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At least 253 records · Page 14

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↗

Emergency Voltage Regulation in Power Systems via Ripple-Type Control: Preprint

With increasing penetration of volatile renewable generation and cyber-physical disruptions, ensuring safe operation of bulk power systems has become unprecedentedly challenging. Since communication and computational costs restrict centralized system dispatch to be called upon every few minutes; and purely local schemes are shown to be insufficient, distributed controls have been advocated for handling unanticipated system conditions in real time. However, the applicability of distributed control schemes is fundamentally limited by their need for widespread communication and model cognizance. In this con-text, we put forth a hybrid low-communication saturation-driven protocol for the coordination of control agents that are distributed over a physical system and are allowed to communicate with peers over a ‘hotline’ communication network. Under this protocol, when agents observe a constraint violation based on local measurements, they respond locally until their control resources saturate, in which case they send a beacon for assistance to peer agents. The scheme ensures that minor violations are efficiently mitigated via fast local controls, while severe violations may be handled by a collaboration of a relatively small set of agents. We evaluate the performance of this scheme via extensive numerical tests on the IEEE 14-bus test feeder, where agents act upon noisy measurements under diverse scenarios of random load variations and severe low/high voltage events.

distributed control↗

Introducing the 9500 Node Distribution Test System to Support Advanced Power Applications: An Operations-Focused Approach

The 9500 Node Test System is a representative section of distribution power system model developed as a part of the GridAPPS-D™ project, an effort funded by DOE as a part of the Grid Modernization Lab Consortium (GMLC) program. The test system was developed to fulfill a growing need to represent the rapidly evolving state of electric distribution systems by combining elements of legacy infrastructure systems, modern feeder topologies, and an anticipated future with smart grid technologies. It also provides a network model capable of supporting the simulation of operational scenarios such as the ones in a utility distribution control center. This test system allows the evaluation of the performance of advanced power applications in real-time, such as one that simulates the operations of an Advanced Distribution Management Systems (ADMS), Distributed Energy Resource Management Systems (DERMS), etc. in a Distribution control center. This model is an extension of the widely used IEEE 8500 Node Test Feeder and is currently being validated to become an IEEE test case to help increase adoption and widespread usage among both academia and industry. It is a full-size model representative of a section of a utility’s distribution system with multiple feeders fed from different substations. The model includes multiple distribution circuits, a sub-transmission system, multiple substations, behind the meter customer rooftop photovoltaics (PV), and multiple utility-scale distributed energy resources. To enable accurate simulations of operational scenarios, the 9500 Node Test System is designed to support procedure-based operations, with the ability to realistically demonstrate switching operations, feeder reconfiguration, adjustment of volt-var control equipment, dispatch of distributed generation, and response to planned and unplanned outages. The 9500 Node Test System includes three radial distribution feeders with 12.3 MVA of average load, consisting of both medium voltage and low voltage equipment each supplied by a different distribution substation. The three distribution feeders are connected to each other through Normally-Open switches which can be closed when needed to simulate restoration scenarios due to a fault. One feeder represents today’s grid with low penetration of customer-side renewables. The second represents a potential future grid with microgrids and 100% renewable penetration. The third has no customer generation resources, a district steam plant, and a utility-scale solar farm. The three diverse circuits were created to allow the simulation of both today’s situation as well as potential future scenarios. All three feeders have customers connected by low-voltage secondary triplex lines. This test system meets all requirements outlined in the report for creating a simulation environment that would enable discussion between key technical stakeholders as well as having the potential to accelerate operational application development and their subsequent testing and integration. The new model is a possible representation of what we believe the distribution grid may look like in the future: a high penetration of renewables, reconfigurable radial and mesh topology, numerous DERs, islanded microgrids, and significantly increased data and measurement density. The system supports both the solution of existing and newer algorithms but also enables the evaluation of applications in a realistic operational environment defined by task oriented procedural steps that represent the interaction between the control center operator and field personnel.

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A Fairness-based Distributed Energy Coordination for Voltage Regulation in Distribution Systems

The rapid adoption of photovoltaic (PV) systems combined with falling prices of energy storage is paving the way for a future in which customers could locally supply their energy needs and export surplus power to the grid. However, reverse power flow from multiple sites in a network can cause overvoltage that decreases system reliability and the utilization level of PV system. In this paper, we present a two-stage approach to solve the energy coordination problem in distribution networks. In the first stage, a household with PV and energy storage is optimized to allow customers to adopt different control strategies such as load following and tariff arbitrage. We show that such customer-led control strategies can cause reverse power flows during peak PV generation periods, thus resulting in overvoltage. In such cases, the second stage of the proposed approach is called upon to solve a fairness-based energy coordination problem that can maintain voltages within limits while maximizing the PV generation while fairly distributing the actions among all the PV systems. As a result, each of the resources in the network has equal opportunity to export power and shares the responsibility of voltage regulation. Simulation studies have been carried out on the IEEE 13-bus test feeder to verify the effectiveness of the proposed approach.

Distributed energy resources, fairness, overvoltag↗

Thoughts and Hypotheses on the Metrics and Needs for the Stability of Highly Inverter-Based Island Systems

As levels of wind, photovoltaics (PVs), and battery energy storage on power systems rise, it is useful to be able to quickly compare how much generation (instantaneous power and annual energy) comes from these inverter-based resources (IBRs). A commonly used metric is the percentage of inverter-based generation (% IBR) in a dispatch scenario (as a percentage of the total generation or total load), which can be useful for estimating when certain operational challenges arise (high rates of change of frequency, underdamped control interactions, low system strength, low fault current availability, and so on). Another similar and commonly used metric pioneered on the relatively large island of Ireland, system nonsynchronous penetration (SNSP), is similar to the % IBR and is subject to similar limitations. SNSP has the advantage of handling high-voltage dc in a defined way.

fault currents↗

Power Sharing-Based Framework for Allocating Automatic Generation Control in Distributed Energy Resources: Preprint

The recent proliferation of distributed energy resources (DERs) in the power network along with the retirement of conventional generators has made it challenging to regulate system frequency. In this paper, we present a centralized control framework to leverage the potential of DERs in the distribution network in provisioning secondary frequency control services to the grid. The proposed framework is based on network volt-watt sensitivity analysis and takes into account DER operational and network-imposed constraints to allocate the automatic generation control (AGC) request among the aggregated units. The proposed framework was implemented on the IEEE 8500-node test feeder and results were validated against a standard linear programming-based scheme. Numerical results indicate that the proposed framework can successfully utilize the available power production headroom of the network to meet the AGC request while maintaining nodal voltages within acceptable limits.

distributed energy resources↗

A Distributed Control Architecture for Cascaded H-Bridge Converter with Integrated Battery Energy Storage

Cascaded H-bridge topology has been used in grid-tied converters for battery energy storage system due to its modular structure. To fully utilize the converter’s modularity, this paper proposes a hierarchical distributed control architecture that consists of primary control, secondary control and battery state of charge (SOC) balancing control. Primary control ensures accurate current tracking while a distributed secondary control based on consensus algorithm is presented to regulate power sharing among modules and is proved to be stable theoretically. Here, a distributed SOC balancing control is further introduced to improve energy efficiency of battery energy storage system. Finally, the hierarchical distributed control strategy is implemented using hardware controllers and a software platform. Besides, a carrier phase shift control is also implemented to achieve multilevel output voltage and harmonic reduction. The experimental results demonstrate the performance of the proposed control scheme effectively.

25 ENERGY STORAGE↗

Blockchain-Enabled Cyber-Secure Microgrid Control Using Consensus Algorithm: Preprint

This paper proposes a distributed control method based on a consensus algorithm for distributed energy resources (DERs) using blockchain as a secure communication medium for cyber resilience. Each DER communicates with a local blockchain server that is maintained by the distributed ledger technology to allow for securely sharing local measurements among neighboring assets to achieve the global control objectives, i.e., voltage and frequency regulation as well as accurate power sharing among the DERs, including collective grid-forming capability. To prove that the distributed control can retain system stability under a blockchain-induced variable communication delay, Lyapunov function-based stability analysis is carried out. This paper demonstrates the concept on an 11-bus test case developed in MATLAB Simulink, which has been modified from the IEEE 9-bus test case, to study dynamic operations of the five inverter-based DERs working with a blockchain-induced variable delay. The results validate the superior performance of the proposed control method, compared to heavily compromised operations of the other test cases without the security measure, affected by heavy communication delays and communication interruptions.

blockchain↗

High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP): Design Guidelines and Specifications for DC Distribution-Based Charging Hub

Managed under U.S. Department of Energy (DOE)-funded EVs@Scale Consortium, High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP) project aims to design and develop a high-power, interoperable charging experimental platform to research, develop, and demonstrate the integration and control approaches for a DC distribution-based high-power charging (HPC) system. The eCHIP project addresses the crucial need to design and validate efficient, low-cost, reliable, and interoperable solutions for DC-coupled charging hub ('DC hub' for short). This report explains the design, development, and implementation process of the experimental platform for the DC hub. The utilization of DC distribution holds significant potential for enhancing the operation of an HPC station architecture. However, there are challenges establishing the DC hub, including interoperability, commoditization, distributed energy resource integration, stability, DC protection, and lack of common system level controllers. To address these challenges, a testing setup is required that accommodates commercial off-the-shelf (COTS) products as well as novel, in-house designed solutions to evaluate different use cases at rated power and voltage levels.

33 ADVANCED PROPULSION SYSTEMS↗

EVs@Scale Lab Consortium High-Power Charging Pillar Deep-Dive Technical Meeting

Managed under the the U.S. Department of Energy (DOE)-funded EVs@Scale Consortium, the High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP) project aims to create an experimental platform for integration and control approaches in a direct current (DC), distribution-based high-power charging (HPC) system. The eCHIP project addresses the crucial need to design and validate efficient, low-cost, reliable, and interoperable solutions for a DC-coupled charging hub ("DC hub" for short). This report explains the design, development, and implementation process of an experimental platform for the DC hub. DC distribution holds significant potential for enhancing the operation of an HPC station architecture. However, there are challenges in establishing a DC hub, including interoperability, commoditization, distributed energy resource integration, stability, DC protection, and a lack of common system-level controllers. To address these challenges, a testing setup is required that accommodates commercial off-the-shelf (COTS) products, as well as novel, in-house designed solutions, to evaluate different use cases at rated power and voltage levels. The developed proof-of-concept charging platform and open-source SEMS allow the development and testing of various controllers and chargers from different vendors. The DC hub platform integrated EVs, an ESS, a PV system, and building load to demonstrate the flexibility of the platform. The open-source SEMS controlled the devices within the hub using a rule-based implementation, realizing available standards.

ADVANCED PROPULSION SYSTEMS↗

Performance Evaluation of Distributed Energy Resources Management System via Advanced Hardware-in-the-Loop Simulation: Preprint

This paper presents an advanced hardware-in-the-loop (HIL) platform to evaluate the performance of voltage regulation coordinated across advanced distribution management systems (ADMS), distributed energy management system (DERMS), and DERs. The HIL platform provides realistic laboratory testing, including accurate modeling of the real-world distribution system from a utility partner, real controller (ADMS and DERMs) and power (DERs) hardware, and standard communications protocols. The test results show proper functionalities of the integrated platform and performance of the peak load management of coordinated control systems. Based on the laboratory testing, the utility can set up the same grid automation system to manage DERs to achieve system-level control and operation objectives (e.g., peak load management), thus derisking potential issues (e.g., instability) for field deployment.

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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.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Real-Time Dispatcher for a Distributed Energy Resource Power Plant to Provide Grid Services [SWR-25-17]

This software dispatches the aggregated power of a distributed energy resource (DER) plant located on an electrical distribution network. It is designed to provide the following services to the grid in real-time: (i) voltage support of the distribution network, (ii) virtual power plant at the substation with power factor support, and (iii) operating reserves for automatic generator control for the transmission system. This dispatcher integrates with the local power plant controller and utilizes the battery energy storage system (BESS) to smooth the volatile net power output from the DERs. It can also integrate with a day-ahead scheduler to strategically charge and discharge.

Comden, Joshua [National Renewable Energy Laborato↗

Event-Driven Predictive Approach for Real-Time Volt/VAR control with CVR in solar PV rich Active Distribution Network

The focus of this paper is on analyzing the impact of conservation voltage reduction in the presence of active devices such as solar photovoltaic (PV) and developing controls that leverage these distributed energy resources. An event-driven predictive approach for real-time volt/volt-ampere reactive (VAR) optimization, along with local two-level adaptive volt/VAR droop-based control algorithm for advanced distribution management systems, is introduced. The methodology covers aggregated and autonomous controls under different timescale operations, including the impact and effect of unpredicted events such as cloud transients on PV power production. In addition, the control schemes include the uncertainties in PV power generation and load power demand. The proposed methodology is validated in a real-time framework using the real-time digital simulator platform through co-simulation with models based on Python and OpenDSS (Open Distribution System Simulator). The developed methodology is tested on the modified IEEE 123-feeder test system. The results reveal that the proposed methodology works well in the presence of high penetrations of PV power, produces significant energy savings, and mitigates over-/undervoltage problems.

14 SOLAR ENERGY↗

A Sequential Model Predictive and Deep Reinforcement Learning-Based Controller for Distribution System Outage Mitigation under Hurricane Events

This paper proposes a proactive outage mitigation framework for power distribution networks to withstand hurricane-induced disruptions. It leverages Model Predictive Control (MPC) to identify safe lines for proactive switching during hurricanes, minimizing the risk of cascading failures and voltage violations. The switching strategies optimized by MPC are sequentially integrated with a Deep Reinforcement Learning agent using the Advantage Actor-Critic algorithm, enabling dynamic line switching to maximize connected buses and minimize voltage violations in real time. Using a probabilistic hurricane model, the framework predicts line failures and adapts to varying conditions to enhance grid resilience. Simulations on the IEEE 123-bus system demonstrate its effectiveness in maintaining high connectivity and minimizing disruptions. Real-time testing with an RTDS confirms the practicality and reliability of the proposed approach.

Selim, Alaa [University of Connecticut]↗

The Future of Renewable Energy Transmission: An Autonomous Energy Grid

The drastic price reduction in variable renewable energy, such as wind and solar, coupled with the ease of use of smart technologies at the consumer level, is driving dramatic changes to the power system that will significantly transform how power is made, delivered, and used. Distributed energy resources (DERs)—which can include solar photovoltaic (PV), fuel cells, microturbines, gensets, distributed energy storage (e.g., batteries, ice storage), and new loads (e.g., electric vehicles (EVs), light-emitting diode (LED) lighting, smart appliances, and electric heat pumps)—are being added to electric grids and causing bidirectional power flows and voltage fluctuations that can impact optimal control and system operation. Residential solar installations, customer battery systems, and EVs are all seeing rapid increases in deployments. With DER seeing such increased use, it is not unreasonable to imagine a residential electricity customer having at least five controllable DERs. In future electric grids, as more DERs are integrated, the number of active control points will be too much for current control approaches to effectively manage.

30 DIRECT ENERGY CONVERSION↗

Anomaly Detection and Mitigation in FACTS-based Wide-Area Voltage Control Systems using Machine Learning

With the increasing deployment of Flexible AC Transmission System (FACTS) devices in wide-area voltage control systems (WAVCS) for achieving improved voltage stability of bulk power systems, the possibility for cyber attacks on these systems is also increasing. Successful stealthy cyber attacks that are difficult to detect by traditional informational technology (IT)-based cybersecurity solutions or threshold-based bad data detectors can lead to a voltage collapse in power grid. This paper presents the testbed-based attacks implementation and real-time evaluation of machine learning (ML) algorithm for detecting and mitigating stealthy cyber attacks on FACTS-based WAVCS on a hardware-in-the-loop (HIL) testbed. Initially, we discuss the implementation of a fuzzy logic controller (FLC) that controls a Static VAR Compensator (SVC) device deployed in a two-area four-machine Kundur power system for improving transient voltage stability. Later, the ML-based Anomaly Detection and Mitigation (ADM) system is implemented on the cyber-physical HIL testbed to detect and mitigate various stealthy cyber attacks, which are injected in real-time over the wide-area network (WAN). The experimental results show accurate and effective performance of ADM system in detecting and mitigating anomalies while keeping the grid stable and within the system operating limits, as defined by the North America Electric Reliability Corporation (NERC).

24 POWER TRANSMISSION AND DISTRIBUTION↗

On the impact of tidal generation and energy storage integration in PV-rich electric distribution systems

Deep decarbonization of power system operations requires the maximal utilization of available renewable resources. At distribution-level operations, however, grid operators can face numerous challenges in integrating renewables at scale owing to the inherent intermittence of renewable energy resources. These include phenomena such as voltage fluctuations, which are typically mitigated through control actuators such as on-load tap changers (OLTC) as well as energy storage devices, such as battery energy storage systems (BESS). On the one hand, high intermittence of the available renewable portfolio may require increasingly aggressive control of actuators, thereby accelerating the probability of equipment failure. On the other hand, integrating BESS operations and having a diverse renewable generation portfolio can typically help stagger power/energy flow to mitigate the aforementioned adverse impacts. In this paper, we employ a Bayesian framework for equipment lifetime estimation to understand the impact of including tidal energy resources and BESS in distribution system operations for feeders having substantial distribution photovoltaic generation. Our results indicate that while tidal energy alone may slightly decrease equipment reliability, the adverse impact on reliability is significantly magnified by a generation portfolio consisting of tidal generation and photovoltaic generation. Here, we also study the tidal and photovoltaic hosting capacity problem with and without energy storage systems using equipment reliability as an added constraint. We conclude that energy storage increases the reliability-constrained hosting capacity of the distribution system.

14 SOLAR ENERGY↗