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At least 667 records · Page 37

Management of Risk and Uncertainty Through Optimized Co-Operation of Transmission Systems and Microgrids With Responsive Loads (Final Report)

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. Ambitious national and state-level goals around the decarbonization of electricity relies on the integration of very high levels of renewable resources, most of which are variable and intermittent. The use of demand response is an ideal approach to counterbalance the intermittency of renewable generation and brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distribution system, these resources are typically modeled as variables at the transmission network level. Demand-side participation cannot be leveraged effectively without explicitly including the distribution system dynamics in the optimization-based wholesale market operations. This project grew from a vision for co-optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system. In this framework, microgrids encompass consumers, distributed renewables and storage. The energy management system of the lower voltage system (distribution or microgrid) can also sell (buy) excess (necessary) energy from the transmission system. Until recently, very little research had been conducted on the co-optimization of these two systems due to computational limitations. However, advances in computational capabilities, and the judicious use of decomposition methods and innovative approximation methods for high-dimension dynamic programming made this goal a viable objective for this project, leading to a fundamental shift in the ability to integrate and fully utilize demand-side resources. To this end, the modeling framework developed introduces a novel co-optimization framework, to include the operations of both the transmission and distribution systems (or microgrids) in operational decision making. This framework was used to analyze renewable and distributed generation along with responsive demand and to compare the capability of co-optimized systems to perform with higher levels of variable renewables. An ideal microgrid is defined as an electric entity capable of operating in both interconnected (with the high-voltage grid) and islanded mode. As such, the microgrid should incorporate generating units (traditional units and intermittent) and if needed, exchange power with the high-voltage grid. The interplay between the microgrid and high-voltage grid motivated the development of the co-optimization approach to ensure efficient performance of the interconnected network. Results show that the use of a bi-level optimization approach is an appropriate structure, capable of co-optimizing a transmission system with multiple distribution systems and microgrids. While increasing the number of connected systems provides increasing flexibility for renewables integration this can also the economic benefits to the low-voltage subsystems with each additional system connected. Comparison of a traditional single-level decision structure with the co-optimization approach illustrates a reduction in overall system cost under co-optimization, while specific cost allocations to transmission and distribution systems are changed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Alternative Approaches to Traditional Net Energy Metering

Most jurisdictions in the United States originally implemented net energy metering (NEM) tariffs to support the deployment and interconnection of distributed generation (DG) resources (e.g., rooftop solar photovoltaic systems). Since then, NEM has proven effective in promoting adoption of DG resources. Recently, due to concerns about sufficient recovery of utilities’ revenue requirements and cost-shifting, there is increasing interest in—or statutory requirements to pursue—alternative compensation approaches, especially in U.S. states and territories with robust growth in distributed solar. Recent increases in other forms of distributed energy resources (DERs) that can potentially send power to the distribution grid (e.g., distributed battery energy storage system (BESS)) are further driving compensation reforms. This brief provides an overview of design elements associated with alternative approaches to traditional NEM, summarizes common arguments for and against them, and identifies implementation issues that utilities may need to address. Although this brief may be most useful in jurisdictions that are interested in or required to move beyond NEM, it is also applicable to those jurisdictions that have already done so—and are looking to further implement reforms to their existing compensation mechanisms. In the broadest sense, there are three primary tariff-related components when interconnecting a DER onto the local utility’s distribution system (adapted from Zinaman et al., 2017): 1. Metering and Billing Arrangements: How utilities measure and bill electricity consumption and production. 2. DER Export Tariff Design: The structure under which utilities compensate customers for electricity they export to the grid. 3. Consumption Tariff Design: The structure under which customers pay for electricity they consume from the grid. When implementing changes to any of these primary tariff-related components, there are likely implications for a utility’s metering system, billing system, and other technology systems. Where applicable, this brief explicitly identifies such implementation challenges.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Analysis of Grid-Forming Inverter Controls for Grid-Connected and Islanded Microgrid Integration

Autonomous grid-forming (GFM) inverter testbeds with scalable platforms have attracted interest recently. In this study, a self-synchronized universal droop controller (SUDC) was adopted, tested, and scaled in a small network and a test feeder using a real-time simulation tool to operate microgrids without synchronous generators. We presented a novel GFM inverter control adoption to better understand the dynamic behavior of the inverters and their scalability, which can impact the distribution system (DS). This paper provides a steady-state and transient analysis of the GFM power inverter controller via simulation to better understand voltage and frequency stabilization and ensure that the critical electric loads are not affected during a prolonged power outage. The controllers of the GFM inverter are simulated in HYPERSIM to examine voltage and frequency fluctuations. This analysis includes assessing the black start capability for photovoltaic microgrids, both grid-connected and islanded, during transient fault conditions. The high photovoltaic PV penetration levels open exciting opportunities and challenges for the DS. The GFM inverter control demonstrated appropriate response times for synchronization, connection, and disconnection to the grid. The DS has become more resilient and independent of fossil fuels by increasing the penetration of inverter-based distributed energy resources (DERs).

Ward, Laura (ORCID:0000000345501581)↗

Application of Intelligent Load Control to Manage Building Loads to Support Rapid Growth of Distributed Renewable Generation

Electricity utilities are faced with the mounting challenge of providing a stable supply of power to meet the growing demand while also integrating rapid growth in distributed variable renewable generation. Traditional means of balancing short- and long-term supply and demand imbalance will be expensive. Alternative approaches of using flexible loads in buildings are needed to mitigate the imbalance at a lower cost. This paper shows how the intelligent load control (ILC) process can be used to manage loads in buildings by dynamically prioritizing loads for curtailment using both quantitative and qualitative criteria. The ILC process can be deployed on low-cost computing platforms without the need for any additional sensing. ILC was first validated in a simulation environment to provide two grid service use cases: (1) managing monthly peak electricity demand and (2) managing buildings’ electricity consumption during a capacity bidding event. After being successfully tested in a simulation environment, ILC was deployed on real buildings to manage electricity consumption to provide two different use cases under different outdoor operating conditions. Both the simulation tests and the real building experiments were deployed using VOLTTRON™, a distributed sensing and control platform. The results from the tests and experiments showed that ILC was able to manage the controllable loads (heat pumps) in the building to maintain the electricity consumption at the desired level without a significant impact on occupant comfort. Overall, the results demonstrate that the ILC allows coordination of the controllable loads and provides a more intelligent means of load management than the traditional duty-cycling approach.

Kim, Woohyun↗

High Speed Medium Voltage CHP System with Advanced Grid Support

The project was a collaboration between Clemson University and TECO Westinghouse Motor Company. The goal of the project was to develop a medium voltage commercial grid-tied system with advanced grid support functions. Current state-of-the-art in medium voltage, multi-megawatt power electronic systems do not support advanced grid functions, traditionally due to power electronic limitations and required applications. The developed system is capable of interacting with the power system at the distribution level to efficiently integrate gas turbine generation systems or any other ac generation system with up to 20MWe of power production capacity. This project demonstrated a high level of technical readiness of the 1MW, 500Hz, 15000 RPM high frequency Combined Heat and Power (CHP) generator and electric machine system, utilizing advanced grid support functions required by IEEE Std. 1547-2018.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Stochastic Microgrid Scheduling With Chance‐Constrained Resilience Consideration

Traditionally, it is assumed that microgrids transition seamlessly from grid‐connected operation to islanded mode in the event of sudden main grid outages. In reality, the islanding process, especially unintentional islanding, is rarely seamless. Instead, it is subject to voltage and frequency fluctuations caused by the instantaneous disconnection of the point of common coupling (PCC) switch, variations in loads and renewable generation output and even the protection tripping of distributed energy resources (DERs). To mitigate these fluctuations and facilitate a smooth islanding process, we propose a stochastic microgrid scheduling model that incorporates chance‐constrained resilience measures. Specifically, the resilience measure is defined as the probability of successful islanding (PSI), that is, the probability that a microgrid can mitigate the generation‐demand imbalance caused by the disconnection of the PCC switch, variations in load and renewable generation and DER tripping. This measure is modelled using chance constraints. Unlike existing reliability and resilience indices, which typically neglect the possibility of microgrid/DER failure under extreme events and assume their survival while primarily focussing on reducing impact duration or magnitude, the proposed PSI‐based framework explicitly addresses microgrid and DER survival during the islanding transition. The formulated nonlinear chance constraints are approximated using a multiinterval approach and equivalently represented as a mixed‐integer linear programming (MILP) formulation. Case study results validate the proposed method, showing that the PSI estimation error is reduced to less than 8%, compared to approximately 28% with existing methods. Various sensitivity analyses on the DER tripping rate and PSI settings were performed to validate the robustness of the proposed method. In particular, the necessity of accounting for DER tripping in the PSI calculation was demonstrated.

chance constrained optimization↗

Building-to-Grid Modeling Framework with a Case Study of Battery Systems

Coordinating electricity load shifting operations of multiple buildings has the potential to achieve significant benefits for both building owners and grid operation. In support of this research, this paper develops a novel building-to-grid modeling framework, which uses EnergyPlus to develop physics-based building energy models and GridLAB-D to develop distribution-level grid models. The data exchanges between buildings and distribution-level grid are conducted using Python script and HELICS co-simulation platform. Then, by using this modeling framework, this paper conducts a case study of battery systems in a connected community, which consists of 10 multi-family buildings with appropriately sized batteries. The three scenarios, baseline operation, tolerant to price fluctuations, and opportune usage, are studied. The result displays that, by adopting onsite batteries, both electricity costs for building owners and aggregated peak power demands are reduced.

Building-to-grid, connected community, co-simulati↗

Comparison of Power System Current Sensors via Playback of Electrical Disturbances

The need to accurately measure high-frequency content in power system voltage and current phenomena is increasingly becoming more of a priority. As the amount of distributed energy resources (DER) and nonlinear loads penetrating the grid increases, so do challenges associated with traditional measurement and metering applications. In this paper, three commercially-available medium-voltage-level current sensors are characterized in terms of their harmonic amplitude and phase performance against reference signals that are “played back” through the sensors through the use of an arbitrary waveform generator. It is shown that none of the three sensors studied are able to faithfully replicate all of the input signals completely, though there are advantages and disadvantages to each in terms of noise, resonance, and induced phase drift. Additionally, the Goodness-of-Fit metric, typically used for PMU model validation, is used to generate side-by-side comparisons of sensor accuracy over a small window around the events under study.

Wilson, Aaron↗

Communication-Constrained Robust Control and Learning of Grid-Connected

The electric grid of things (EGoT) promises great potential for innovative grid services by tapping into vast load flexibility. However, the unique characteristics of EGoT, being a part of the cyber-physical electric power system, present both opportunities and challenges, especially concerning supply-demand balancing, stability, and communication constraints. Traditionally, centralized control was employed to ensure balance and stability in power systems. However, with the massive influx of EGoT devices, new strategies are needed to efficiently coordinate and control these distributed devices for optimal grid operations. While some studies have explored efficiency and economic models, there remains a gap in ensuring reliability under everyday operations and resilience during extreme conditions. Addressing this gap, this project develops the technology for an Energy Service Interface (ESI) that includes novel pricing, control, learning, and distributed optimization algorithms, which will enable utilities to recruit EGoT assets for crucial grid services such as load flexibility, voltage regulation, and situation-awareness. The key novelty of the proposed technology is the careful distribution of learning and control functions across utility and EGoT asset owners such that provably efficient and resilient grid operations are attained while respecting communication and information-exchange constraints. Specifically, the project team develops machine-learning enhanced load modeling methods to allow EGoT asset owners to learn their load capability and flexibility, and develops pricing-based and decentralized learning-based control so that asset owners can coordinate to meet system-wide demand-supply balance and reliability goals. For extreme situations involving high-impact, low-probability catastrophic events (termed the “black-sky” events), the team also develops (1) a “Feeder-Operating Center-on-a-Laptop” (FOCAL) software that can assist utility personnel in leveraging EGoT assets to accelerate the service recovery of damaged feeders, and (2) distributed optimization algorithms that can coordinate the operation points of EGoT devices under severe communication constraints. The proposed technology has been extensively tested and evaluated through simulations and on a testbed. In summary, as we transition into a more interconnected and digital power grid era, our project’s findings and developments offer a pivotal step toward guaranteeing both efficiency and resilience in the face of both everyday operations and rare “black-sky” events.

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An Analysis of Post Attack Impacts and Effects of Learning Parameters on Vulnerability Assessment of Power Grid

Due to the increasing number of heterogeneous devices connected to electric power grid, the attack surface increases the threat actors. Game theory and machine learning are being used to study the power system failures caused by external manipulation. Most of existing works in the literature focus on one-shot process of attacks and fail to show the dynamic evolution of the defense strategy. In this paper, we focus on an adversarial multistage sequential game between the adversaries of the smart electric power transmission and distribution system. We study the impact of exploration rate and convergence of the attack strategies (sequences of action that creates large scale blackout based on the system capacity) based on the reinforcement learning approach. We also illustrate how the learned attack actions disrupt the normal operation of the grid by creating transmission line outages, bus voltage violations, and generation loss. This simulation studies are conducted on IEEE 9 and 39 bus systems. The results show the improvement of the defense strategy through the learning process. The results also prove the feasibility of the learned attack actions by replicating the disturbances created in simulated power system.

attack impacts↗

Assessment and Commissioning of Electrical Substation Grid Testbed with a Real-Time Simulator and Protective Relays/Power Meters in the Loop

Electrical utility substations are wired with intelligent electronic devices (IEDs), such as protective relays, power meters, and communication switches. Substation engineers commission these IEDs to assess the appropriate measurements for monitoring, control, power system protection, and communication applications. Like real electrical utility substations, complex electrical substation grid testbeds (ESGTs) need to be assessed for measuring current and voltage signals in monitoring, power system protection, control (synchro check), and communication applications that are limited by small measurement percentage errors. In the process of setting an ESGT with real-time simulators and IEDs in the loop, protective relays, power meters, and communication devices must be commissioned before running experiments. In this study, an ESGT with IEDs and distributed ledger technology was developed. The ESGT with a real-time simulator and IEDs in the loop was satisfactorily assessed and commissioned. The commissioning and problem-solving tasks of the testbed are described to define a method with flowcharts to assess possible trouble-shooting in ESGTs. This method was based on comparing the simulations versus IED measurements for the phase current and voltage magnitudes, three-phase phasor diagrams, breaker states, protective relay times with selectivity coordination at electrical faults, communication data points, and time-stamp sources.

Piesciorovsky, Emilio↗

Electrifying education: Exploring the electrification potential of U.S. School bus fleets

We analyze the operations of 270 diesel school buses across the United States to assess their electrification potential and evaluate the impact of various charging strategies on electricity demand. We find that school buses typically follow a two-route schedule on weekdays, featuring extended dwell times between morning and evening trips. Weekday trip distances average 25 miles, while weekend trips average 42 miles. Charging simulations indicate over 90% of the U.S. school bus fleet could be electrified using current technologies (300-mile range at 1.21 kWh/mile with 19.2-kW depot charging) without modifying existing operating patterns. Depot charging is a key enabler of school bus electrification, however, the strategic placement of charging stations at other locations (e.g., schools) can further increase electrification potential. Additionally, we find electric school bus charging to be highly flexible, with charge management capable of reducing peak charging loads at depots by up to 77%.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Use Case-Informed Framework for Utility Cloud Migration

This white paper presents a comprehensive methodology for assessing utilities’ cloud postures and frameworks. It aims to produce a roadmap and strategy for a cloud-enabled grid future, providing guidance for integrators, asset owners, and operators. Instead of offering a yes or no answer for cloud implementation, this framework offers strategic guidance on responsibly preparing for and deploying cloud solutions. This paper delves into cloud-service models pertinent to the electric sector, dissecting the shared responsibility model and elucidating what on-premise infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) entail. A pivotal consideration within the context of the shared responsibility model is the allocation of responsibility for foundational security aspects—a decision that will be informed by a comprehensive risk assessment. The ensuing discussion will present a checklist of certifications necessary for a secure cloud transition, equipping utilities with the knowledge to navigate this digital transformation with confidence and with a strategic roadmap. Furthermore, the paper outlines gaps in understanding the U.S. government’s role in shaping technology development and responsible use. Its purpose is to aid decision-making by offering support for risk-informed solutions that benefit those managing assets and operating in the cloud environment. The primary objective is to enhance the resilience and future readiness of a decarbonized electric grid, with cloud solutions as one viable option. The paper synthesizes information on current and future grid architectures and applications, considering both conservative and progressive energy transitions, along with scalable and distributed computing considerations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

ARIES / Flatirons Facility - Hydrogen System Capability Buildout

Under the "Advanced Research on Integrated Energy Systems" (ARIES) initiative, hydrogen system capabilities including a MW-scale electrolyzer, storage system, and MW-scale fuel cell generator will be designed and commissioned at NREL's Flatirons Campus. This hydrogen infrastructure will support H2@Scale goals by enabling integrated systems R&D to study the science of scaling for hydrogen energy systems.The system is designed with flexibility to provide a testbed to demonstrate systems integration, grid services, energy storage, direct renewable hydrogen production, and innovative end use applications (e.g. HD transportation, natural gas blending, etc.).

electrical grid↗

Topology Optimization of 3D Flow Fields for Flow Batteries

We report as power generated from renewables becomes more readily available, the need for power-efficient energy storage devices, such as redox flow batteries, becomes critical for successful integration of renewables into the electrical grid. An important aspect of a redox flow battery is the planar flow field, which is usually composed of two-dimensional channels etched into a backing plate. As reactant-laden electrolyte flows into the flow battery, the channels in the flow field distribute the fluid throughout the reactive porous electrode. We utilize topology optimization to design flow fields with full three-dimensional geometry variation, i.e., 3D flow fields. Specifically, we focus on vanadium redox flow batteries and use the optimization algorithm to generate 3D flow fields evolved from standard interdigitated flow fields by minimizing the electrical and flow pressure power losses. To understand how these 3D designs improve performance, we analyze the polarization of the reactant concentration and exchange current within the electrode to highlight how the designed flow fields mitigate the presence of electrode dead zones. While interdigitated flow fields can be heuristically engineered to yield high performance by tuning channel and land dimensions, such a process can be laborious; this work provides a framework for automating that design process.

25 ENERGY STORAGE↗

Oscillation Risks of Grid-Following and Grid-Forming Inverter-Based Resources in Series-Compensated Networks

Here, this paper investigates the dynamic behavior of a grid-connected inverter-based resource (IBR) when connected radially to a series compensated line. Potential interactions between the series compensation and the IBR have been identified for both types: grid-following (GFL) or grid-forming (GFM). The study begins with electromagnetic transient (EMT) simulations to demonstrate stability issues. Subsequently, nonlinear analytical models are formulated in the dq frame, validated against the EMT simulation, and leveraged to assess eigenvalues and participation factors. Influencing factors of the dominant oscillation modes have been identified. The analysis results show that series compensation may make a mode associated with the synchronization unit unstable. Furthermore, customized feedback systems are built for the synchronizing loop. Series compensation can increase the sensitivity of the voltage phase angle towards the synchronizing angle, and introduce phase lag in the real power response towards the synchronizing angle. These factors may cause interactions with the phase-locked loop in GFL-IBR systems and with power-based synchronization in GFM-IBR systems, potentially leading to instability.

24 POWER TRANSMISSION AND DISTRIBUTION↗