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At least 505 records · Page 28

Architecture for Quantum-in-the Loop Real-Time Simulations for Designing Resilient Smart Grids

With the power grid growing more complex every day with the inclusion of new sensors and regulatory approvals that enable end-users and small local developers to participate in the grid, it is becoming challenging for conventional smart grid simulation, emulation, and testing technologies to keep up. In this work, we propose that quantum-encoded real-time simulations can be helpful under the new paradigm and operational circumstances to solve optimization problems for power grids. By leveraging the principles of quantum mechanics, the proposed quantum-in-loop (QIL) framework will enable better and faster optimization solutions based on real-world, real-time data streams, facilitating the real-time planning and operations of electrical grids that rely on millions of distributed sensors and controllers. Furthermore, QIL will allow researchers and engineers to assist utilities in designing, developing, and de-risking algorithms to optimize power grid operation and resilience by considering inputs from millions of grid-connected devices. QIL framework is being developed to have a self-limiting triage mechanism, which will help engineers and practitioners identify fundamental physical limits on quantum processors, revealing what quantum algorithms can and cannot do in utility-specific use cases and must continue to count on classical high-performance computing infrastructure.

digital real-time simulation↗

Simplified Transactive Distribution Grids for Bulk Power System Mechanism Development

As distributed energy resources and smart devices become omnipresent in the electrical power grid, transactive energy control mechanisms are evolving. From real-time to day-ahead markets, these transactive energy algorithms involve more and more agents, whose behavior is going to affect the transmission and generation network. In order to study the interaction between the wholesale and retail energy markets, extensive co-simulations are performed. To be able to redesign, evaluate, and verify new control algorithms, the simulations need to provide results in a fast and reliable manner. This work has built and tested a transactive distribution grid model, the DSO-Stub, meant to offer a configurable distribution retail market while ensuring the computational burden is not significantly increased.

Transactive Energy, , Distribution System Operator↗

A method to identify weak points of interconnection of renewable energy resources

The increasing penetration of renewable energy resources (RERs) is challenging power grid planning and operation in maintaining grid reliability. Potential power grid reliability and stability issues may arise when large-scale RERs are connected to a weak power grid. These issues may become more significant due to the mutual interactions among RERs that are interconnected electrically close through a power network. Weakness analysis based on grid strength assessment is useful for identifying the potential weak grid issues. However, when taking into account the impact of the interactions among RERs, the weakness analysis becomes computationally challenging. Different combinations of points of interconnections (POIs) of RERs may have different impacts on grid strength at each POI. Due to the combination nature, such weakness analysis may be time-consuming when identifying the weakest combination of POIs from a large number of potential candidates in realistic power grids. To address this concern, the impact of the power network structure on grid strength is analyzed in this paper. It is found that the impact mainly depends on the impedance ratios at POIs. The findings can be summarized as two criteria to develop a recursive method for fast identification of the weakest combination in this paper. The efficacy of the proposed method is demonstrated through case studies on the IEEE 39-bus system and a realistic power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Dynamically reconfigurable photovoltaic system

A PV system composed of sub-arrays, each having a group of PV cells that are electrically connected to each other. A power management circuit for each sub-array has a communications interface and serves to connect or disconnect the sub-array to a programmable power grid. The power grid has bus rows and bus columns. A bus management circuit is positioned at a respective junction of a bus column and a bus row and is programmable through its communication interface to connect or disconnect a power path in the grid. As a result, selected sub-arrays are connected by selected power paths to be in parallel so as to produce a low system voltage, and, alternately in series so as to produce a high system voltage that is greater than the low voltage by at least a factor of ten.

14 SOLAR ENERGY↗

Dynamically reconfigurable photovoltaic system

A PV system composed of sub-arrays, each having a group of PV cells that are electrically connected to each other. A power management circuit for each sub-array has a communications interface and serves to connect or disconnect the sub-array to a programmable power grid. The power grid has bus rows and bus columns. A bus management circuit is positioned at a respective junction of a bus column and a bus row and is programmable through its communication interface to connect or disconnect a power path in the grid. As a result, selected sub-arrays are connected by selected power paths to be in parallel so as to produce a low system voltage, and, alternately in series so as to produce a high system voltage that is greater than the low voltage by at least a factor of ten.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electric Grid Supply Chain Review: Large Power Transformers and High Voltage Direct Current Systems

The report “America’s Strategy to Secure the Supply Chain for a Robust Clean Energy Transition” lays out the challenges and opportunities faced by the United States in the energy supply chain as well as the federal government plans to address these challenges and opportunities. It is accompanied by several issue-specific deep dive assessments, including this one, in response to Executive Order 14017 “America’s Supply Chains,” which directs the Secretary of Energy to submit a report on supply chains for the energy sector industrial base. The Executive Order is helping the federal government to build more secure and diverse U.S. supply chains, including energy supply chains. The need to modernize and increase the capacity of the U.S. power grid is increasing due to growing population, aging infrastructure, grid resilience requirements, operational flexibility needs, and a growing portfolio of renewable energy. As part of the Paris Climate Agreement the United States has committed to reducing its net greenhouse gas emissions by 50 to 52 percent below 2005 levels in 2030 and has set a goal of 100 percent carbon pollution free electricity by 2035 (The United States of America Nationally Determined Contribution, 2021). Meeting these targets will require a significant expansion of the power system to integrate a large amount of new renewable resources (United States Department of State & United States Executive Office of the President, 2021). However, many critical components supporting the power grid have limited to no domestic manufacturing capacity and face complex challenges in supporting a rapid expansion of the grid to meet multiple objectives, including decarbonization goals. This report focuses on two key grid components: large power transformers (LPTs) and high-voltage direct current (HVDC) transmission.

24 POWER TRANSMISSION AND DISTRIBUTION↗

System and method for islanding detection and prevention in distributed generation

A method for detecting and preventing islanding includes issuing a command to an inverter connected to a power source, where the inverter is coupled to a power grid and supplies power to the power grid, the command causes a frequency of a waveform output by the inverter to vary, and the frequency of the waveform output by the inverter is a command frequency, determining that a amount of change of the command frequency is a constant value for a predetermined amount of time, removing the power supplied by the inverter from the power grid, and determining whether the power grid is valid.

Bhowmik, Shibashis↗

A Guide to Current Limiting and Stability with Grid-Forming Inverters

The electric power grid is changing. For many decades, the synchronous generator - an electromechanical device invented in 1887 - has been the workhorse and backbone of power grids across the globe. Our entire infrastructure is built around it. But times change, and so does the power grid. Since the early 21st century, we have seen a gradual shift in modern power grids away from synchronous generators to ones dominated by power electronic inverter-based resources (IBRs). Sources such as photovoltaics, wind turbines, battery storage, fuel cells, and other technologies like high-voltage DC transmission interconnections all rely on an inverter to connect and interface with the grid. They are increasingly being installed on the grid to augment, or even replace, traditional energy sources. This change is a fundamental shift that brings tremendous technical challenges and questions: Can a power grid remain stable with many more inverter-based resources? How do we avoid more blackouts on the grid? How do we keep the grid secure and resilient during disturbances? After all, power electronic inverters are nothing like the big, rotating, iron-and-copper machines that the grid heavily relies on. Many of these questions can be answered by using grid-forming (GFM) inverters, yet many research challenges remain. This document explores GFM inverters and how they can help stabilize the future grid, especially during disturbances and contingencies. It summarizes a two-year research and development fellowship program at NREL. We point interested readers to more detailed works developed during the project along the way. Let's dive in

24 POWER TRANSMISSION AND DISTRIBUTION↗

High-Performance Computing for Advanced Smart Grid Applications

The power grid is becoming far more complex as a result of the grid evolution meeting an information revolution. Due to the penetration of smart grid technologies, the grid is evolving as an unprecedented speed and the information infrastructure is fundamentally improved with a large number of smart meters and sensors that produce several orders of magnitude larger amounts of data. How to pull data in, perform analysis, and put information out in a real-time manner is a fundamental challenge in smart grid operation and planning. The future power grid requires high performance computing to be one of the foundational technologies in developing the algorithms and tools for the significantly increased complexity. New techniques and computational capabilities are required to meet the demands for higher reliability and better asset utilization, including advanced algorithms and computing hardware for large-scale modeling, simulation, and analysis. This chapter summarizes the computational challenges in smart grid and the need for high performance computing, and present examples of how high performance computing might be used for future smart grid operation and planning.

computational challenges↗

Experiences from Field Testing for Black Start of a Run-of-the-river Hydropower Plant in Idaho Falls Power Distribution Grid

Idaho Falls Power (IFP) utility has local generation portfolio comprising of 56.3MVA of run-of-the-river (ROR) hydropower that can serve typically 25%-30% of the total load demand. The remaining load is served by importing power from Bonneville Power Administration through two Pacificorp transmission interconnections. In case of emergencies (power disruption or directed load reduction), the capability to island from transmission grid and stably serve critical loads in the IFP distribution grid can be a huge advantage. In this direction, the capability to black start with ROR is an essential requirement, and a challenge due to limited dispatchability and requires re-tuning of hydro-governor and excitation system controls. This paper presents the field experience from the testing done for black start of 8.9 MW ROR hydro plant in the IFP distribution grid using an adjustable load bank in December 2017. The lessons from the successful black start testing is presented along with test results to establish the potential value and requirements to develop black start capability with a ROR hydro plant.

13 HYDRO ENERGY↗

Understanding the Grid

The electric power grid has been rightly celebrated as the single most important engineering feat of the 20th century. The grid powers our homes, offices, hospitals, and schools; and, increasingly, it powers our favorite devices from smartphones to HDTVs. With those and other modern innovations and challenges, our grid will need to evolve. Grid modernization efforts will help the grid make full use of today’s advanced technologies and serve our needs in the 21st century. While the vast majority of upgrades are implemented by private sector energy companies that own and operate the grid, DOE has been investing in technologies that are revolutionizing the way we generate, store and transmit power.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Survey on Social Media to Enhance the Cyber-PhysicalSocial Resilience of Smart Grid

Smart sensor that enables power grid resiliency at distribution network is a very expensive solution and its implementation has been very sluggish. Social media has great potential to become an alternate abstract information channel that can replace/reinforce smart sensor capabilities towards a more resilient power grid. In this paper, we present a survey on the progress of utilizing social media as a platform to extract and analyse abstract data to produce intelligent information. This information can be utilized to plan and implement resources towards power grid resiliency from micro level (consumers) to macro level (cities/states). This paper discusses the reliability of social sensors, various concepts relating to social media and their implementation to solve problems, and how we can develop a framework based on the social media towards a resilient power grid. The realization of social media framework for information will benefit as robust communication and control channels that can be used together with prediction models to improve the accuracy and effectiveness of system operators' decision-making.

DISASTER RESPONSE, HASHTAGS, POWER GRID RESILIENCE↗

Wide-area, real-time monitoring and visualization system

A real-time performance monitoring system for monitoring an electric power grid. The electric power grid has a plurality of grid portions, each grid portion corresponding to one of a plurality of control areas. The real-time performance monitoring system includes a monitor computer for monitoring at least one of reliability metrics, generation metrics, transmission metrics, suppliers metrics, grid infrastructure security metrics, and markets metrics for the electric power grid. The data for metrics being monitored by the monitor computer are stored in a data base, and a visualization of the metrics is displayed on at least one display computer having a monitor. The at least one display computer in one said control area enables an operator to monitor the grid portion corresponding to a different said control area.

24 POWER TRANSMISSION AND DISTRIBUTION↗

GridOPTICS Software System

GridOPTICS Software System (GOSS) is a middleware that facilitates creation of new, modular and flexible operational and planning platforms that can meet the challenges of the next generation power grid. GOSS enables Department of Energy, power system utilities, and vendors to build better tools faster. GOSS makes it possible to integrate Future Power Grid Initiative software products/prototypes into existing power grid software systems, including the PNNL PowerNet and EIOC environments. GOSS is designed to allow power grid applications developed for different underlying software platforms installed in different utilities to communicate with ease. This can be done in compliance with existing security and data sharing policies between the utilities. GOSS not only supports one-to-one data transfer between applications, but also publisher/subscriber scheme. To support interoperability requirements of future EMS, GOSS is designed for CIM compliance. In addition to this, it supports authentication and authorization capabilities to protect the system from cyber threats. In summary, the contributions of the GOSS middleware are as follows: A platform to support future EMS development. A middleware that promotes interoperability between power grid applications. A distributed architecture that separates data sources from power grid applications. Support for data exchange with either one-to-one or publisher/subscriber interfaces. An authentication and authorization scheme for limiting the access to data between utilities.

Akyol, BoraA↗

GridOPTICS Software System

GridOPTICS Software System (GOSS) is a middleware that facilitates creation of new, modular and flexible operational and planning platforms that can meet the challenges of the next generation power grid. GOSS enables Department of Energy, power system utilities, and vendors to build better tools faster. GOSS makes it possible to integrate Future Power Grid Initiative software products/prototypes into existing power grid software systems, including the PNNL PowerNet and EIOC environments. GOSS is designed to allow power grid applications developed for different underlying software platforms installed in different utilities to communicate with ease. This can be done in compliance with existing security and data sharing policies between the utilities. GOSS not only supports one-to-one data transfer between applications, but also publisher/subscriber scheme. To support interoperability requirements of future EMS, GOSS is designed for CIM compliance. In addition to this, it supports authentication and authorization capabilities to protect the system from cyber threats. In summary, the contributions of the GOSS middleware are as follows: A platform to support future EMS development. A middleware that promotes interoperability between power grid applications. A distributed architecture that separates data sources from power grid applications. Support for data exchange with either one-to-one or publisher/subscriber interfaces. An authentication and authorization scheme for limiting the access to data between utilities.

Akyol, Bora A↗

Mitigating Voltage Instability in the Saudi Grid for a Decarbonized, Fully Solar Power System

Lately, solar photovoltaic (PV) has received significant interest due to its economic and environmental benefits. As the integration of renewable energy sources (RES) increases into existing power grids, challenges such as the decrease in short circuit ratio (SCR) are introduced. Here, this paper investigates a case study of the Saudi power grid, examining the voltage stability as the grid transitions from traditional power generation to 100% penetration of solar PV gradually. Moreover, the paper explores the relationship between the increase in solar penetration and the potential effects on the short circuit MVA (SCMVA), which could significantly impact the overall SCR of the system. To meet the North American Electric Reliability Corporation (NERC) recommendation of maintaining SCR at a particular level, synchronous condensers (SC)s were integrated into the grid. The effectiveness of utilizing SCs to maintain the system voltage at optimal levels in a fully solar grid is also considered. In addition, this paper covers the weak grid analysis via utilizing the Newton-Raphson load flow method, along with PV and QV curve analyses. The purpose behind that is to determine weak bus locations in need of voltage improvements, and to meet the amount of reactive power to be injected. Finally, the amount of power being delivered by SCs will be added progressively in three scenarios to show the enhancements on SCR more precisely.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Trilevel Model for Segmentation of the Power Transmission Grid Cyber Network

Network segmentation of a power grid's communication system can make the grid more resilient to cyberattacks. Here we develop a novel trilevel programming model to optimally segment a grid communication system, taking into account the actions of an information technology (IT) administrator, attacker, and grid operator. The IT administrator is allowed to segment existing networks, and the attacker is given a budget to inflict damage on the grid by attacking the segmented communication system. Finally, the grid operator can redispatch the grid after the attack to minimize damage. The resulting problem is a trilevel interdiction problem that we solve using a branch and bound algorithm for bilevel problems. We demonstrate the benefits of optimal network segmentation through case studies on the 9-bus Western System Coordinating Council (WSCC) system and the 30-bus IEEE system. These examples illustrate that network segmentation can significantly reduce the threat posed by a cyberattacker.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Analyzing Residential Charging Demand for Light-Duty Electric Vehicles in Colorado

The past decade has witnessed a remarkable surge in adoption of electric vehicles (EVs). The momentum is expected to continue with strong support from governments and industry. Rapid EV adoption will add significant electricity demand, making it critical to plan for and manage EV charging to avoid causing additional stress and non-negligible risks to the already-aging power grid. To help power grid operators understand the impacts of residential EV charging and identify risk factors, this study presents a data-driven charging demand analysis for light-duty vehicles. This study considers two real-world grid service regions in Colorado and merges multiple data sources and state-of-the-art tools that characterize EV adoption projections, vehicle travel patterns, seasonal variations, residential charging accessibility, ambient temperature impact, EV charging behaviors, grid utility customers, vehicle registration, and household-level EV charging demand distribution. We characterize potential residential charging demand in 2030 for two regions within the state of Colorado: Boulder and Aurora regions. We project that EVs will be 26% of the light-duty vehicle population in Boulder and 16% in Aurora areas. Charging demand is characterized for ten power grid feeders (five for each study region). Across the ten feeders, peak total EV charging powers during wintertime range from less than 1 MW to more than 4 MW.

ADVANCED PROPULSION SYSTEMS↗