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DOE OSTI2024

Trust-Based Detection and Mitigation of Cyber Attacks in Distributed Cooperative Control of Islanded AC Microgrids

In this study, we address the challenge of detecting and mitigating cyber attacks in the distributed cooperative control of islanded AC microgrids, with a particular focus on detecting False Data Injection Attacks (FDIAs), a significant threat to the Smart Grid (SG). The SG integrates traditional power systems with communication networks, creating a complex system with numerous vulnerable links, making it a prime target for cyber attacks. These attacks can lead to the disclosure of private data, control network failures, and even blackouts. Unlike machine learning-based approaches that require extensive datasets and mathematical models dependent on accurate system modeling, our method is free from such dependencies. To enhance the microgrid’s resilience against these threats, we propose a resilient control algorithm by introducing a novel trustworthiness parameter into the traditional cooperative control algorithm. Our method evaluates the trustworthiness of distributed energy resources (DERs) based on their voltage measurements and exchanged information, using Kullback-Leibler (KL) divergence to dynamically adjust control actions. We validated our approach through simulations on both the IEEE-34 bus feeder system with eight DERs and a larger microgrid with twenty-two DERs. The results demonstrated a detection accuracy of around 100%, with millisecond range mitigation time, ensuring rapid system recovery. Additionally, our method improved system stability by up to almost 100% under attack scenarios, showcasing its effectiveness in promptly detecting attacks and maintaining system resilience. These findings highlight the potential of our approach to enhance the security and stability of microgrid systems in the face of cyber threats.

Computer Science↗

DOE OSTI2020

State Strategies for Valuing Distributed Energy Resources in Cost-Effective Locations

The deployment of Distributed Energy Resources (DERs), small-scale electricity generation sources or controllable loads connected to the distribution system or a facility served by the distribution system, can have wide-ranging and positive impacts for the electricity grid. Interconnecting a DER in a high-value location on the grid can unlock benefits beyond those that accrue to the off-taker or asset owner. When DERs are deployed optimally, not only can the individual consumer benefit, but the local utility, the electricity system, and other ratepayers can benefit as well. By engaging in locational DER planning, states can help protect their communities and ratepayers and can help ensure the reliability and resilience of the electricity system. This report explores states' role in better integrating locational value into DER siting and development. It first outlines some of the benefits that can be achieved through the deployment of DERs in high-value locations. It then looks at state policy and regulatory roles and the tools states can use to influence the location of DER development. The report next examines the challenges of locational DER planning, with a particular focus on the challenges that states face in influencing the location of DER development. It highlights three case studies from states that engaged in locational DER planning through the Multistate Initiative to Develop Solar in Locations that Provide Benefits to the Grid and then presents several lessons learned from these efforts. The final section of this report summarizes some recent publications related to locational value of DERs in the form of an abbreviated literature review.

14 SOLAR ENERGY↗

DOE OSTI2012

Optimal Control of Distributed Energy Resources using Model Predictive Control

In an isolated power system (rural microgrid), Distributed Energy Resources (DERs) such as renewable energy resources (wind, solar), energy storage and demand response can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizing costs associated with low battery life of energy storage and maintaining system frequency at the nominal operating value. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem. Simulation studies using high and low wind profiles, as well as, different MPC prediction horizons demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in wind and demand.

Mayhorn, Ebony T.↗

DOE OSTI2019

Approximate Scheduling of DERs with Discrete Complex Injections

Rapid penetration of renewable energy based Distributed Energy Resources (DER) has the potential to exacerbate the challenges inherent in grid frequency and voltage regulation. However, their real time controllability can be leveraged to not only mitigate such challenges, but improve the economics and quality of grid operations. A plethora of DER scheduling algorithms have been developed for fast and efficient scheduling of these resources. These algorithms schedule the complex - real and reactive power injected into (or drawn from) the grid by the DERs under various cost objective functions and grid constraints. However, a vast majority of such algorithms assume the feasible range of power injections to be continuous. In reality, the control options available for several DERs form a discrete space. This implies that the feasible range of power injections also forms a discrete space. This makes DER scheduling an NP-hard problem. Integer/Mixed Integer program based algorithms, which guarantee optimality in the objective value, have been developed. But these are prohibitively expensive in terms of computational time requirements. On the other hand, fast heuristic based solutions have also been developed. But as they do not provide any guarantee on the optimality of the objective, or on satisfying the constraints, they are unreliable for grid operations. Recent works have developed approximation algorithms which offer the best of both the approaches above: (near) optimality and low computational complexity, both of which are governed by a user defined accuracy parameter ϵ. In this work, we significantly improve upon such existing works by developing an approximation algorithm which schedules DERs with complex injections (as opposed to only real injection) and whose runtime is polynomial (as opposed to exponential) in 1/ϵ. We provide theoretical analysis and support them with experimental results to validate the guarantees provided by our approximation algorithm.

14 SOLAR ENERGY↗

DOE OSTI2024

Systems and methods for randomized energy draw or supply requests

The present disclosure can provide a distributed and anonymous approach to demand response of an electricity system. The approach can conceptualize energy consumption and production of distributed-energy resources (DERs) via discrete energy packets that are coordinated by a cyber computing entity that grants or denies energy packet requests from the DERs. The approach leverages a condition of a DER, which is particularly useful for (1) thermostatically-controlled loads, (2) non-thermostatic conditionally-controlled loads, and (3) bi-directional distributed energy storage systems, among others. In a first aspect of the present approach, each DER independently requests the authority to switch on for a fixed amount of time (i.e., packet duration). The coordinator determines whether to grant or deny each request based electric grid and/or energy or power market conditions. In a second aspect, bi-directional DERs, such as distributed-energy storage systems (DESSs) are further able to request to supply energy to the grid.

Frolik, Jeff↗

DOE OSTI2025

Modifying the Optical Emission of Vanadyl Phthalocyanine via Molecular Self-Assembly on van der Waals Materials

Vanadyl phthalocyanine (VOPc) is a promising organic molecule for applications in quantum information because of its thermal stability, efficient processing, and potential as a spin qubit. The deposition of VOPc in different molecular orientations allows the properties to be customized for integration into various devices. However, such customization has yet to be fully leveraged to alter its intrinsic properties, particularly optical emission. Normally, VOPc films on dielectric substrates emit a broad photoluminescence peak in the near-infrared range, attributed to transitions in the Pc ring from its π orbital structure. Here, in this work, we demonstrate that the dominant optical transition of VOPc can be shifted by ∼250 meV through the controlled deposition of thin films on van der Waals material substrates. The weak interactions with van der Waals materials allow the molecules to uniquely self-assemble, resulting in modified optical behavior modulated by the molecular phase and thickness. This work connects the self-assembling properties of molecules to their altered electronic structures and the resulting optical emission.

anions↗

DOE OSTI2018

Narrowing Frequency Probability Density Function for Achieving Minimized Uncertainties in Power Systems Operation – a Stochastic Distribution Control Perspective

With the increased penetration of renewables and other distributed energy resources (DERs), the frequency response in power systems exhibits stochastic nature, where the standard deterministic swing equation should be either represented or transferred into an Ito stochastic differential equation whose solution should be the non-stationary transient behavior of the probability density function (PDF) of the frequency. This transfers the frequency quality control for power systems into a stochastic distribution control problem, where the shape of the frequency distribution, namely the frequency PDF, needs to be directly controlled. In this context, this requires the development of control strategies via controlling the power balance so that the PDF of the frequency is made as narrow as possible whilst centered at its required mean value simple because such a sharp distribution shape means less uncertainties or randomness for the frequency response. In this paper, the formulation of the stochastic swing equation will be made first taking into account of DERs. This will then be followed by the development of stochastic distribution control model that links the power sources with the PDF of the frequency using Fokker Planck Kolmogorov (FPK) equations. A generic constrained optimization problem will be formulated where the cost function is composed of a functional distance between the actual and the desired PDFs of the frequency. A feasible solution using B-spine Neural Networks based stochastic distribution control model will be described. Using the obtained stochastic distribution control model, a set of control algorithms will be described that uses available power sources to shape the PDF of the frequency or to minimize the randomness of the frequency via minimized entropy approach. Future directions will be discussed in the later part of the paper

Swing equation, Power Systems, stchastic distribut↗

DOE OSTI2022

Electrically controllable chirality in a nanophotonic interface with a two-dimensional semiconductor

Chiral nanophotonic interfaces enable propagation direction-dependent interactions between guided optical modes and circularly dichroic materials. Electrical tuning of interface chirality would aid active, switchable non-reciprocity in on-chip optoelectronic and photonic circuitry, but remains an outstanding challenge. Here, in this paper, we report electrically controllable chirality in a nanophotonic interface with atomically thin monolayer tungsten diselenide (WSe 2 ). Titanium dioxide waveguides are directly fabricated on the surface of low-disorder, boron nitride-encapsulated WSe 2 . Following integration, photoluminescence from excitonic states into the waveguide can be electrically switched between balanced and directionally biased emission. The operational principle leverages the doping-dependent valley polarization of excitonic states in WSe 2 . Furthermore, the nanophotonic waveguide can function as a near-field source for diffusive exciton fluxes, which display valley and spin polarizations that are inherited from the interface chirality. Our versatile fabrication approach enables the deterministic integration of photonics with van der Waals heterostructures and could provide optical control over their excitonic and charge-carrier behaviour.

42 ENGINEERING↗

DOE OSTI2018

Magnetism in two-dimensional van der Waals materials

The discovery of materials has often introduced new physical paradigms and enabled the development of novel devices. Two-dimensional magnetism, which is associated with strong intrinsic spin fluctuations, has long been the focus of fundamental questions in condensed matter physics regarding our understanding and control of new phases. Here we discuss magnetic van der Waals materials: two-dimensional atomic crystals that contain magnetic elements and thus exhibit intrinsic magnetic properties. These cleavable materials provide the ideal platform for exploring magnetism in the two-dimensional limit, where new physical phenomena are expected, and represent a substantial shift in our ability to control and investigate nanoscale phases. Here, we present the theoretical background and motivation for investigating this class of crystals, describe the material landscape and the current experimental status of measurement techniques as well as devices, and discuss promising future directions for the study of magnetic van der Waals materials.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Deep Reinforcement Learning for Distribution System Restoration Using Distributed Energy Resources and Tie-Switches

Distributed energy resources (DERs), such as solar PVs and energy storage, can be used to restore distribution system critical loads after the extreme weather events to increase grid resilience. However, coordinating multiple DERs together with tie-switches for multi-step restoration process under renewable uncertainty is challenging. This paper proposes a deep reinforcement learning to control discrete actions of switching on/off tie switches and DERs for critical load restoration. The restoration problem is first cast into the Markov decision process suitable for DRL. Then, the original soft actor critic (SAC) method for continuous actions has been extended to handle discrete and continuous actions. Numerical comparison results with other stochastic optimization-based approaches on the modified IEEE 33-bus system show that the proposed method can achieve fast critical load restoration in the presence of substation power outage while maintaining system voltage limit throughout the restoration process.

active distribution systems↗

DOE OSTI2019

Distributed energy management for community microgrids considering phase balancing and peak shaving

Here, a distributed energy management for community microgrids considering phase balancing and peak shaving is introduced. In each iteration, the house energy management system (HEMS) installed in each house minimises its electricity costs and the costs associated with the discomfort of customers due to deviations in indoor temperature from customers’ set points. At the community level, the microgrid central controller (MCC) schedules the distributed energy resources (DERs) and energy storage based on the received load profiles from customers and the forecast energy price at the point of common coupling. The MCC updates the energy price for each phase based on the amount of unbalanced power between generation and consumption. The updated energy price and unbalanced power for each phase are distributed to the HEMSs on corresponding phases. When the optimisation converges, the unbalanced power of each phase is close to zero. Meanwhile, the schedules of DERs, energy storage systems and the energy consumption of each house are determined by the MCC and HEMSs, separately. Specifically, the phase balancing and peak shaving are considered in the proposed distributed energy management model. The effectiveness of the proposed distributed energy management has been illustrated by case studies.

25 ENERGY STORAGE↗

DOE OSTI2021

Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) (Final Scientific/Technical Report)

This report summarizes the activities conducted under the DOE VTO funded project DE- EE0008451, where ABB Inc. (ABB), in collaboration with Idaho National Laboratory (INL), APS Global (APS), and XOS Trucks (XOS) pursued the development of a cyber-resilient extreme fast charging (XFC) management system. This project entitled Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) focuses on a resilient architecture for smart charging EV Supply Equipment (EVSE) device control and Coordinated Anomaly Detection System (CADS) features that can be added at the charging site depot level to increase cybersecurity. The project was split into two budget periods focused first on developing the threat model and resilient control concepts and second on testing, improving, and validating those developed resilient control algorithms and features with a focus on key vulnerabilities identified during the threat assessment portion of the project. During the first budget period of the CyberX project, the ABB led team focused on activities to identify, model, and quantitatively prioritize high-impact attack scenarios with potential cyber-physical effects while also modeling and developing concepts for a resilient control system that could securely address integration of DERs and other resources with EV charging. Development of the security focused XFC management system (XMS) was accomplished first by offline simulation using a developed XFC station or depot with 480V input level and simulating measurement inputs to monitoring and control systems in concept development. A representative distribution grid model was developed supporting an EV charging site model with BESS and 6 general EV charging models. These EV charging models allowed multiple configurations of charging level, multiple connected protection and measurement devices, and simulation function to show general compromise of EV, BESS, and protection features based on parallel threat analysis. During the second budget period, the EV site and supporting systems model was developed in more detail and converted from offline model to real-time to real-time with EV charging hardware in the loop (HIL). The resilient control architecture developed as concept in the first part of the project was further tested and validated for integration of local energy resources and XFC charging station site equipment while maintaining cybersecure operating principles. The proposed resilient architecture for smart charging and cybersecurity features consists of two main concepts developed and tested within the project. The first concept is an XFC management system (XMS) consisting of a hardware gateway, software platform, and Supervisory Control and Data Acquisition (SCADA) or Distribution Management System integration components. The second concept is a Coordinated Anomaly Detection System (CADS) which forms a primarily software-related subsystem of the total CyberX solution focused on monitoring system measurements, estimation of measurement states, and predicting current at the utility point of interaction based on machine learning for anomaly detection.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Decentralized Distribution System Restoration with Grid-Forming/Following Inverter-Based Resources

The high penetration of distributed energy resources (DERs) in active distribution systems has posed challenges to the centralized distribution system restoration (DSR) strategies in current practice. On the other hand, the advancement in smart inverter technologies enables the bottom-up restoration capability. This paper is motivated to develop a 3-layered hierarchical framework for decentralized DSR, based on the grid-forming (GFM) and grid-following (GFL) grid-edge inverters. The first layer presents the tertiary control, which determines the load pickup schedule and generation dispatch of DERs, using the alternating direction method of the multipliers algorithm. The second layer consists of two control functions: GFM control, which regulates voltage and frequency, establishing a stable grid for GFL inverters to follow; and GFL control, which regulates the real and reactive power. In the third layer, the primary control is proposed to regulate the inverter voltage and current, which is developed based on the virtual oscillator control (VOC). Furthermore, the developed framework is tested in the modified IEEE 13-node test feeder. Two scenarios of grid-connected and islanded operating modes are designed, and simulation results demonstrate the effectiveness of decentralized DSR strategies for controlling grid-edge inverters to enhance the distribution system resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2014

Simplified continuum solvent model with a smooth cavity based on volumetric data

We present a continuum solvent model (CSM) with a smooth cavity for the application in grid-based electronic structure methods. The cavity is identified with the inherently smooth distribution function of a binary mixture at infinite dilution. We obtain a cavity model based on atomic van der Waals radii and one free parameter controlling the overall size. This single parameter is sufficient to adequately reproduce experimental partial molar volumes. The CSM based on this cavity is of similar accuracy in the prediction of aqueous solvation Gibbs energies of small neutral molecules and ions as other CSMs with a smooth cavity. We apply the model to systems in non-aqueous solution, i.e., spiropyran/merocyanin energetics, a proton transfer reaction in dimethyl sulfoxide, and the electrostatic screening of charged gold clusters in an ionic liquid.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Smart Contracts for Power Grid Applications Using the Advanced DLT Cyber Grid Guard Testbed

In this study is presented two power system applications with distributed ledger technology (DLT) and smart contracts (SC) that were assessed in a Cyber-Grid-Guard System (CGGS) advanced testbed, with protective relays, power meters, communication devices, DLT devices, synchronized time source, clock displays and real time simulator. This CGGS testbed was set in the Advanced Protection Lab, 252 lab space of the Grid Research Integration and Deployment Center (GRID- C), at Oak Ridge National Laboratory. In power grids, customer-owned distributed energy resources (DERs) are more frequent than in the past, and the numbers of points of interconnection (POI) with customer-owned DERs have increased. Disruptive operation from DERs presents a risk to grid operations, and protective relays located at the POI are used to isolate out-of-tolerance or poorly behaving of DERs. Ensuring the integrity of data from the relays at the POI, and DLT could enhance the security of the power grids. The first application is a SC to define and control the allowable total power factor (TPF) of the DER (wind farm) output, and the terms of the SC are implemented using DLT with a CGGS for a customer-owned DER. The TPF SC was implemented by the CGGS using DLT. The experimental model was performed with a real-time simulator using a CGGS and relay in-the-loop. The data collected from the CGGS were used to execute the TPF SC. The TPF limits were between +0.9 and +1.0, and the breakers’ operation in the POI was controlled by the relay using the SC. The events were collected from the real-time simulator, CGGS, and SEL 700GT relay to validate a successful application of the TPF SC using DLT. The second application is a SC to measure and control the allowable voltage service limits (VSL) by the CGGS using DLT. The tests were performed by using a real-time simulator, CGGS and relay in-the-loop. The data was collected from the CGGS that executed the SC. The main constraints were defined based on ANSI C84.1 service voltage limits, and the operation of the breakers in the POI. The events were collected from the CGGS, and SEL 700GT relay to assess a successful operation of the VSL SC using DLT.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Building Artificial Layered Solids from the Bottom-up: Materials by Design to Enable New Energy Technologies

This final technical report summarizes the key accomplishments on this DOE Early Career Program award received by PI Guihua Yu at the University of Texas at Austin. The main goal of this ECP award was to develop synthetic methodologies, self-assembly approaches towards structurally controlled nanosheets-like solids from the bottom up, and to understand and characterize their chemical/physical characteristics for the design of future-generation energy devices with novel functions and properties, that will have direct implications for energy science and technologies such as energy storage and conversion, and catalysis. The project accomplished these goals by completing the following objectives: • Rational design, synthesis, and self-assembly of structurally-controlled molecular ‘nanosheets’ materials. Moving beyond conventional van der Waals two-dimensional crystals, this project enables new synthesis and processing strategies to develop ultrathin nanosheets materials, from inorganic transition-metal oxides-based, to hybrid organic-inorganic nanomaterials, with structural factors such as facet, thickness and pore structure being well controlled during synthesis or assembly processes. • Fundamental understanding and electrochemical characterization of these assembled molecular ‘nanosheets’ materials via charge/mass transport studies through electrochemical intercalation of different metal ions for next-generation energy storage, as well as electrocatalytic studies using this new material platform for understanding catalytic reaction kinetics and the roles of surface functionalization and interface interactions owing to atomic thickness, nanoscale porosity, and other structural factors.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Coordinated Optimal Control of PV Inverters and HVAC Loads in Distribution Systems

The increasing integration of distributed energy resources (DERs), such as photovoltaics (PVs) and smart buildings into distribution systems complicate power system operation and controls. This paper proposes a coordinated optimal control strategy for PV inverters and Heating, ventilation, and air conditioning (HVAC) loads in smart buildings to minimize the total network loss in a distribution system. For the HVAC units, we enforce minimum on and off time constraints to avoid frequent switching that can degrade the unit. The proposed control will dispatch optimal control signals of active and reactive power to PV inverters and on/off commands to HVAC units while maintaining the nodal voltage within a secure range and the temperature of HVAC units at a comfort level. The simulation results on a modified IEEE 33-node distribution system demonstrate that the proposed coordinated control scheme can reduce the network loss.

Pani, Naveen↗

DOE OSTI2023

Decarbonizing all-electric communities via carbon-responsive control of behind-the-meter resources

The progression of electrification in the building and transportation sectors brings new opportunities for energy decarbonization. With higher dependence on the grid power supply, the variation of the grid carbon emission intensity can be utilized to reduce the carbon emissions from the two sectors. Existing coordinated control methods for buildings with distributed energy resources (DERs) either consider electricity price or renewable energy generation as the input signal, or adopt optimization in the decision-making, which is difficult to implement in the real-world environment. This paper aims to propose and validate an easy-to-deploy rule-based carbon responsive control framework that facilitates coordination between all-electric buildings and electric vehicles (EVs). The signals of the grid carbon emission intensity and the local photovoltaics (PV) generation are used for shifting the controllable loads. Extensive simulations were conducted using a model of an all-electric mixed-use community in a cold climate to validate the control performance with metrics such as emissions, energy consumption, peak demand, and EV end-of-day state-of-charge (SOC). Our study identifies that 4.5% to 27.1% of annual emission reduction can be achieved with limited impact on energy costs, peak demand, and thermal comfort. Additionally, up to 32.7% of EV emission reduction can be obtained if the EV owners reduce the target SOC by less than 21.2%.

24 POWER TRANSMISSION AND DISTRIBUTION↗