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At least 667 records · Page 37

Utility-Scale Operational Consequences for Solar Grid Services

This report delves into the critical aspects of grid services provided by solar inverter-based resources (IBRs), with an emphasis on the evolving landscape of microgrids, virtual power plants (VPPs), aggregators, and distributed energy resource management systems (DERMS). As the energy sector undergoes a transformative shift towards more decentralized and resilient grid architectures, understanding the multifaceted risks associated with these technologies becomes paramount. The report categorizes these risks into organizational, technical, and procedural domains, providing a thorough risk assessment framework that stakeholders can utilize to anticipate and mitigate potential issues. In addressing the increasing complexity of grid interconnections, the report highlights the importance of Cyber-Informed Engineering (CIE). By embedding engineering controls and cybersecurity measures into the early stages of system design, this approach aims to fortify grid infrastructure against emerging cyber threats. The analysis includes an exploration of best practices and strategies for integrating CIE principles to enhance grid security and resilience. To provide practical insights, the report conducts a detailed consequence analysis of various grid services and cyber mitigations that can be applied through the interconnection process. This analysis evaluates the potential impacts of different failure modes and vulnerabilities, offering a clear understanding of the consequences that could arise from disruptions within the energy grid. The findings are further enriched by a series of case studies that illustrate real-world scenarios and lessons learned from past incidents. Through this comprehensive examination of grid services and their criticality, the report aims to prepare industry professionals with the knowledge and tools necessary to navigate the complexities of modern energy systems. By providing a comprehensive approach that includes risk assessment, cybersecurity, and consequence analysis, solar stakeholders can more effectively guarantee the reliability, efficiency, and security of the energy grid.

14 SOLAR ENERGY↗

Real-time evaluation of cybersecurity threats to DER inverter grid-support functions

In this project we aim to contribute to the understanding of the type and severity of potential cybersecurity attacks to the grid-support functionalities of DER systems interconnected to the AC distribution grid via inverters. Our preliminary work focused on developing a small-scale testbed allowing to study cybersecurity threats to an isolated photovoltaic-battery system using a real-time simulator (Typhoon HIL602+) with a real DNP3 communication connection over TCP/IP, allowing for safe and efficient monitoring and manipulation of data traffic between the simulated hardware and supervisory control and data acquisition (SCADA) system. In this project we propose to expand upon this development by utilizing a) a recently acquired NovaCor RTDS (Real Rime digital Simulator) to emulate the DER-inverter-grid topology including main grid-support functions as defined by IEEE Std. 1547-2018, and b) an industrial control and automation device to enable realistic evaluation of control functions and utilization of communication protocols for real-time data transmission.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Data Collection and Analysis Challenges and Mitigation Strategies for Quantitative Human Factors Research Studies in Nuclear Power Plant Modernization

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program Plant Modernization Pathway is conducting targeted research and development (R&D) to address aging and reliability concerns with the legacy instrumentation and control and related information systems of the U.S. LWR fleet. In this effort, the application of human factors engineering (HFE) provides an important role in ensuring new digital plant technologies enable broad innovation and business improvement with continued operational safety. Evaluation is a key activity in HFE, which often occurs iteratively through the system design lifecycle. While qualitative methods are important in collecting information of how users perform tasks through observations, quantitative methods are equally important in assessing system design based on performance. In collecting and analyzing this quantitative data, there are notable challenges in the nuclear HFE domain that may threaten the validity and reliability of the inferences made in these studies. Notable challenges include small sample size and limited resources, large error variance and small effect size, an “adding test features to losing degrees of freedom” dilemma, non-normal distribution, and heterogeneity of variance. The results in control room usability studies are often statistically non-significant, which makes it hard to interpret. This work discusses these challenges across different scientific viewpoints and provides real-world examples of these challenges in practice. Collectively, the objective of this work is to position these challenges to the larger data science community as a means of identifying future opportunities to address these issues.

99 GENERAL AND MISCELLANEOUS↗

Integration Study of Converter-Interfaced Combined Heat and Power Plants

Combined Heat and Power (CHP) systems, as a proven technology, provide numerous benefits to the plant owner by saving electricity bill, reducing carbon dioxide emissions, and improving electricity service reliability. However, their integration into the distribution grid faces many barriers including the complexity of grid code requirements and the lack of technical expertise in commercial and small industrial plants to interface with the utility and accelerate the interconnection process. To solve these issues, this study proposes a converter-interfaced solution for CHP integration. Simulations including various fault scenarios and load flow under different grid conditions are carried out to compare technical performances of the proposed solution with directly-coupled CHP. Results show that the generator size of converter-interfaced CHP can be reduced by approximately 25% and it also provides advantageous features such as reduced stress level under fault conditions and a better dynamic stability margin. In addition, a power factor controller is designed and reactive power from CHP is dispatched in such a way that the CHP plant is compliant with power factor requirements from utilities under all operating conditions.

Converter, Combined heat and power, Distributed en↗

Transactive HVAC Agent - Design and Performance Evaluation

Transactive energy systems are playing an increasingly important role in the efficient and reliable marketbased operation of the power grid. Since a significant portion of the residential building energy consumption is from heating ventilation and air conditioning (HVAC) systems, HVAC is one of the most promising resources to provide load flexibility. However, utilizing HVAC flexibility to provide various grid services while simultaneously maintaining consumer comfort and cost-reductions is challenging. This paper presents a design of a transactive HVAC agent (T-HVAC) to be used as a supervisory control for the HVAC system that can simultaneously ensure comfort and cost-reduction. In particular, the T-HVAC a) estimates HVAC thermal dynamics, b) ensures optimal operations of the HVAC system, and c) participates into markets, and d) implements a market-based control via controlling the thermostat temperature set-point. The T-HVAC performance is demonstrated through multiple scenarios and illustrations.

Demand flexibility, distribution system, HVAC, Tra↗

Quantifying the Financial Impacts of Electric Vehicles on Utility Ratepayers and Shareholders [Slides]

Widespread electric vehicle (EV) adoption is critical for meeting economy-wide decarbonization goals and, as a result, states are considering enabling policies and rate designs to accelerate EV deployment. EVs can provide possible financial upside to electric utilities and ratepayers in several ways. For example, from the utility perspective, EVs could drive increased electricity sales and new earnings opportunities through increased capital investments. From the ratepayer perspective, increased electric loads from EVs could reduce average all-in retail rates. The degree to which there are net benefits or costs to shareholders and/or ratepayers depends on how EVs are integrated and managed through enabling grid investments and charging strategies. Using Berkeley Lab’s Financial Impacts of Distributed Energy Resources (FINDER) model that mimics the electric utility investment planning and ratemaking processes, we estimate the utility earnings and customer rate impacts of EVs using a bookend approach of “managed” (i.e., best case) and “mismanaged” (i.e., worst case) charging strategies for a generic summer-peaking, investor-owned, and vertically integrated utility. The analysis also examines the sensitivity of results to different assumptions of EV deployment characteristics, EV impacts on retail electricity sales, incremental distribution system costs, EV charging location, and utility EV enablement costs (i.e., utility costs to invest in EV charging, controls, and communication to deliver and administer EV programs). The results are intended to inform EV policies and deployment strategies that maximize utility system benefits and minimize ratepayer costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Demonstration of Power System Black Start with Hydropower Generator and Battery Energy Storage: Preprint

Battery energy storage systems (BESS) are an important asset for power systems with high integration levels of renewable energy, and they can be controlled to provide various services to the grid. This paper presents the hardware demonstration and characterization of using a utility-scale BESS with grid-following (GFL) and grid-forming (GFM) controls and a run-of-river (ROR) hydropower plant to perform a bottom-up power system black start that enhances power systems' resiliency. ROR hydropower plants are generally not used for power system restoration due to their frequency instability during islanded operation; however, BESS with droop control can provide critical damping to convert a ROR hydropower generator into a blackstart- capable unit. To demonstrate this, we carry out hardware experiments at the megawatt-scale integrating a synchronous generator driven by a dynamometer, an actual GFL/GFM BESS, a medium-voltage impedance network, and a load bank. The demonstration shows the different roles of BESS with GFL and GFM control in power system restoration. GFL BESS can suffer from high-frequency oscillations, even instability, depending on the droop control gain and loading condition. The results provide further insights for system operators on how GFL- or GFMcontrolled BESS can enhance grid stability and how hydro-BESS hybrids can operate as a black-start-capable unit. The presented experimental results are also a valuable resource to understand the different stability characteristics of real-world BESS with different control modes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A digital twin platform for building performance monitoring and optimization: Performance simulation and case studies

Advancements in sensor technology, data analytics, affordable compute, and communication infrastructure have paved the way for Digital Twin technology in optimizing building operations and controls. This study presents the development of an open and interoperable web-based Digital Twin platform for integrating diverse data streams and facilitating effective user interactions. The platform utilizes modern technologies for the web framework and time-series data management, ensuring scalability and responsiveness. The backend supports seamless integration of diverse data sources and emulators, incorporating data from building sensors and meters, external weather Application Programming Interfaces, and advanced EnergyPlus simulation models of the building and its energy systems including the Distributed Energy Resources that are formulated in Functional Mockup Units. A simulation case study was conducted with FlexLab, a test facility on Lawrence Berkeley National Laboratory campus. The case study includes normal operations, Distributed Energy Resource integration, and power outage scenarios, to illustrate the Digital Twin’s ability to provide critical insights into energy performance and thermal resilience. The results demonstrated the platform’s potential as a decision-support tool for optimizing building energy performance and enhancing resilience against extreme weather events. Future work will focus on deploying the Digital Twin platform to a real building for field validation, extending its capabilities to cover more scenarios such as bidirectional Electric Vehicle interactions, and enhancing user engagement.

EnergyPlus↗

Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation

Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.

adaptation models↗

A Graph-Net with Node Embeddings to Detect False Data Injection Attacks in Photovoltaic Systems

Distributed energy resources (DER) contribute to the operational stability of the larger power grid both at utility-scale as well as commercial and residential scales in aggregated forms. These DER in-turn are susceptible to increasing cyber threats. An adversary can plug into the same local network that a field photovoltaic (PV) system uses to interconnect its data loggers and inverters and manipulate certain measurements collected from the network or trick existing irradiance and inverter readings through false data injection attacks (FDIA). Control routines that rely on these measurements can propagate the false data, impacting critical decisions that result in a suboptimal operation or even cause intentional harm leading to inverter-tripping or unscheduled loads that need to be shed. To detect FDIA in PV systems, the paper introduces an attention-based graph neural network with node embeddings and applied it to a simple prototypical DC-coupled microgrid with PV, energy storage, and load. The algorithm shows a detection accuracy of up to 98.95%. The proposed FDIA detection technique will provide micro-grid operators with an effective method to safeguard their systems, guaranteeing the secure and reliable operation.

Parvez, Imtiaz [Utah Valley University]↗

A Relaxed PV Bus Model in Linear Power Flow

The emerging multimodal active energy resource units make it necessary to introduce constant voltage amplitude buses (PV bus) in the operation of modern distribution systems. To enable the analysis of PV bus using linear power flow models, this letter proposes a relaxed PV bus model for solving power flow related problems using an indirect modeling approach. The developed PV bus model can be applied to linear power flow models in both rectangular and polar coordinates. Besides, the approximation error of the relaxed PV bus model can also be controlled and quantified. Lastly, the proposed relaxed PV bus model is validated using different test systems. According to the numerical studies, the maximum error on the PV bus approximation in all case studies is only 0.61%, and the maximum error of the supporting power at the PV buses is 6.5%.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Enhancement of a global lake and reservoir database to aid climate studies and resource monitoring utilizing satellite radar altimetry

Here, we describe the expansion and enhancement of a large (surface area ≥100 sq. km) lake and reservoir database (1.GREALD). These efforts have also resulted in the spin-off of two additional databases, one containing lakes and reservoirs (2.GREALD, area 10–99 sq. km), and the other containing ephemeral lakes (3.GELD, area ≥100 sq. km). These databases are unique sources for projects that utilize satellite radar altimeter data to monitor surface water levels. While 1.GREALD aims to be a complete catalog, 2.GREALD focuses on reservoirs in response to applied sciences programs that monitor water and energy resources. The creation of 3.GELD has climate change objectives as well as water resources and ecosystem conservation applications. The recording of information pertaining to the potential overpasses (waterbody crossings) of the current and archive satellite altimeters is a primary objective as is the need to highlight any form of controlled water level variation. The permanent water databases now contain 6282 entries, half experience some form of anthropogenic influence and ∼430 have been identified as potential climatically sensitive terminal lakes. The revised integral surface area distribution is a power law with exponent −1.016. Statistics reveal that with altimetric repeat visit times of 10-day to monthly, at least 80% of the permanent water bodies (≥10 sq. km) have been overflown at some period since the 1990s. Current information on water use and reservoir formation date show that the primary use of the reservoir class is hydroelectric power, and that China, Brazil, India, Turkey, and Vietnam dominate the dam building in recent decades.

Charon M. Birkett↗

Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation: Preprint

Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.

distribution system operator↗

Quantum computing in power systems

Electric power systems provide the backbone of modern industrial societies. Enabling scalable grid analytics is the keystone to successfully operating large transmission and distribution systems. However, today's power systems are suffering from ever-increasing computational burdens in sustaining the expanding communities and deep integration of renewable energy resources, as well as managing huge volumes of data accordingly. These unprecedented challenges call for transformative analytics to support the resilient operations of power systems. Recently, the explosive growth of quantum computing techniques has ignited new hopes of revolutionizing power system computations. Quantum computing harnesses quantum mechanisms to solve traditionally intractable computational problems, which may lead to ultra-scalable and efficient power grid analytics. This paper reviews the newly emerging application of quantum computing techniques in power systems. We present a comprehensive overview of existing quantum-engineered power analytics from different operation perspectives, including static analysis, transient analysis, stochastic analysis, optimization, stability, and control. We thoroughly discuss the related quantum algorithms, their benefits and limitations, hardware implementations, and recommended practices. We also review the quantum networking techniques to ensure secure communication of power systems in the quantum era. Finally, we discuss challenges and future research directions. This paper will hopefully stimulate increasing attention to the development of quantum-engineered smart grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

AI-Based Optimal Design and Controls Can Greatly Reduce Carbon Emissions and Enhance Resilience in Residential Communities in Cold Climates

Net-zero energy residential communities are crucial for achieving decarbonization goals, but the high-penetration photovoltaic (PV) in those communities is posing challenges to the distribution grid. Traditional design and operation of net-zero communities rely on rule-of-thumb methods and may not work in complex scenarios. Artificial intelligence and machine learning methods can optimally size PV for net-zero energy, identify user preferences and usage patterns, and fully unlock the potential of distributed energy resources to address distribution grid issues.

artificial intelligence↗

Future energy infrastructure, energy platform and energy storage

Today fossil energy dominates energy consumption across the world. There has been an increasing momentum to reduce fossil energy consumption and increase renewable energy utilization to more than 70%. Such high penetrations of distributed renewable resources bring large uncertainty and complexity that cannot be easily handled by the current infrastructure. For the last two decades, telecommunication industry has gone through a similar transition from centralized to distributed systems, and more recently to platform approaches, which become the corner stone of today’s vibrant platform economy. Based on telecommunication history, we believe that a platform-based approach, called the energy platform, is a viable solution for addressing the renewable energy challenges. The energy platform consists of an array of computational algorithms, sensing and control technologies for key industry, energy generators and users to jointly manage and control the complex energy infrastructure. It includes the following key components: (1) the hardware and software to generate, store, control and transmit electricity/data (the energy cloud), (2) the digital platforms and tools for key energy producers, digital, service and communication industry to share the assets, participate in and manage the complex infrastructure, and for customers to participate in energy transactions, (3) the transaction platform for new service and business models. Additionally, the energy platform requires breakthroughs in large scale energy storage and many other areas including efficient power electronics, sensors and controls, new mathematical and computational tools, and deep integration of energy technologies and information sciences to control and stabilize such complex chaotic systems.

25 ENERGY STORAGE↗

Supply Chain Management in Cyber Grid Guard Framework

Grid modernization has impeded innovative power grid applications and energy resources that are increasingly distributed. Blockchain/distributed ledger technology (DLT) has the potential to enhance the resilience of the electric infrastructure, particularly in a decentralized and distributed environment. The benefits of blockchain are to ensure asset information and lifecycle events are secure and traceable and identify potential malicious modification of data. Oak Ridge National Laboratory (ORNL) has developed a framework, Cyber Grid Guard (CGG), incorporating blockchain. The system implements a low-energy, fast, and robust enhancement to system trustworthiness within and across electric grid systems, including substations, control centers, and metering infrastructures. Currently, one of the major concerns is supply chain attacks. There have been several recent attacks that have significantly impacted critical infrastructures and organizations around the world. This document focuses on how CGG can be used to address the supply chain issue.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Regulatory Protection and Control Standards Applicable to The Vietnam Grid Under High Inverter-Based Resource (IBR) Penetration: A Review of Standards Applicable for Vietnam Grid

This report provides a review of the current standards and practices followed by regulatory authorities for interconnection of inverter-based resources (IBR). With the increased penetration of IBRs into the transmission and distribution networks, the legacy protection methodologies are getting challenged. Due to the lack of regulations on IBR operations under a fault it is essential to have a thorough understanding of the present-day interconnection standards to ensure proper IBR operations. A focus is placed on the regulation and standards enforced by the North American Reliability Corporation (NERC), Federal Energy Regulatory Commission (FERC), Institute of Electrical and Electronics Engineer (IEEE), Underwriters Laboratories (UL) and other regulations proposed by the responsible commissions.

24 POWER TRANSMISSION AND DISTRIBUTION↗