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At least 487 records · Page 27

Performance Evaluation of Hierarchical Controls for Advanced Distribution Management System-Centered Grid Operations: Preprint

This paper presents a hardware-in-the-loop (HIL) platform to evaluate the performance of voltage regulation using an advanced distribution management system (ADMS) for grid operations to control legacy and grid-edge voltage control devices and coordinate with distributed energy management systems (DERMS) to manage high penetrations of photovoltaics (PV) on a utility distribution system. The HIL platform provides realistic laboratory testing, including accurate modeling (legacy devices, grid-edge devices, and PV) of the real-world distribution system from a utility partner, a real controller (ADMS), software controller DERMS, hardware grid-edge devices, and standard communications protocols. The test results show proper functionalities of the integrated platform and the performance of voltage regulation of the coordinated control systems. Based on laboratory testing, the utility can set up the same grid-automation system to manage DERs, legacy devices, and grid-edge devices to achieve their system-level control and operation objectives (e.g., voltage regulation), thus de-risking potential issues (e.g., instability) for field deployment.

ADMS↗

DMS Advanced Applications for Accommodating High Penetrations of DERs and Microgrids

Efficient and effective management of the electric distribution system requires an integrated approach to allow various systems to work in harmony, including distribution management systems (DMS), distributed energy resources (DERs), distributed energy resources management systems, and microgrids. This study highlights some outcomes from a recent project sponsored by the US Department of Energy, Office of Electricity Delivery and Energy Reliability, including information about (i) the architecture of these integrated systems and (ii) expanded functions of two example DMS applications to accommodate DERs: volt-var optimisation and fault location, isolation, and service restoration. In addition, the relevant DER group functions necessary to support communications between the DMS and a microgrid controller in grid-tied mode are identified.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Layer-resolved magnetic proximity effect in van der Waals heterostructures

Magnetic proximity effects are integral to manipulating spintronic, superconducting, excitonic and topological phenomena in heterostructures. These effects are highly sensitive to the interfacial electronic properties, such as electron wavefunction overlap and band alignment. The recent emergence of magnetic two-dimensional materials opens new possibilities for exploring proximity effects in van der Waals heterostructures. In particular, atomically thin CrI 3 exhibits layered antiferromagnetism, in which adjacent ferromagnetic monolayers are antiferromagnetically coupled. In this paper, we report a layer-resolved magnetic proximity effect in heterostructures formed by monolayer WSe 2 and bi/trilayer CrI 3 . By controlling the individual layer magnetization in CrI 3 with a magnetic field, we show that the spin-dependent charge transfer between WSe 2 and CrI 3 is dominated by the interfacial CrI 3 layer, while the proximity exchange field is highly sensitive to the layered magnetic structure as a whole. In combination with reflective magnetic circular dichroism measurements, these properties allow the use of monolayer WSe 2 as a spatially sensitive magnetic sensor to map out layered antiferromagnetic domain structures at zero magnetic field as well as antiferromagnetic/ferromagnetic domains at finite magnetic fields. Our work reveals a way to control proximity effects and probe interfacial magnetic order via van der Waals engineering.

36 MATERIALS SCIENCE↗

Dynamic Distribution Voltage Stability Control Using Distributed Energy Resources for Improved Resiliency

The main goal of this paper is to present the development and simulation of a new dynamic voltage stability control technique, with a focus on effective control and coordination of all available reactive power generation resources in a microgrid setting. Both power electronics and synchronous generator based distributed energy resources (DERs), and grid-supporting functions, are considered to accommodate a high penetration of diverse DERs and energy storage by using an enhanced microgrid voltage stabilizer. A systematic controller parameter synthesizing method is employed, and the overall dynamic voltage stability of the system is studied and evaluated with a time-domain dynamic simulation during emergency, hazard and disaster events. The results with the new approach show significant improvements and enhancements on the dynamic voltage profile of the distribution system, leading towards a more resilient grid system with high penetration of diverse DERs during emergency, hazard and disaster events.

Hatipoglu, Kenan↗

Disassembling 2D van der Waals crystals into macroscopic monolayers and reassembling into artificial lattices

Two-dimensional materials from layered van der Waals (vdW) crystals hold great promise for electronic, optoelectronic, and quantum devices, but technological implementation will be hampered by the lack of high-throughput techniques for exfoliating single-crystal monolayers with sufficient size and high quality. Here, we report a facile method to disassemble vdW single crystals layer by layer into monolayers with near-unity yield and with dimensions limited only by bulk crystal sizes. The macroscopic monolayers are comparable in quality to microscopic monolayers from conventional Scotch tape exfoliation. The monolayers can be assembled into macroscopic artificial structures, including transition metal dichalcogenide multilayers with broken inversion symmetry and substantially enhanced nonlinear optical response. This approach takes us one step closer to mass production of macroscopic monolayers and bulk-like artificial materials with controllable properties.

Science & Technology - Other Topics↗

Risk aware net load balancing in micro grids with high DER penetration

The rapid transformation of micro grids due to the accelerated integration of renewables, storage systems and IoT enabled monitoring and control has opened up new opportunities as well as challenges. Future micro grids will be characterized by high DER penetration and will require sophisticated net load balancing frameworks which explicitly consider the errors in prediction of load and generation due to uncertainty in weather conditions while making decisions. Traditional techniques for grid net load management which rely on isolated shaping of load and supply curves are inadequate and inefficient. For micro grids with high PV penetration, the intermittent and unpredictable nature of PV based energy generation can lead to dramatic and sudden supply demand imbalances thus requiring a holistic framework for balancing net load over the entire horizon. In this paper, we develop a sequential decision making framework for net load management that optimally balances the usage of storage and energy market transactions as a mechanism for mitigating supply demand imbalances (net load imbalances) over the horizon. Our framework specifically accounts for prediction uncertainty of future net load imbalances and minimizes the tail end risk of storage shortfall at the end of the horizon. Using qualitative analysis, we show that our framework achieves its objective of minimum cost net load balancing while accounting for the tail end risk.

14 SOLAR ENERGY↗

Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency

Behind-the-meter distributed energy resources (DERs), including building solar photovoltaic (PV) technology and electric battery storage, are increasingly being considered as solutions to support carbon reduction goals and increase grid reliability and resiliency. However, dynamic control of these resources in concert with traditional building loads, to effect efficiency and demand flexibility, is not yet commonplace in commercial control products. Traditional rule-based control algorithms do not offer integrated closed-loop control to optimize across systems, and most often, PV and battery systems are operated for energy arbitrage and demand charge management, and not for the provision of grid services. More advanced control approaches, such as MPC control have not been widely adopted in industry because they require significant expertise to develop and deploy. Recent advances in deep reinforcement learning (DRL) offer a promising option to optimize the operation of DER systems and building loads with reduced setup effort. However, there are limited studies that evaluate the efficacy of these methods to control multiple building subsystems simultaneously. Additionally, most of the research has been conducted in simulated environments as opposed to real buildings. This paper proposes a DRL approach that uses a deep deterministic policy gradient algorithm for integrated control of HVAC and electric battery storage systems in the presence of on-site PV generation. The DRL algorithm, trained on synthetic data, was deployed in a physical test building and evaluated against a baseline that uses the current best-in-class rule-based control strategies. Performance in delivering energy efficiency, load shift, and load shed was tested using price-based signals. The results showed that the DRL-based controller can produce cost savings of up to 39.6% as compared to the baseline controller, while maintaining similar thermal comfort in the building. The project team has also integrated the simulation components developed during this work as an OpenAIGym environment and made it publicly available so that prospective DRL researchers can leverage this environment to evaluate alternate DRL algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Phasor-Based Control for Scalable Integration of Variable Energy Resources

We propose an innovative framework termed phasor-based control (PBC) to facilitate the integration of heterogeneous and intermittent distributed energy resources (DER) on the electric grid. PBC presents a unified approach that is agnostic to optimization criteria and to the particular characteristics of participating resources. It is enabled by synchronized, high-precision voltage phasor measurements that allow stating control objectives in grid-specific, rather than resource-specific, terms. We present qualitative justification and examine the general feasibility of this control approach, including the behavior of candidate control algorithms in simulation. Initial results suggest that PBC has significant potential to support stable and resilient grid operations in the presence of arbitrarily high penetrations of DER.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multiferroicity in atomic van der Waals heterostructures

Materials that are simultaneously ferromagnetic and ferroelectric - multiferroics - promise the control of disparate ferroic orders, leading to technological advances in microwave magnetoelectric applications and next generation of spintronics. Single-phase multiferroics are challenged by the opposite d -orbital occupations imposed by the two ferroics, and heterogeneous nanocomposite multiferroics demand ingredients' structural compatibility with the resultant multiferroicity exclusively at inter-materials boundaries. Here we propose the two-dimensional heterostructure multiferroics by stacking up atomic layers of ferromagnetic Cr 2 Ge 2 Te 6 and ferroelectric In 2 Se 3 , thereby leading to all-atomic multiferroicity. Through first-principles density functional theory calculations, we find as In 2 Se 3 reverses its polarization, the magnetism of Cr 2 Ge 2 Te 6 is switched, and correspondingly In 2 Se 3 becomes a switchable magnetic semiconductor due to proximity effect. This unprecedented multiferroic duality (i.e., switchable ferromagnet and switchable magnetic semiconductor) enables both layers for logic applications. Van der Waals heterostructure multiferroics open the door for exploring the low-dimensional magnetoelectric physics and spintronic applications based on artificial superlattices.

36 MATERIALS SCIENCE↗

Influence of surfactants on the morphology of SnO{sub 2} nanocrystals prepared via a hydrothermal method

Nanoscaled SnO{sub 2} with different morphologies has been synthesized via a simple hydrothermal process at 180 Degree-Sign C using polyvinylpyrrolidone (PVP), sodium dodecyl sulfonate (SDS), cetyl trimethyl ammonium bromide (CTAB) or tetrapropyl ammonium bromide (TPAB) as surfactant. All the prepared SnO{sub 2} are of a tetragonal crystal structure. Nanocubes, nanorods, nanosheets, nanobelts and nanoparticles were prepared when changing the type and dosage of organic surfactants. It is shown that anionic surfactant (SDS) and cationic surfactant (CTAB or TPAB) at their suitable addition amounts can largely influence the morphologies of SnO{sub 2} nanocrystals. The effect is significantly dependent on the solvent types: water or ethanol. The non-ionic surfactant (PVP) can also change the morphologies like SDS but the impacts are less obvious. The effect of surfactants on the shape and size of SnO{sub 2} nanoparticles was discussed in detail. The particle growth mechanism is described based on the electrostatic interactions and Van der Waals' forces. - Graphical abstract: SnO{sub 2} nanocrystals with controllable morphologies were prepared via a hydrothermal method with surfactants. Highlights: Black-Right-Pointing-Pointer SnO{sub 2} nanocrystals were prepared via a hydrothermal method with surfactants. Black-Right-Pointing-Pointer SnO{sub 2} morphologies changed with the type and the dosage of surfactants. Black-Right-Pointing-Pointer The effect of surfactants on the growth of crystal planes was studied. Black-Right-Pointing-Pointer The controlling mechanisms of surfactants on SnO{sub 2} morphologies were discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chance-constrained Service Restoration for Distribution Networks with Renewables

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

Chance constrained optimization, Distribution serv↗

Resilience of the Electric Grid Through Trustable IoT-Coordinated Assets

The electricity grid has evolved from a physical system to a cyberphysical system with digital devices that perform measurement, control, communication, computation, and actuation. The increased penetration of distributed energy resources (DERs) including renewable generation, flexible loads, and storage provides extraordinary opportunities for improvements in efficiency and sustainability. However, they can introduce new vulnerabilities in the form of cyberattacks, which can cause significant challenges in ensuring grid resilience. We propose a framework in this paper for achieving grid resilience through suitably coordinated assets including a network of Internet of Things devices. A local electricity market is proposed to identify trustable assets and carry out this coordination. Situational Awareness (SA) of locally available DERs with the ability to inject power or reduce consumption is enabled by the market, together with a monitoring procedure for their trustability and commitment. With this SA, we show that a variety of cyberattacks can be mitigated using local trustable resources without stressing the bulk grid. Multiple demonstrations are carried out using a high-fidelity cosimulation platform, real-time hardware-in-the-loop validation, and a utility-friendly simulator.

distributed energy resources↗

Polynomial law for controlling the generation of n-scroll chaotic attractors in an optoelectronic delayed oscillator

Controlled transitions between a hierarchy of n-scroll attractors are investigated in a nonlinear optoelectronic oscillator. Using the system's feedback strength as a control parameter, it is shown experimentally the transition from Van der Pol-like attractors to 6-scroll, but in general, this scheme can produce an arbitrary number of scrolls. The complexity of every state is characterized by Lyapunov exponents and autocorrelation coefficients.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Real Time - Optimal Power Flow Based Distributed Energy Resources Management System (DERMS) (CRADA Number CRD-20-16909 Final Report)

The integration of behind-the-meter distributed energy resources (DERs) into distribution systems brings transformative changes to power systems. This requires operators and planners to find solutions to modernize electric grids and to effectively manage DERs for grid services. NREL developed novel DER management algorithms (referred to as Real-Time Optimal Power Flow, RT-OPF) through U.S. Department of Energy (DOE)-funded efforts, including Advanced Research Projects Agency–Energy (ARPA-E) Network Optimized Distributed Energy Systems (NODES) funding. This cutting-edge control technology aims to modernize distribution systems with large amounts of DER integration, which will help utilities solve issues brought by renewable integration and build resilient and renewable-based electric grids nationwide. Utilidata worked with NREL to investigate the commercialization opportunity of this RT-OPF-based distributed energy resource management system (DERMS). In this project, NREL performs the technology transfer of the RT-OPF to Utilidata to help them fully understand the RT-OPF solution, to identify potential engineering hurdles, and to assess the expected commercial value of various RT-OPF use cases and deployment. The technology transfer work includes two major tasks. First, NREL performs an in-depth knowledge transfer of the entire RT-OPF solution to Utilidata to help them gain an extensive and detailed understanding of the complete RT-OPF solution. In this task, NREL provides exhaustive information (e.g., documentation, code packages, laboratory and field trial data, performance results) while conducting in-depth training sessions to provide a thorough explanation of the entire solution. NREL hosts meetings to present different topics related to the RT-OPF solution, and question-and-answer sessions are included in each meeting to better explain the RT-OPF-related work. Second, the RT-OPF simulations are performed in a laboratory environment. The main objectives of this task are to walk through with Utilidata engineers how to set up a simulation of RT-OPF, identifying each RT-OPF code block/component in operation, learning how these components interact with each other, and eventually running RT-OPF simulations under various system conditions. This task helps Utilidata engineers understand performance limitations and constraints while also quantifying the commercial value of the RT-OPF for different use cases. Based on these two tasks, Utilidata engineers should be able to define and prioritize the next steps of RT-OPF implementation with an eye toward commercial success and scalability of the solution. The next steps are expected to be part of a new project following the conclusion of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Photovoltaic MPPT Charge Controller Real-Time Testbed for Cybersecurity Applications

The increasing deployment of distributed energy resources (DER) over the last decade is a great ally to combat climate change and strengthen the grid during increasingly common extreme weather events. However, DER systems, combined with the ongoing transition to a digital power grid, also pose substantial cybersecurity threats. One of the most common communication protocols used in DER integration is the Distributed Network Protocol 3 (DNP3), which is known to have many security vulnerabilities. Thus, it is essential to investigate cyberattack behaviors and mitigation on power systems using DNP3. In this paper, we designed and implemented a cybersecurity testbed for a simulated photovoltaic (PV) maximum power point tracking (MPPT) charge controller. Our testbed uses an MPPT charge controller simulated on a Typhoon HIL602+ real-time simulator with a real DNP3 communication connection over TCP/IP, allowing for safe and efficient monitoring and manipulation of data traffic between the simulated hardware and supervisory control and data acquisition (SCADA) systems.

14 SOLAR ENERGY↗

Distributed Optimization Approaches with Discrete Variables in the Power Distribution Systems

Traditionally, centralized approaches have predominantly been used for the power system operation and control. With increasing penetration of small-scale distributed energy resources (DERs) in the distribution network, especially independently owned renewable resources, distributed algorithms can serve as a potential alternative for improving scalability, resiliency and addressing privacy concerns. However, the complexity of distributed algorithms significantly increases with the integration of the legacy devices, the operation of which depend on discrete control variables. This paper aims to provide a review of the distributed optimization algorithms incorporating discrete control variables for the power distribution system. While the research in this domain is still at its nascence, an extensive comparison of the approaches in the literature for applying quadratic penalty, branch and bound,ordinal optimization and proximal operator to handle discrete variables in the framework of ADMM and dual decomposition have been addressed. Future research direction in this field have been also provided.

Adan, Jannatul↗