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Grid Modernization Energy Storage and the Role of Power Electronics.
Abstract not provided.
ESIF 2016: Modernizing Our Grid and Energy System
This 2016 annual report highlights work conducted at the Energy Systems Integration Facility (ESIF) in FY 2016, including grid modernization, high-performance computing and visualization, and INTEGRATE projects.
Models and methods for assessing the value of HVDC and MVDC technologies in modern power grids
This report reflects the results of U.S. Department of Energy’s (DOE) Grid Modernization project 0074 “Models and methods for assessing the value of HVDC [high-voltage direct current] and MTDC [multi-terminal direct current] technologies in modern power grids.” The work was done by the Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory (ORNL) in cooperation with Mid-Continent Independent System Operator (MISO) and Siemens. The main motivation of this study was to show the benefit of using direct current (DC) systems larger than those in existence today as they overlap with the alternating current (AC) systems. Proper use of their flexibility in terms of active/reactive power control and fast response can provide much-needed services to the grid at the same time as moving large blocks of energy to take advantage of cost diversity. Ultimately, the project’s success will enable decision-makers and investors to make well-informed decisions regarding this use of DC systems. This project showed the technical feasibility of HVDC macrogrid for frequency control and congestion relief in addition to bulk power transfers. Industry-established models for commonly used technologies were employed, along with high-fidelity models for recently developed HVDC converter technologies; like the modular multilevel converters (MMCs), a voltage source converters (VSC). Models for General Electric Positive Sequence Load Flow (GE PSLF) and Siemens Power System Simulator (PSS/E), widely used analysis programs, were for the first time adapted to include at the same time both Western Electricity Coordinating Council (WECC) and Eastern Interconnection (EI), the two largest North American interconnections. The high-fidelity models and their control were developed in detail for MMC system and extended to HVDC systems in point-to-point and in three-node multi-terminal configurations. Using a continental-level mixed AC-DC grid model, and using a HVDC macrogrid power flow and transient stability model, the results showed that the HVDC macrogrid relieved congestion and mitigated loop flows in AC networks, and provided up to 24% improvement in frequency responses. These are realistic studies, based on the 2025 heavy summer and EI multi-regional modeling working group (MMWG) 2026 summer peak cases. This work developed high-fidelity models and simulation algorithms to understand the dynamics of MMC. The developed models and simulation algorithms are up to 25 times faster than the existing algorithms. Models and control algorithms for high-fidelity models were designed and tested for point-to-point and multi-terminal configurations. The multi-terminal configuration was tested connecting simplified models of EI, WI, and Electric Reliability Council of Texas (ERCOT). The developed models showed up to 45% improvement in frequency response with the connection of all the three asynchronous interconnections in the United States using fast and advanced DC technologies like the multi-terminal MMC-DC system. Future work will look into developing high-fidelity models of other advanced DC technologies, combining high-fidelity models with the continental-level model, incorporating additional services. More scenarios involving large-scale HVDC and MTDC will be evaluated.
Durability, Reliability and Safety of Energy Storage Systems
For grid modernization, energy storage systems play a critical role in reliability. There are many technical issues and barriers that need to be addressed to redefine the reliability issues in modern grid system integration with renewable and distributed energy resources. This presentation is to disseminate some existing reliability issues in the energy storage systems to paint a bigger picture of what needs to be addressed. This presentation is intended to define these issues before we strive for a solution.
Modernizing Distribution System Restoration to Achieve Grid Resiliency Against Extreme Weather Events: An Integrated Solution
Recent severe power outages caused by extreme weather hazards have highlighted the importance and urgency of improving the resilience of the electric power grid. As the distribution grids still remain vulnerable to natural disasters, the power industry has focused on methods of restoring distribution systems after disasters in an effective and quick manner. The current distribution system restoration practice for utilities is mainly based on predetermined priorities and tends to be inefficient and suboptimal, and the lack of situational awareness after the hazard significantly delays the restoration process. As a result, customers may experience an extended blackout, which causes large economic loss. On the other hand, the emerging advanced devices and technologies enabled through grid modernization efforts have the potential to improve the distribution system restoration strategy. However, utilizing these resources to aid the utilities in better distribution system restoration decision-making in response to extreme weather events is a challenging task. Therefore, this paper proposes an integrated solution: a distribution system restoration decision support tool designed by leveraging resources developed for grid modernization. We first review the current distribution restoration practice and discuss why it is inadequate in response to extreme weather events. Then we describe how the grid modernization efforts could benefit distribution system restoration, and we propose an integrated solution in the form of a decision support tool to achieve the goal. The advantages of the solution include improving situational awareness of the system damage status and facilitating survivability for customers. The paper provides a comprehensive review of how the existing methodologies in the literature could be leveraged to achieve the key advantages. The benefits of the developed system restoration decision support tool include the optimal and efficient allocation of repair crews and resources, the expediting of the restoration process, and the reduction of outage durations for customers, in response to severe blackouts due to extreme weather hazards.
A hybrid architecture for volt-var control in active distribution grids
Modern active distribution grids are characterized by the increasing penetration of distributed energy resources (DERs). The proper coordination and scheduling of a large numbers of these small-scale and spatially distributed DERs is necessary, and warrants the use of novel distributed approaches. In this paper, we propose a hybrid volt-var control architecture for the distribution grid, which leverages existing centralized and local approaches to planning, decision making, and control, and augments it with distributed optimization and distributed control for DER management. First, we propose a convex model to describe the power physics of distribution grids of meshed topology and unbalanced structure, based on current injection and McCormick Envelopes. Second, we employ the distributed proximal atomic coordination (PAC) algorithm to coordinate DERs to provide voltage support. We implement volt-var optimization by optimally coordinating DERs including PV smart inverters and demand response. We present results using the IEEE-34 bus network, using real data from a distribution feeder in Hawaii, to model load and PV generation. Different levels of DER penetration and objective functions are simulated. Finally, our results show the need for the coordination of DERs to improve voltage profiles, even in networks with existing voltage control devices. Further, we show the need for flexible reactive power capabilities to achieve desired grid performance.
Impact of cyber attacks on distributed compressive sensing based state estimation in power distribution grids
Modern power distribution grids suffer from multiple vulnerabilities due to the tight integration between the physical system and the cyber infrastructure. Sophisticated and malicious cyber attacks continue to adversely impact the grid operation leading to performance degradation, service interruption, and grid failure. State estimation plays an essential role in grid monitoring and advancing cyber-attack situational awareness. In this regard, this paper first proposes a distributed compressive sensing (CS) state estimation approach for an unobservable distribution grid. Further, the proposed distributed CS approach divides the distribution grid into sub-areas to perform local state estimation. Then an alternating direction method of multipliers (ADMM) based iterative information exchange among neighboring areas is employed to complete the estimation process. In this estimation process, the impact of loss of measurement data, false data injection (FDI), replay, and neighborhood cyber-attacks is analyzed. Extensive simulations are performed on the IEEE 37-bus and IEEE 123-bus standard networks to demonstrate the algorithm’s robustness to the aforementioned cyber-attacks. A quantitative analysis of computational complexity and simulation time of the distributed CS based approach is also presented.
Exploratory analysis of high-resolution power interruption data reveals spatial and temporal heterogeneity in electric grid reliability
Modern grid monitoring equipment enables utilities to collect detailed records of power interruptions. Here, these data are aggregated to compute publicly reported metrics describing high-level characteristics of grid performance. The current work explores the depth of insights that can be gained from public data, and the implications of losing visibility into heterogeneity in grid performance through aggregation. We present an exploratory analysis examining three years of high-resolution power interruption data collected by archiving information posted in real-time on the public-facing website of a utility in the Western United States. We report on the size, frequency and duration of individual power interruptions, and on spatio-temporal variability in aggregate reliability metrics. Our results show that metrics of grid performance can vary spatially and temporally by orders of magnitude, revealing heterogeneity that is not evidenced in publicly reported metrics. We show that limited access to granular information presents a substantive barrier to conducting detailed policy analysis, and discuss how more widespread data access could help to answer questions that remain unanswered in the literature to date. Lastly, given open questions about whether grid performance is adequate to support societal needs, we recommend establishing pathways to make high-resolution power interruption data available to support policy research.
Time Synchronization Techniques in the Modern Smart Grid: A Comprehensive Survey
In modern smart grids, accurate and synchronized time signals are essential for effective monitoring, protection, and control. Various time synchronization methods exist, each tailored to specific application needs. Widely adopted solutions, such as GPS, however, are vulnerable to challenges such as signal loss and cyber-attacks, underscoring the need for reliable backup or supplementary solutions. This paper examines the timing requirements across different power grid applications and provides a comprehensive review of available time synchronization mechanisms. Through a comparative analysis of timing methods based on accuracy, flexibility, reliability, and security, this study offers insights to guide the selection of optimal solutions for seamless grid integration.
Impacts of Using Distributed Energy Resources to Reduce Peak Loads in Vermont
To help the United States develop a modern electricity grid that provides reliable power from multiple resources as well as resiliency under extreme conditions, the U.S. Department of Energy (DOE) is leading the Grid Modernization Initiative (GMI) to help shape the future of the nation's grid. Under the GMI, DOE funded the Vermont Regional Initiative project to provide the technical support and analysis to utilities that need to mitigate possible impacts of increasing renewable generation required by statewide goals. Advanced control of distributed energy resources (DER) can both support higher penetrations of renewable energy by balancing controllable loads to wind and photovoltaic (PV) solar generation and reduce peak demand by shedding noncritical loads. This work focuses on the latter. This document reports on an experiment that evaluated and quantified the potential benefits and impacts of reducing the peak load through demand response (DR) using centrally controllable electric water heaters (EWHs) and batteries on two Green Mountain Power (GMP) feeders. The experiment simulated various hypothetical scenarios that varied the number of controllable EWHs, the amount of distributed PV systems, and the number of distributed residential batteries. The control schemes were designed with several objectives. For the first objective, the primary simulations focused on reducing the load during the independent system operator (ISO) peak when capacity charges were the primary concern. The second objective was to mitigate DR rebound to avoid new peak loads and high ramp rates. The final objective was to minimize customers' discomfort, which is defined by the lack of hot water when it is needed. We performed the simulations using the National Renewable Energy Laboratory's (NREL's) Integrated Energy System Model (IESM) because it can simulate both electric power distribution feeder and appliance end use performance and it includes the ability to simulate multiple control strategies.
Distributed Generation Cost-Benefit and Ratemaking Considerations for Idaho
This memo was completed through the Grid Modernization Laboratory Consortium (GMLC), a strategic partnership between the U.S. Department of Energy (DOE) and the national laboratories to bring together leading experts, technologies, and resources to collaborate on the goal of modernizing the nation’s grid. The GMLC was established as part of the DOE Grid Modernization Initiative to accelerate the development of technology, modeling analysis, tools, and frameworks to help enable grid modernization. Special thanks to DOE project leads, Larry Mansueti and Elaine Ulrich, and the laboratory project lead for this effort, Peter Cappers from Lawrence Berkeley National Laboratory (LBNL). The Idaho Public Utility Commission (IPUC) Staff requested this technical assistance to improve their understanding of the emerging, complex, and consequential issues around distributed energy resource (DER) rate design to help the staff achieve its goal of making a fair, just, and reasonable rate design recommendation with respect to Order 34147 under Case No. IPC-E-17-13. 2 PNNL-28285 In Case No. IPC-E-17-13, Idaho Power requested authorization from the IPUC to establish new rate schedules for residential and small general service customers with on-site generation. The IPUC’s Order No. 34046 of May 9, 2018 authorized Idaho Power to (IPUC 2018a): Close Schedule 84 and create Schedule 6 for residential on-site generators and Schedule 8 for small general service on-site generators; Acknowledge smart inverter technology; Make proposed revisions to interconnection Schedule 72; Open an Idaho Power-specific docket to “to comprehensively study the costs and benefits of on-site generation on Idaho Power’s system, as well as proper rates and rate design, transitional rates, and related issues of compensation for net excess energy provided as a resource” to Idaho Power; File a study with the IPUC “exploring fixed-cost recovery in basic charges and other rate design options prior to its next general rate case.”
2014 Modern Power Grid Video
A video from NETL that describes the details of a modern power grid and how it can help our nation save on energy costs.
Semantic Information Modeling for Emerging Applications in Smart Grid
Smart Grid modernizes power grid by integrating digital and information technologies. Millions of smart meters, intelligent appliances and communication infrastructures are under deployment allowing advanced IT applications to be developed to secure and manage power grid operations. Demand response (DR) is one such emerging application to optimize electricity demand by curtailing/shifting power load when peak load occurs. Existing DR approaches are mostly based on static plans such as pricing policies and load shedding schedules. However, improvements to power management applications rely on data emanating from existing and new information sources with the growth of Smart Grid information space. In particular, dynamic DR algorithms depend on information from smart meters that report interval-based power consumption measurement, HVAC systems that monitor buildings heat and humidity, and even weather forecast services. In order for emerging Smart Grid applications to take advantage of the diverse data influx, extensible information integration is required. In this paper, we develop an integrated Smart Grid information model using Semantic Web techniques and present case studies of using semantic information for dynamic DR. We show the semantic model facilitates information integration and knowledge representation for developing the next generation Smart Grid applications.