AC connectivity is proposed to enable DC extreme fast charging (XFC) of electric vehicles. Single-phase-modules (SPMs), each consisting of an active-front-end (AFE) stage and an isolated DC-DC stage, are connected in input-series-output-parallel (ISOP) configuration. The modular hardware is co-designed with decentralized control of the DC-DC stages where voltage and power balancing are achieved by each SPM using only its local sensor feedback; a centralized controller (CC) regulates the low voltage (LV) DC bus through the AFE stages without any sensor feedback form the SPMs. The controller architecture contrasts sharply with the prior art for MV AC to LV DC SSTs where high-speed bidirectional communication among SPMs and a CC are required for module-level voltage and power balancing, which severely limits the scalability and practical realization of higher voltage and higher power units. Detailed small-signal analysis and controller design guidelines are developed. Furthermore, a soft start-up strategy is presented. The proposed converter and control structure are validated through simulation and experimental results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Coordinated Self-Assembly of Networked Microgrids Using Irving’s Algorithm

Abstract— Microgrid installations have regained significant interest, driven by the increasing adoption of distributed energy resources, decentralized controls, and ongoing technological advancements. While the number of microgrids increases, there are opportunities to coordinate networks of microgrids. In this study, Irving’s algorithm is applied to a framework for the coordinated self-assembly of networked microgrids. Compared with the authors’ previous work, this new study relaxes the constraint on participated microgrids to have a single global objective. Thus, each microgrid can rank others according to its local preference. This reduces the amount of shared information, improves the privacy, and enhances the flexibility. The adaptability to that proposed framework is also maintained. Examples are presented to illustrate the networking processes and self-assembly operations.

Xie, Jing↗
DOE OSTI2024

Modular Wide-bandgap String Inverters for Low-cost Medium-voltage Transformerless PV Systems

The proposed technology combines advances in wide-bandgap power electronics with breakthroughs in distributed and decentralized control to produce ultra-low-cost medium-voltage transformerless PV inverters that are composed of stackable lightweight blocks. Taken together, the proposed circuit designs and accompanying control strategies will yield integrated control+circuit (C2) blocks, each comprising a converter and local controller, that can be assembled in a modular fashion to obtain distributed conversion interfaces for next-generation commercial and utility-scale PV systems. We will utilize SiC devices to obtain C2 blocks that can individually operate at a voltage and power in excess of 1 kV and 100 kW, respectively, such that ensembles of series-connected blocks perform direct dc to three-phase ac conversion at medium voltages (e.g., 12 kV–35 kV) and at multi-MW power levels.

42 ENGINEERING↗
DOE OSTI2024

Distributionally Robust Decentralized Volt-Var Control With Network Reconfiguration

Here, this paper presents a decentralized volt-var optimization (VVO) and network reconfiguration strategy to address the challenges arising from the growing integration of distributed energy resources, particularly photovoltaic (PV) generation units, in active distribution networks. To reconcile control measures with different time resolutions and empower local control centers to handle intermittency locally, the proposed approach leverages a two-stage distributionally robust optimization; decisions on slow-responding control measures and set points that link neighboring subnetworks are made in advance while considering all plausible distributions of uncertain PV outputs. We present a decomposition algorithm with an acceleration scheme for solving the proposed model. Numerical experiments on the IEEE 123 bus distribution system are given to demonstrate its outstanding out-of-sample performance and computational efficiency, which suggests that the proposed method can effectively localize uncertainty via risk-informed proactive timely decisions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Decentralized Filtering Adaptive Neural Network Control for Uncertain Switched Interconnected Nonlinear Systems

This article presents a novel decentralized filtering adaptive neural network control framework for uncertain switched interconnected nonlinear systems. Each subsystem has its own decentralized controller based on the established decentralized state predictor. For each subsystem, the nonlinear uncertainties are approximated by a Gaussian radial basis function (GRBF) neural network incorporated with a piecewise constant adaptive law, where the adaptive law will update adaptive parameters from the error dynamics between the host system and the decentralized state predictor by discarding the unknowns, whereas a decentralized filtering control law is derived to cancel both local and mismatched uncertainties from other subsystems, as well as achieve the local objective tracking of the host system. The achievement of global objective depends on the achievement of local objective for each subsystem. The matched uncertainties are canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. By exploiting the average dwell time principle, the error bounds between the real system and the virtual reference system, which defines the best performance that can be achieved by the closed-loop system, are derived. A numerical example is given to illustrate the effectiveness of the decentralized filtering adaptive neural network control architecture by comparing against the model reference adaptive control (MRAC).

Average dwell time, decentralized, filtering adapt↗
DOE OSTI2022

Decentralized modular hybrid supervisory control for the formation of unmanned helicopters

Abstract Formation control of Unmanned Aerial Vehicles (UAVs) requires them to tightly cooperate to reach and keep the formation, while avoiding collision. This paper proposes a novel decentralized hybrid supervisory control approach for the formation control of multiple UAVs. This is achieved by developing a symbolic motion planning technique to polarly partition the motion space resulting in a finite state discrete event model for the motion dynamics of each UAV. Then, a modular discrete supervisor is designed for different components of the formation mission including reaching the formation, keeping the formation, and collision avoidance. Further, for the collision avoidance mechanism, a novel top‐down decomposition‐based approach is developed to design local supervisors decentralizedly. It is formally proved that with the proposed top‐down decomposition‐based approach, the (locally) supervised UAVs, as a whole, can cooperatively satisfy the desired (global) collision avoidance specification. The proposed decentralized supervisory control algorithm is also verified through a hardware‐in‐the‐loop simulator for the formation control of unmanned helicopters.

Karimoddini, Ali↗
DOE OSTI2021

Attention Enabled Multi-Agent DRL for Decentralized Volt-VAR Control of Active Distribution System Using PV Inverters and SVCs

This paper proposes attention enabled multi-agent deep reinforcement learning (MADRL) framework for active distribution network decentralized Volt-VAR control. Using the unsupervised clustering, the whole distribution system can be decomposed into several sub-networks according to the voltage and reactive power sensitivity relationships. Then, the distributed control problem of each sub-network is modeled as Markov games and solved by the improved MADRL algorithm, where each sub-network is modeled as an adaptive agent. An attention mechanism is developed to help each agent focus on specific information that is mostly related to the reward. All agents are centrally trained offline to learn the optimal coordinated Volt-VAR control strategy and executed in a decentralized manner to make online decisions with only local information. Compared with other distributed control approaches, the proposed method can effectively deal with uncertainties, achieve fast decision makings, and significantly reduce the communication requirements. Comparison results with model-based and other data-driven methods on IEEE 33-bus and 123-bus systems demonstrate the benefits of the proposed approach.

distribution network↗
DOE OSTI2021

Preventing Voltage Divergence in Series-Stacked Bidirectional Battery Energy Storage DC-DC Converter under Asymmetrical Operating Conditions

DC stacked topologies have gained popularity for interfacing individual photovoltaic panels to a high-voltage DC bus. A similar approach can be used to interface individual battery packs to the same DC bus, which allows active balancing of battery substrings and the use of lower voltage switches. Any imbalance in battery current, however, can cause the converter output voltages to diverge. This paper describes the source of voltage divergence and demonstrates a solution that allows seamless stacking of multiple battery packs to be interfaced to a high voltage DC bus. To prevent the voltage divergence phenomenon and allow asymmetrical battery charging for efficient battery state of charge management, the PI-based decentralized voltage control enabling both capacitor voltage sharing and asymmetrical capacitor voltage control is proposed. The effectiveness of the decentralized voltage control strategy is demonstrated through controller hardware-in-the-loop test results.

Kim, Namwon↗
DOE OSTI2020

Multi-Agent Control of Lane-Switching Automated Vehicles for Energy Efficiency

The proliferation of automatic control systems and their connectivity accents the performance of their interactions. In particular, connected and automated vehicles could become high-impact examples thanks to their energy use and productivity effects. Ideally, a controller might collectively optimize all agents' control moves for a given objective. However, limits on computational complexity, incomplete knowledge of the central planner, and risks of a single point of failure make distributed control attractive as well. This paper proposes a collaborative heuristic to approach the performance of centralized control with decentralized-like computational effort. The related centralized controller is also described in detail and evaluated as a baseline. A collaboration-intensive obstacle avoidance scenario involving electric vehicles is simulated to demonstrate benefits over fully decentralized control. While centralized optimization performed best with an 8.6 % energy reduction, the collaborative decentralized scheme reached a favorable computation-performance tradeoff with a 6.7 % energy reduction.

Dollar, R. Austin↗
DOE OSTI2022

Control and Grid Support Function Evaluation for a Three-Phase Back-to-Back Modular Multilevel Converter System

This paper focuses on the evaluation of advanced inverter controls for a 500kW back-to-back (B2B), silicon carbide, multilevel modular converter (MMC) used as a direct-connected medium-voltage grid intertie. A decentralized hierarchical controller architecture for the MMC system is presented, which uses the main controller to implement higher level grid interconnection functions per the IEEE 1547–2018 standards and the local controllers to execute lower level closed-loop functionality of the MMC stages. This paper presents and elaborates on the grid functionalities are elaborated and presented. The back-to-back converter system is equipped with local controllers and their corresponding functionalities are presented. Case study results for the corresponding functionalities presented show the effectiveness of the proposed architecture. To enhance the operation capabilities of the system, a parameter update scheme has been implemented and utilized in unison with the controller.

decentralized control↗