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At least 559 records · Page 31

Implementing a Terrestrial Timing Solution: Best Practices

This document is an overview and guide on the concept of precision time and how an alternative terrestrial timing solution to the Global Positioning System (GPS) can be implemented. What follows is a set of recommendations and best practices, derived from research at Oak Ridge National Laboratory (ORNL), across industry, and within the U.S. government, to implement a system of precision timing synchronization to support resilient operations for the U.S. grid. Precision time is a fundamental necessity for operating the grid today, and it becomes even more important as the grid modernizes with clean energy sources, microgrids, and precision sensors placed throughout the grid system to ensure failureresistant operations. The Global Navigation Satellite System (GNSS), which includes (GPS), is currently the primary provider of precision timing today. A terrestrial-based system for time delivery and synchronization to augment GPS is outlined below and it would provide secure time, synchronized with Coordinated Universal Time (UTC), in the event of outages or other interruptions associated with time delivery.

47 OTHER INSTRUMENTATION↗

Overview on Transactive Energy—Advantages and Challenges for Weak Power Grids

This document lists some challenges that researchers face when implementing transactive energy in weak power grids. These challenges often include high voltage fluctuations, limited generation, high line loadability, and unbalanced grids. The operation of transactive energy, as well as optimization techniques, are also considered, highlighting the performance and functionalities depending on power grid characteristics and market topology. Some of the most used optimization techniques for market clearing, considering the characteristics and topology, are presented as part of the research work. In addition, this paper compares different market topologies and highlights their advantages and challenges. Furthermore, this paper contains a brief description of the interoperability frameworks applied to a smart grid. As a result, it was determined that interoperability is necessary for the proper functioning of the grid. Moreover, all methods were found to be effective for their purpose from the user’s point of view as each technique has different characteristics relevant to the user and the grid. It was concluded that it is convenient to combine the optimization techniques to consider different constraints in the market clearing.

14 SOLAR ENERGY↗

Using a Grid-Forming Inverter to Stabilize a Low-Inertia Power System - Maui Hawaiian Island

As power systems around the world integrate greater amounts of wind and solar photovoltaic power, periods of very high instantaneous power shares of inverters, the primary interfacing technology for these generation sources, are complicating system stability and control. The contemporary, primary mode of inverter operation, grid-following, which explicitly assumes the presence of a local, stable voltage waveform, yields operational inadequacy at high instantaneous power shares potentially leading to instability due to the low-inertia conditions, as well as the correlated reduced voltage forming capacity on the respective system. Parallel connected grid-forming inverters, which directly regulate the local voltage, are a solution that is expected to bolster system stability and mitigate the shortcomings of the grid-following technology. In this paper, grid-following and two types of grid-forming inverter control, the traditional linear droop and the recently introduced nonlinear exponential droop (Droop-e), are simulated on a low-inertia, H = 0.48s, high inverter-based resource scenario, 97%, with a validated electromagentic transient domain model of the Hawaiian island of Maui power system. The benefit of a single grid-forming device over its grid-following counterpart is significant, both in terms frequency deviation and voltage stability. Further, the superiority of the Droop-e and the associated secondary power sharing control over both grid-following and linear droop grid-forming technologies is displayed, with improved nadir and rate of change of frequency over the linear droop control.

droop control↗

Intelligently Partitioned Phasor-EMT Hybrid Simulations of Large-Scale, High-IBR Power Systems

As the penetration level of power electronics-interfaced renewables such as photovoltaics (PV) and wind has surged in modern electric grids, new operational risks caused by the dynamics of those inverter-based resources (IBRs) are emerging in parallel. Lessons learned from various grid events include that the impact of IBRs on system-level grid stability will become prominent along with the increase of renewables and that the short-timescale dynamic impacts of IBRs on grid stability are not fully captured by current commercial dynamic simulation tools [1] [2]. For example, IBRs can be controlled to mitigate those destabilizing interactions, but conventional phasor-domain tools (e.g. PSS/E, PSLF) often cannot capture that; likewise, the existing electromagnetic transient (EMT) simulation tools (e.g. PSCAD, EMTP) can simulate detailed IBR controls, but for large power systems with many IBRs, slow simulation speeds severely impede the ability to study dynamic events [3] [4]. Massively paralleling simulations using high-performance computing (HPC) can help address this, especially now that cloud-based HPC capability is widely available, but today s EMT tools are not HPC-compatible, and parallelization of dynamic simulation solvers is not trivial because each region can dynamically affect the others. Thus, dynamic simulation of grids with very large numbers of IBRs potentially poses a barrier to the ongoing energy transition.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Emerging Computing Architectures: Simulation of Power Electronics in Power Grids

As the penetration of power electronics increases in power grids, new computing architectures needed to be evaluated for the simulation of high-fidelity models of power electronics in power grids in operations. In this paper, emerging computing architectures such as quantum processing units are evaluated for the simulation of power electronics in power grids. A hybrid algorithm based on classical computing and quantum computing is developed and tested for different use cases of electromagnetic transient (EMT) simulation of power electronics (PE)-based systems and simple circuits. The algorithms needed to simulate power electronics in emerging computing architectures are discussed and thereafter, simulation results are shown.

Debnath, Suman↗

Optimal Control for Fast Frequency Response and Black-Start using Embedded Storages with Grid-Forming Control

The grid-forming inverter is regarded as the solution for integrating high levels of renewable resources into future power systems. Ensuring the stable operation of grids necessitates that grid-forming inverters offer fast frequency response. This report introduces an optimal control method that coordinates the embedded storage within the grid-forming control model with conventional synchronous generators. The optimized active power reference for the embedded storage is generated using receding horizon optimization control, aiming to keep the center of inertia frequency within acceptable limits. The effectiveness of the proposed control is verified through testing in the IEEE 39-bus system. In addition, with grid-forming capability, we will also investigate the application of using mobile embedded storages as black-start units to provide cranking power to energize non-blackstart generators in a black-start process.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Deep reinforcement learning assisted co-optimization of Volt-VAR grid service in distribution networks

With the increasing penetration of distributed energy resources in distribution networks, Volt-VAR control and optimization (VVC/VVO) have become very important to ensure an acceptable quality of service to all customers. System operators can rely on slow-responding utility devices, including capacitor banks and on-load tap changing transformers, along with fast-responding battery and photovoltaic (PV) inverters for the VVC/VVO implementation. Because of variations in response time of these two classes of devices, and different control actions (discrete versus continuous), coordinated and optimal scheduling and operation have become of utmost importance. Here, this paper develops a look-ahead deep reinforcement learning (DRL)-based multi-objective VVO technique to improve the voltage profile of active distribution networks, decrease network and inverter power loss, and save the operational cost of the grid. It proposes a deep deterministic policy gradient (DDPG)-based approach to schedule the optimal reactive and/or active power set-points of fast-responding inverters, and a deep Q-network (DQN)-based DRL agent to schedule the discrete decisions variables of slow-responding assets. The reactive power output of PV and battery smart inverters are scheduled at 30-minute intervals and the capacitors’ commitment status is scheduled with several hour intervals. The proposed framework is validated on the modified IEEE 34-bus and 123-bus test cases with embedded PV and PV-plus-storage. To validate the efficacy of the proposed VVO, it is compared with several scenarios, including the base case without VVO, localized droop control of DERs, DDPG-only, and twin delayed DDPG (TD3) agent-based DRL techniques. The results justify the superior performance of the proposed method to improve the voltage profile, reduce network power loss, and minimize the look-ahead grid operational cost while minimizing the undesirable power losses in inverters as a result of power factor adjustments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Feedback Optimization of Incentives for Distribution Grid Services

Energy prices and net power injection limitations regulate the operations in distribution grids and typically ensure that operational constraints are met. Nevertheless, unexpected or prolonged abnormal events could undermine the grid's functioning. During contingencies, customers could contribute effectively to sustaining the network by providing services. Herein this paper proposes an incentive mechanism that promotes users' active participation by essentially altering the energy pricing rule. The incentives are modeled via a linear function whose parameters can be computed by the system operator (SO) by solving an optimization problem. Feedback-based optimization algorithms are then proposed to seek optimal incentives by leveraging measurements from the grid, even in the case when the SO does not have a full grid and customer information. Numerical simulations on a standard testbed validate the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Demonstrating the data center as a flexible grid asset using a C-HIL setup

Increasing data center demand is outpacing grid infrastructure development. Artificial intelligence workloads and hyperscale cloud growth are creating unprecedented demand for power, while traditional grid expansion faces multiyear development timelines. Verrus is developing an innovative datacenter solution for this challenge, data centers that act as active grid-supportive assets rather than passive loads. Our approach integrates a novel grid-aware power flow management system with battery energy storage systems(BESS) into a microgrid-controlled, medium-voltage power distribution architecture that delivers critical capabilities, such as: * Fast response to grid disturbances such over/ under voltage or over/ under frequency * Demand flexibility that can service requests from the utility within 10 s * Uninterrupted transition to islanded operation during grid outages * Continuous uptime assurance for compute loads while maintaining all customer service level agreements. Through Verrus' strategic partnership with the National Renewable Energy Laboratory (NREL), these capabilities were validated using NREL's Advanced Research on Integrated Energy Systems (ARIES) virtual emulation environment to model a 70-MW grid-interactive data center. This paper outlines the design, methodology, and results of this emulated deployment, demonstrating that data centers can provide both critical load resilience and ancillary grid support without compromising uptime requirements. Specifically, we present a digital real time simulation of a 70 MW data center integrated with a physical microgrid controller, and demonstrate the data center response in the event of a grid voltage and frequency event, utility demand response request and utility outage.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multi-Port Autonomous Reconfigurable Solar Power Plant

As the penetration level of power electronics increases and remote photovoltaic (PV) generation is integrated into the alternating current (ac) grid, the short-circuit ratio (SCR) at the point of interconnection of a hybrid PV–energy storage system (ESS) plant may be low. Additionally, the inertia of the alternating current (ac) grid may be low. The low SCRs and inertias can lead to reliability challenges in the power grid. These operating conditions require additional reinforcements, such as synchronous condensers, static var compensators, static synchronous compensators, and high-voltage direct current (HVdc) links/grids. HVdc links or grids may also provide the additional capability of connecting the plant to asynchronous grids and/or connecting asynchronous grids, among others. This scenario leads to discrete development of solar inverters, energy storage inverters, HVdc converters, and several transformers. Some of the problems associated with this discrete development and inverter-based generation include increased cost, lower reliability, and reduced efficiency associated with duplication of power electronics (PEs); competing controls of several individual discrete inverter-based generators due to the presence of multiple PEs, which leads to derating of the system; and transient stability problems arising from inverter-based generation, such as voltage/frequency events leading inverter shutdowns, voltage instability and control interactions in the formed weak grid, and harmonics caused by resonances of multiple inverters.

14 SOLAR ENERGY↗

A Data-Driven Algorithm for Enabling Delay Tolerance in Resilient Microgrid Controls Using Dynamic Mode Decomposition

The increased implementation of smart grid technologies in the power distribution grid presents unique opportunities that enable resiliency, but also brings challenges motivating needs for novel solutions and mitigation techniques. The bi-directional power and data flow allow for the grid to operate with increased resiliency, which is the ability to avoid discontinuity of service to end-use loads during extreme events. However, in applications where control of the distribution grid or microgrid relies on communication networks, the degradation of communication systems in the form of loss or high latency can cause maloperation and result in loss of end-use loads. Here this paper presents a novel framework to enable delay tolerance of centralized microgrid control schemes to mitigate communication system latency impacts and guarantee successful control action. We demonstrate the delay tolerance on a control scheme that operates a battery energy storage system (BESS) to offset the sudden loss of generation and maintain system frequency. During periods of severely degraded communication system performance, the proposed delay-tolerant algorithm compensates for the latency by utilizing a data-driven model generated at the device level using dynamic mode decomposition (DMD) to determine the performance of the communications. The DMD technique predicts the system’s frequency using device-level terminal measurements and provides updated control signals. The HELICS cosimulation platform evaluates the cyber-physical interaction of the power system model in GridLAB-D, the centralized control agent in Python, and the discrete network model in NS-3. The framework is tested and validated on the IEEE-123 node system modified to represent a networked remote microgrid model, and the results show an improvement in the dynamic performance

24 POWER TRANSMISSION AND DISTRIBUTION↗

Federated Architecture for Secure and Transactive Distributed Energy Resource Management Solutions (FAST-DERMS)

This document provides system-level specifications for a federated architecture for secure and transactive distributed energy resource management solutions (FAST-DERMS), presents a solution, and describes operational concepts for the proposed solution. FAST-DERMS enables the provision of reliable, resilient, and secure transmission and distribution (T&D) grid services through the scalable aggregation and near-real-time management of utility-scale and small-scale distributed energy resources (DERs). We first present the principles and objectives of FAST-DERMS. Then, after discussing important system concepts, we present the specifications for FAST-DERMS and a solution that employs a distributed and federated control methodology in which the DERs connected to a single point of common coupling with the rest of the system, such as individual substations, are optimized coordinately to provide system-level grid services. FAST-DERMS aims to aggregate and coordinate the operations of DERs to support T&D grid operations. The key optimization and control component of this FAST-DERMS reference implementation is a flexible resource scheduler (FRS) that aggregates the DERs within a substation service area. These FRSs operate at the substation level and perform constrained economic dispatch of DERs, either directly or through a transactive market or aggregator, as shown in Figure ES-1. An FRS Coordinator at the distribution system operator (DSO) level aggregates distribution substations operated by FRSs and interfaces with the transmission system operator (TSO) to provide transmission services. FAST-DERMS also allows for the integration of the FRS Coordinator with an existing distribution utility management system that could be employed by the DSO to enhance distribution grid operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Soft Actor Critic Based Volt-VAR Co-optimization in Active Distribution Grids

Modern distribution networks are undergoing several technical challenges, such as voltage fluctuations, because of high penetration of distributed energy resources (DERs). This paper proposes a deep reinforcement learning (DRL)-based Volt VAR co-optimization technique for reducing voltage fluctuations as well as power loss under high penetration of DERs. In addition, the proposed approach minimizes the operational cost of the grid. A stochastic policy optimization based soft actor critic (SAC) agent is proposed to configure the optimal set-points of the reactive power outputs of the inverters. The performance of the proposed model is verified on the modified IEEE 34- and 123-bus systems and compared with a base case scenario with no reactive supply by inverters, and a local droop control approach. The results demonstrate that the proposed framework outperforms the conventional droop control method in improving the voltage profile, minimizing the network power loss, and reducing grid operational cost.

—Distribution grids, deep reinforcement learning, ↗

Balancing Authority Data Reformatted

We collect the data from the electricity balancing authorities (BAs) that operate the grid. A balancing authority ensures, in real time, that power system demand and supply are finely balanced. This balance is needed to maintain the safe and reliable operation of the power system.

17 WIND ENERGY↗

Electric Power Grid and Natural Gas Network Operations and Coordination

In this report, we present findings from three studies related to the coordination of natural gas and electricity system operations. We first propose and demonstrate a modeling platform for examining the interdependence of natural gas and electricity networks based on a direct current unit-commitment and economic dispatch model for the power system and a transient hydraulic gas model for the gas system. We use this platform to analyze the value of day-ahead coordination of power and natural gas network operations and to show the importance of considering gas system constraints when analyzing power systems operation with high penetration of gas generators and variable renewable energy sources. In the second study, we utilize our modeling platform to consider the U.S. Federal Energy Regulatory Commission (FERC) Order 809, issued in 2015 to improve day-ahead and intraday coordination of power and gas systems. Finally, in the third study we expand our modeling platform to focus on market-based coordination of electricity and natural gas system operations for a real system, namely a subset of the power and gas networks in the Front Range region of Colorado. We use real system data to evaluate the benefits of coordination operations under different conditions, including different levels of renewable penetration and the use of time-variant, shaped flow nominations. Our results indicate that coordination at various timescales can contribute to a reduction in curtailed gas in high-stress periods (such as those with large ramps in gas offtakes) and a reduction in energy consumption of gas compressor stations. We find that intraday coordination can reduce total power system production costs and natural gas deliverability constraints, yielding cost and reliability benefits. We observe these benefits for the test system as well as in the Colorado case study, where we find that coordination and shaped flows may provide additional value for systems with high penetration of variable renewable energy. Together, these three studies demonstrate a pathway for integrated gas and electricity grid modeling and for studying the benefits of coordinated operations of these increasingly interdependent energy systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Coordinated Modeling of Electric Grid and Natural Gas Network Operations

Presentation based upon full report of a Colorado case study and coordination framework, which is available at https://www.nrel.gov/docs/fy20osti/77096.pdf. JISEA analysts Brian Sergi, Omar Guerra, and Bri-Mathias Hodge will present on recent JISEA work on coordination between the natural gas and electricity sectors. Power and gas are becoming increasingly interdependent but weren't designed to function together. How does greater coordination impact system operations with different levels of solar and wind penetrations? This free JISEA presentation will take place in a Webinar on Tuesday, May 11, 2021 at 12 p.m.: Learn how greater coordination between the natural gas and electricity sectors impacts system operations with different levels of solar and wind penetrations. Presentation information includes: Historical and projected data for natural gas consumption and power generation in the United States as demonstrated by 2014 East Coast Polar Vortex, 2021 Texas Winter Storm Uri. Showing coupling points, FERC identified need for better coordination, different levels of coordination (decision making and optimization control), coordination framework. Case study on Colorado Front Range, ramping requirements and gas nominations, real-time dispatch (June and December scenarios), results of analysis of impacts of coordination on unserved load. Total real-time gas offtakes by node, impacts on unserved gas, effect on CO2 emissions. Discussions on clusions drawn from Colorado Case study expanded co-simulation via HELICS, objectives of the HELICS+ natural gas use case, modeling of hydrogen blending, techno economic assessment of blending, and blending impacts on energy content and pressure.

analysis↗

A Novel Protection Scheme for Unbalanced Faults in Inverter Dominated Networks: A Computationally Efficient Algorithm for Entry-Level Relays

Microgrids are now a common practice in distribution systems to increase resilience and reliability. However, microgrid protection remains a critical challenge, considering its requirement to operate in both grid connected and islanded, and the variability in fault characteristics under each mode of operation. This paper presents unbalanced power (S unb ) based fault detection algorithm, which considers local voltage and current unbalances to determine faults in the system. S unb is a computationally efficient fault detection algorithm that is suitable for implementation in the programmable logic of entry level protective relays. In addition, the difference in current and voltage unbalance (D n ) is used to determine the fault type. The proposed method demonstrates high sensitivity and selectivity for line-to-ground (LG), line-to-line (LL), and double line-to-ground (LLG) faults, representing the most common faults in distribution systems. It also allows relay coordination with upstream and downstream protection devices in both island and grid connected operation, while preserving grading margins. The same pickup and time multiplier settings of a particular relay for both modes of operation eliminates the need for adaptive settings, which rely on communication networks. Validation was performed with a hardware-in-the-loop (HIL) setup using Typhoon HIL real time simulator interfaced with three entry-level, SEL 751 relays. Results confirmed the algorithm’s ability to discriminate fault conditions, and determine the fault type under both operating modes, maintain fast detection times, and ensure proper protection coordination.

fault classification↗

Digital Twin + AI: Control Room of the Future

A digital twin enhances power grid control room operations by providing real-time monitoring, predictive insights, simulation capabilities, remote control, training opportunities, data integration, and decision support. This technology empowers control room operators to effectively manage the grid, optimize performance, and ensure reliable and efficient energy distribution.

control room of the future↗