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Cloud-based Testbed for Adaptive Under-Frequency Load Shedding with High DER Penetration

Increasing penetration of distributed energy resources and behind-the-meter renewables may soon disrupt the efficacy of critical protection schemes, such as under-frequency load shedding (UFLS). Improved data exchange and coordination across the transmission-distribution boundary will be required to maintain reliability of bulk electric system. Standards-based data integration platforms using agreed-upon semantic vocabularies, such as the Common Information Model, will be key to enabling adaptive protection schemes requiring synthesized data from both the bulk power system and behind-the-meter resources. This paper introduces a cloud-based open-source data integration environment and UFLS clustering algorithm being developed to enable adaptive relay coordination between transmission and distribution utilities in the state of Vermont.

Anderson, Alexander A.↗

Clean 2D superconductivity in a bulk van der Waals superlattice

Alternative route to a 2D superconductor Single layers of transition metal dichalcogenides exhibit exotic properties, including superconductivity. The usual route to obtaining such samples is to exfoliate a three-dimensional (3D) crystal. Devarakonda et al. instead grew a superlattice comprising alternating layers of the transition metal dichalcogenide hexagonal NbS 2 and the material Ba 3 NbS 5 (see the Perspective by Schoop). The inert Ba 3 NbS 5 layers serve to dissociate the superconducting NbS 2 layers from one another, resulting in 2D superconductivity with high carrier mobility. The combination of high mobility and reduced dimensionality may give rise to exotic quantum phases. Science , this issue p. 231 see also p. 170

Science & Technology - Other Topics↗

Programmable hyperbolic polaritons in van der Waals semiconductors

Lighting a route for hyperbolic dispersion The propagation of light within a material is usually well defined, with the propagation described by scattering and dispersion. In artificially designed metamaterials and in anisotropic layered materials, the dispersion can be hyperbolic, giving rise to subwavelength confinement of the light. Sternbach et al. show that the hyperbolic dispersion can be optically switched on and off on demand in the layered transition metal dichalcogenide tungsten diselenide (see the Perspective by Deng and Chen). Illuminating the material with ultrafast pulses of sub-bandgap light creates a transient waveguide, resulting in hyperbolic dispersion in the material. The ability to tune the dispersion characteristics on demand using optical pumping is an effective approach for developing ultrafast switching photonic devices and controlling the propagation of light on the nanoscale. Science , this issue p. 617 ; see also p. 572

Science & Technology - Other Topics↗

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs). In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation (SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

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Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗

Planning Roadmap for DER Integration in India: Industry Best Practices and Resource Guide

Ensuring safe, reliable, cost-effective DER integration at scale requires holistic planning, broad stakeholder engagement, and should address key development areas such as standards adoption, equipment testing and certification, interoperability and cybersecurity, interconnection procedures, and advanced forecasting and DER management. Each of these areas currently represent significant challenges for utilities, regulators, OEMs, developers, and even consumers worldwide. India has already seen significant growth of DERs and has announced targets for substantial growth yet to come, with the potential for DERs to make up a non-negligible portion of the country's overall generation capacity. As such, it is of critical importance that Indian stakeholders consider the potential impacts of wide-spread adoption of DERs and take preemptive action related to the five development areas listed here, among others. India should consider strategies including the adoption of key DER standards related to interconnection, testing, and cybersecurity; enabling effective and secure communication channels for DER interoperability; testing and certifying DER equipment in accredited testing laboratories; building robust, streamlined interconnection procedures; and revamping legacy system planning structures to incorporate DERs in a holistic planning framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Recommendations for Data-in-Transit Requirements for Securing DER Communications

With the adoption of Distributed Energy Resource (DER) interoperability standards, common communication protocols are now being deployed between power system operators and DER devices. In 2018, a revision to the US interconnection and interoperability standard, Institute of Electrical and Electronics Engineers (IEEE) Std. 1547, required DER equipment to have an IEEE 2030.5, IEEE 1815, or SunSpec Modbus communication exchange interface. This change supports the future transition to secure connection and exchange of information between the DER equipment and implementing parties, such as grid operators. Adoption of standardized communication protocols and associated information models is a critical step toward interoperability between power system operators and DER, such as photovoltaic (PV) and energy storage systems. However, security requirements for these standardized communication protocols are not comprehensive, resulting in non-standard and vendor-specific implementation that may leave DER equipment susceptible to cyberattacks. This paper examines the data-in-flight security requirements for standardized DER communication protocols, per IEEE 1547-2018 revision, as it relates to device authentication, key management, and encryption. The state of the art for these security features is also explored, addressing their impact on communication and performance of low-cost single board computers, which are typical of DER devices. In conclusion, a recommendation is provided to adopt a common set of communication requirements, which are intended to achieve interoperability and implement data security over DER network pathways, while ensuring reliable, secure, and real-time information delivery.

42 ENGINEERING↗

Cybersecurity Standards, Certification, and Best Practices for DERs

Distributed energy resources (DERs) are becoming increasingly important to the electric grid, including solar energy systems. However, DERs also introduce new cybersecurity risks, including those posed by cloud computing. Standards harmonization is essential for ensuring that DERs are secure and can be safely integrated into the grid. This panel will discuss cyber standards harmonization for solar security. The panel will feature experts from the S2G Program, National Labs and Industry who will discuss the following topics: the cybersecurity risks and future benefits posed by ubiquitous solar energy systems, the development and implementation of cloud-based security solutions for DERs, including solar energy systems, the challenges and opportunities for harmonizing DER cybersecurity standards, and Cyber Informed Engineering and the solar security implementations The panel will also discuss the following specific initiatives: the S2G Program's DER Cybersecurity Framework, UL's DER Cybersecurity Certification Program, and IEEE 1547 Updates. The panel will conclude with a discussion of the future of standards harmonization for DER cybersecurity.

14 SOLAR ENERGY↗

Stability Impact of IEEE 1547 Operational Mode Changes Under High DER Penetration in the Presence of Cyber Adversary

The IEEE 1547 standard addresses the integration of Distributed Energy Resources (DER) into Area Electric Power Systems (AEPS). The updated standard, released in 2018 with revisions ongoing, specifies the need for more flexible settings, requiring the DER to remain connected during certain disturbances and provide voltage support via active and reactive power modes. With these increased capabilities comes increased risks, and our analysis of the standard has produced potential settings combinations, which, while allowable under the standard, may actually create instability. This contradicts the main purpose of the revised standard. Since the DER must support a communication interface through which the AEPS operator can change settings, adversarial mode changes are possible via a cyberattack. This concern is heightened as DER penetration increases, where under a reasonable threat model, an attacker could affect multiple DER simultaneously. We have conducted a simulation analysis of potentially adverse combinations of mode change and ridethrough parameters on a hypothetical AEPS with varying degrees of DER penetration. We conclude that certain adverse mode changes, whether through error or cyberattack, can lead to unstable conditions with DER penetrations as low as 24% of the AEPS system capacity.

24 POWER TRANSMISSION AND DISTRIBUTION↗