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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Impact of Behind-the-Meter Heterogeneous Distributed Energy Resources on Distribution Grids

The increasing integration of distributed energy resources (DERs) on the electric grid brings new challenges and opportunities for utility grid operations. With the rapid deployment of DERs, there is emerging interest in integrating these controllable devices with utility operations at all levels for monitoring and management. To understand the challenges with increasing behind-the-meter (BTM) DERs and to identify the needs in deploying advanced controls, a comprehensive grid impact study is indispensable. This paper presents the analysis which help visualize the DER impact on the grid, identify the challenges and provides an insight into the new distribution management and control needs to enable reliable and resilient grid operations.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2021

Voltage Control Strategy for Energy Storage System in Sustainable Distribution System Operation

Due to the increasing penetration of distributed energy resources (DERs) required for the sustainable distribution system, new voltage control strategy is needed by utilities. Traditional voltage control strategy can not support the increasing number of DERs in a coordinated and scalable manner to meet the operational voltage regulation requirement. Supported by the power electronics converter, the energy storage system can provide fast, smooth, and flexible voltage control services. In this paper, an effective and easy to implement sensitivity-based voltage control strategy is developed for the energy storage system. The developed control strategy is validated using an industrial feeder data in Northwest Washington. The proposed strategy can mitigate the voltage unbalance issue, improve the voltage profile, and correct power factors while supporting sustainable distribution system operation.

Zhang, Yue (ORCID:0000000241469716)↗
DOE OSTI2020

Hierarchical, Grid-Aware, and Economically Optimal Coordination of Distributed Energy Resources in Realistic Distribution Systems

Renewable portfolio standards are targeting high levels of variable solar photovoltaics (PV) in electric distribution systems, which makes reliability more challenging to maintain for distribution system operators (DSOs). Distributed energy resources (DERs), including smart, connected appliances and PV inverters, represent responsive grid resources that can provide flexibility to support the DSO in actively managing their networks to facilitate reliability under extreme levels of solar PV. This flexibility can also be used to optimize system operations with respect to economic signals from wholesale energy and ancillary service markets. Here, we present a novel hierarchical scheme that actively controls behind-the-meter DERs to reliably manage each unbalanced distribution feeder and exploits the available flexibility to ensure reliable operation and economically optimizes the entire distribution network. Each layer of the scheme employs advanced optimization methods at different timescales to ensure that the system operates within both grid and device limits. The hierarchy is validated in a large-scale realistic simulation based on data from the industry. Simulation results show that coordination of flexibility improves both system reliability and economics, and enables greater penetration of solar PV. Discussion is also provided on the practical viability of the required communications and controls to implement the presented scheme within a large DSO.

distribution network↗
DOE OSTI2023

Learning Provably Stable Local Volt/Var Controllers for Efficient Network Operation

Here this paper develops a data-driven framework to synthesize local Volt/Var control strategies for distributed energy resources (DERs) in power distribution grids (DGs). Aiming to improve DG operational efficiency, as quantified by a generic optimal reactive power flow (ORPF) problem, we propose a two-stage approach. The first stage involves learning the manifold of optimal operating points determined by an ORPF instance. To synthesize local Volt/Var controllers, the learning task is partitioned into learning local surrogates (one per DER) of the optimal manifold with voltage input and reactive power output. Since these surrogates characterize efficient DG operating points, in the second stage, we develop local control schemes that steer the DG to these operating points. We identify the conditions on the surrogates and control parameters to ensure that the locally acting controllers collectively converge, in a global asymptotic sense, to a DG operating point agreeing with the local surrogates. We use neural networks to model the surrogates and enforce the identified conditions in the training phase. AC power flow simulations on the IEEE 37-bus network empirically bolster the theoretical stability guarantees obtained under linearized power flow assumptions. The tests further highlight the optimality improvement compared to prevalent benchmark methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Optimal Coordination of Distributed Energy Resources Using Deep Deterministic Policy Gradient

Recent studies showed that reinforcement learning (RL) is a promising approach for coordination and control of distributed energy resources (DER) under uncertainties. Many existing RL approaches, including Q-learning and approximate dynamic programming, are based on lookup table methods, which become inefficient when the problem size is large and infeasible when continuous states and actions are involved. In addition, when modeling battery energy storage system (BESS), the loss of life is not reasonably considered into the decision-making process. This paper proposes an innovative deep RL method for DER coordination considering BESS degradation. The proposed deep RL is designed based on an adaptive actor-critic architecture and employs an off-policy deterministic policy gradient method for determining the dispatch operation that minimizes the operation cost and BESS life loss. Case studies were performed to validate the proposed method and demonstrate the effects of incorporating degradation models into control design.

Das, Avijit↗
DOE OSTI2020

Catalytically mediated epitaxy of 3D semiconductors on van der Waals substrates

The formation of well-controlled interfaces between materials of different structure and bonding is a key requirement when developing new devices and functionalities. Of particular importance are epitaxial or low defect density interfaces between two-dimensional materials and three-dimensional semiconductors or metals, where an interfacial structure influences electrical conductivity in field effect and optoelectronic devices, charge transfer for spintronics and catalysis, and proximity-induced superconductivity. Epitaxy and hence well-defined interfacial structure has been demonstrated for several metals on van der Waals-bonded substrates. Semiconductor epitaxy on such substrates has been harder to control, for example during chemical vapor deposition of Si and Ge on graphene. Here, we demonstrate a catalytically mediated het-eroepitaxy approach to achieve epitaxial growth of three-dimensional semiconductors such as Ge and Si on van der Waals-bonded materials such as graphene and hexagonal boron nitride. Epitaxy is "transferred" from the substrate to semiconductor nanocrystals via solid metal nano-crystals that readily align on the substrate and catalyze the formation of aligned nuclei of the semiconductor. In situ transmission electron microscopy allows us to elucidate the reaction pathway for this process and to show that solid metal nanocrystals can catalyze semiconductor growth at a significantly lower temperature than direct chemical vapor deposition or deposition mediated by liquid catalyst droplets. We discuss Ge and Si growth as a model system to explore the details of such hetero-interfacing and its applicability to a broader range of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Data-driven based coordinated smart inverter control for distributed energy resources

Smart inverters (SI) for distributed energy resources (DER) are becoming popular since they have the ability to stabilize as well as restore the voltage and frequency of power systems. Aiming at establishing the mathematical models combined with SI control methods, multiple optimization methods are developed. However, the computational complexity of solving such a mathematical model with various uncertainties limits the real-time application of the SI control. To conquer this challenge, a data-driven-based SI control approach is developed to achieve coordinated control in the high penetration DER system. First, an optimization problem for maximizing the active power generation and minimizing the power loss is designed using the Volt/VAR control. To reduce the time consumption, the recurrent neural network (RNN) is proposed to model the relationship between the uncertainties and control actions during the offline site. The RNN with different sub-structures such as the long short-term memory cell and gated recurrent unit cell are included to enrich the diversity of features. In the last stage, different experiment comparisons, including multiple uncertainties maps and stateof- art machine learning methods, are conducted to verify the effectiveness of the proposed method based on the IEEE 123 bus power system. The results demonstrate that the proposed method can effectively achieve a rapid and coordinated control with a lower error rate.

Qiu, Wei↗
DOE OSTI2023

Controllable Skyrmionic Phase Transition between Néel Skyrmions and Bloch Skyrmionic Bubbles in van der Waals Ferromagnet Fe 3-δ GeTe 2

The van der Waals (vdW) ferromagnet Fe 3-δ GeTe 2 has garnered significant research interest as a platform for skyrmionic spin configurations, that is, skyrmions and skyrmionic bubbles. However, despite extensive efforts, the origin of the Dzyaloshinskii–Moriya interaction (DMI) in Fe 3-δ GeTe 2 remains elusive, making it challenging to acquire these skyrmionic phases in a controlled manner. In this study, it is demonstrated that the Fe content in Fe 3-δ GeTe 2 has a profound effect on the crystal structure, DMI, and skyrmionic phase. For the first time, a marked increase in Fe atom displacement with decreasing Fe content is observed, transforming the original centrosymmetric crystal structure into a non-centrosymmetric symmetry, leading to a considerable DMI. Additionally, by varying the Fe content and sample thickness, a controllable transition between Néel-type skyrmions and Bloch-type skyrmionic bubbles is achieved, governed by a delicate interplay between dipole–dipole interaction and the DMI. The findings offer novel insights into the variable skyrmionic phases in Fe 3-δ GeTe 2 and provide the impetus for developing vdW ferromagnet-based spintronic devices.

2D ferromagnet Fe3-δGeTe2↗
DOE OSTI2020

Control of magnetic properties of MnBi 2 Te 4 using a van der Waals ferroelectric III 2 -VI 3 film and biaxial strain

Using the first-principles calculations, we systematically investigated magnetic properties of a MnBi 2 Te 4 (MBT) monolayer in contact with III 2 -VI 3 two-dimensional ferroelectric substrates. As the electric polarization in the ferroelectric films is switched, a semiconductor to half-metal transition occurs in MBT, and its magnetic easy axis in several cases reorients. As an example, the Curie temperature of MBT/In 2 Se 3 can be enhanced to 21.5 or 32 K under the influence of electric polarization and biaxial strain, much higher than that of the pristine MBT monolayer, which is 14.5 K in our calculations. Our results in this work suggest effective ways to tune magnetic properties of MBT and provide useful insights for the further development of these important van der Waals functional materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Hierarchical Control of Megawatt-Scale Charging Stations for Electric Trucks with Distributed Energy Resources

Electrifying medium- and heavy-duty trucks is critical to decarbonizing the transportation sector. Energy needs of electric trucks will likely require megawatt-scale charging stations, which could significantly stress the electric distribution grid. Distributed energy resources (DER) can alleviate this stress and reduce charging costs with proper management. To that end, this work develops a hierarchical predictive control algorithm for future multi-port megawatt-scale charging stations that can provide real-time energy management for stations, decide charging rates, dispatch energy storage system (ESS), and provide grid voltage support. We integrate three algorithmic components: (i) an energy management optimization (EMO) that provides supervisory control to DER assets and charging loads at minute scale, (ii) a real-time energy management system (RT-EMS) that heuristically compensates for fast disturbances at sub-second scale, and (iii) a model predictive control (MPC)-based battery management system (BMS) that communicates future charging demands to the EMO, to manage the overall megawatt-scale site. Additionally, validation in a controller hardware-in-the-loop (CHIL) environment shows that the hierarchical controller can reduce the total energy consumption from the grid by approximately 28% compared to an uncontrolled case for the station configuration in this paper, without impacting charging time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Resilient Cyber Infrastructure for the Minimum Wind Curtailment Remedial Control Scheme

Integration of Distributed Energy Resources (DER) has been significantly increasing in the electric power grid. One of the predominant renewable energy sources, wind energy, possess a significant challenge for grid operations, due to its intermittency, uncertainty and variability. In changing operating conditions with wind uncertainty, part of wind may need to be curtailed for the safe utilization of the transmission system. In order to minimize the wind power curtailment and to keep the power flow on a transmission line under limits, a cyber resilient Distributed Remedial Action Scheme (DRAS) is developed in this paper. The RAS is formulated as an optimization problem, considering the real power flow constraints of the transmission lines and given wind variability. In this paper, DRAS is developed to operate even with failures in the computing nodes to make it cyber-resilient. Distributed simplex algorithm is used for optimization in the distributed RAS. The DRAS is implemented in a decentralized platform called Resilient Information Architecture Platform for Smart Grid (RIAPS) to enable cyber resiliency of DRAS. The effectiveness of the proposed approach is validated through offline simulations of the New England 39 bus system and online simulations of IEEE 14 bus test system. In conclusion, a cyber physical test bed utilizing Real Time Digital Simulator (RTDS), Phasor Measurement Units (PMUs), and BeagleBones has been used for the online simulation and validation of the developed cyber-resilient RAS.

17 WIND ENERGY↗
DOE OSTI2022

Optimal Voltage Control in Low-Observable Unbalanced Distribution Systems

The increased integration of distributed energy resources (DERs) in distribution systems brings both advantages and technical challenges. High levels of DERs can often cause over/under voltage problems. Classical voltage control algorithms are based on full knowledge of voltage states across all nodes in the system. However, this may not be a practical assumption since many locations in distribution systems are unobservable. Therefore, this paper proposes a new model predictive control (MPC) based control algorithm that accounts for system unobservability to efficiently eliminate voltage violations with as low as 50% fraction of observable nodes. Additionally, an analytical voltage sensitivity framework is employed to quickly determine the change in voltage states due to PV injections. The effectiveness of the proposed method is validated via simulations on the unbalanced IEEE 37 node test system.

Abujubbeh, Mohammad↗
DOE OSTI2018

Optimal Regulation of Virtual Power Plants

This paper develops a real-time algorithmic framework for aggregations of distributed energy resources (DERs) in distribution networks to provide regulation services in response to transmission-level requests. Leveraging online primal-dual-type methods for time-varying optimization problems and suitable linearizations of the nonlinear AC power-flow equations, we believe this work establishes the system-theoretic foundation to realize the vision of distribution-level virtual power plants. The optimization framework controls the output powers of dispatchable DERs such that, in aggregate, they respond to automatic-generation-control and/or regulation-services commands. This is achieved while concurrently regulating voltages within the feeder and maximizing customers' and utility's performance objectives. Convergence and tracking capabilities are analytically established under suitable modeling assumptions. Simulations are provided to validate the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Distributed Automatic Generation Control Considering DPV Using T&D Dynamic Co-Simulation

The increasing adoption of distributed energy resources (DERs) over the last decade warrants a reconsideration of control of generation resources. This paper proposes a distributed Automatic Generation Control (AGC) using transmission-and-distribution (T&D) dynamic co-simulation framework for the efficient DPV frequency regulation services. The co-simulation framework allows AGC units to exchange the information for distributed AGC, based on their adopted communication network topology. As a result, a cost-effective automatic generation control is achieved with DPV and conventional generators. The proposed distributed AGC is based on the gossip algorithm in which the neighboring AGC units share the relevant local information with each other and updates their share of AGC regulation signal. Distributed photovoltaics (DPV) unit contribute to AGC response based on their headroom capacity via DER aggregators. The algorithm is tested on IEEE-14 bus transmission system under conditions of generation failure and random load variation to observe effective frequency regulations service offered by DPVs and other AGC units. The study shows that DPV can effectively participate in AGC with the proposed distributed control framework.

automatic generation control↗
DOE OSTI2021

Integrating Transactive Energy into Reliability Evaluation for a Self-healing Distribution System with Microgrid

Non-utility owned distributed energy resources (DERs) are mostly untapped currently, but they can provide many grid services such as voltage regulation and service restoration, if properly controlled, and can improve the distribution systems reliability when coordinated with utility-owned assets such as self-healing control and microgrids. This paper integrates transactive energy control into the distribution system reliability evaluation to quantitatively assess the impact of non-utility owned DERs on reliability improvement. Here, a transactive reactive power control strategy is designed to incentivize the DERs to provide reactive power support for improving voltage profiles thus enabling additional customer load restoration during an outage. Also, an operational sequence to coordinate the non-utility owned DERs with the utility owned self-healing control and utility owned microgrids is designed and integrated into the service restoration process with the operational constraints guaranteed by checking the three-phase unbalanced power flow for post-fault network reconfiguration. The reliability indices are then calculated through a Monte Carlo simulation. The transactive reactive power control strategy is tested on a four-feeder distribution system operated by Duke Energy in the U.S. Results demonstrate that the non-utility owned DERs with the transactive control improve the reliability of both the system and critical loads by more than 30%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Voltage Regulation Performance Evaluation of Distributed Energy Resource Management via Advanced Hardware-in-the-Loop Simulation

This paper evaluates the performance of coordinated control across advanced distribution management systems (ADMS), distributed energy resources (DERs), and distributed energy resource management systems (DERMS) using an advanced hardware-in-the-loop (HIL) platform. This platform provides a realistic laboratory testing environment, including accurate dynamic modeling of a real-world distribution system from a utility partner, real controllers (ADMS and DERMS), physical power hardware (DERs), and standard communications protocols. One grid service—voltage regulation—is evaluated to show the performance of the coordinated grid automation system. The testing results demonstrate that the coordinated DERMS and ADMS system can effectively regulate system voltages within target operation limits using DERs. The realistic laboratory HIL testing results give utilities confidence in adopting the grid automation systems to manage DERs to achieve system-level control and operation objectives (e.g., voltage regulation). This helps utilities mitigate potential risks (e.g., instability) prior to field deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗