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DOE OSTI2021

Evaluation of Centralized Model-Based FLISR in a Lab Setup: Preprint

Utilities are installing advanced distribution management systems (ADMS) around the globe to improve the sensing and control of distribution systems. ADMS is becoming a critical component to improve the resiliency and reliability of distribution systems. These management systems host a multitude of applications that can be used to sense, control, and operate distribution systems. Fault location, isolation, and service restoration (FLISR) is one of the ADMS applications that is critical to improving resilience during fault conditions. FLISR applications use smart, controllable devices that are installed in the distribution system for FLISR operation. These controllable devices include distributed energy resources (DER) and reclosers. Evaluating such ADMS applications before installation in the field can help de-risk the field implementation and avoid costly failures in the field. This paper presents a background on experimental setup that are typically used to evaluate ADMS applications. This is followed by briefly presenting the setup used to evaluate the FLISR application in an off-the-shelf ADMS tool. Finally, results from the evaluation experiments are presented.

94 GMLC - Grid Modernization Laboratory Consortium↗

DOE OSTI2018

Combining Simulation and Emulation Systems for Smart Grid Planning and Evaluation

Software-defined networking (SDN) enables efficient network management. As the technology matures, utilities are looking to integrate those benefits to their operations technology (OT) networks. To help the community to better understand and evaluate the effects of such integration, we develop DSSnet, a testing platform that combines a power distribution system simulator and an SDN-based network emulator for smart grid planning and evaluation. DSSnet relies on a container-based virtual time system to achieve efficient synchronization between the simulation and emulation systems. To enhance the system scalability and usability, we extend DSSnet to support a distributed controller environment. To enhance system fidelity, we extend the virtual time system to support kernel-based switches. In conclusion, we also evaluate the system performance of DSSnet and demonstrate the usability of DSSnet with a resilient demand response application case study.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Cost benefit analysis for smart grid projects

The U.S. is unusual in that a definition of the term “smart grid” was written into legislation, appearing in the Energy Independence and Security Act (2007). When the recession called for stimulus spending and the American Recovery and Reinvestment Act (ARRA, 2009) was passed, a framework already existed for identification of smart grid projects. About $4.5B of the U.S. Department of Energy’s (U.S. DOE’s) $37B allocation from ARRA was directed to smart grid projects of two types, investment grants and demonstrations. Matching funds from other sources more than doubled the total value of ARRA-funded smart grid projects. The Smart Grid Investment Grant Program (SGIG) consumed all but $620M of the ARRA funds, which was available for the 32 projects in the Smart Grid Demonstration Program (SGDP, or demonstrations). Given the economic potential of these projects and the substantial investments required, there was keen interest in estimating the benefits of the projects (i.e., quantifying and monetizing the performance of smart grid technologies). Common method development and application, data collection, and analysis to calculate and publicize the benefits were central objectives of the program. For this purpose standard methods and a software tool, the Smart Grid Computational Tool (SGCT), were developed by U.S. DOE and a spreadsheet model was made freely available to grantees and other analysts. The methodology was intended to define smart grid technologies or assets, the mechanisms by which they generate functions, their impacts and, ultimately, their benefits. The SGCT and its application to the Demonstration Projects are described, and actual projects in Southern California and in China are selected to test and illustrate the tool. The usefulness of the methodology and tool for international analyses is then assessed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

Model-driven Privacy Assessment in the Smart Grid

In a smart grid, data and information are transported, transmitted, stored, and processed with various stakeholders having to cooperate effectively. Furthermore, personal data is the key to many smart grid applications and therefore privacy impacts have to be taken into account. For an effective smart grid, well integrated solutions are crucial and for achieving a high degree of customer acceptance, privacy should already be considered at design time of the system. To assist system engineers in early design phase, frameworks for the automated privacy evaluation of use cases are important. For evaluation, use cases for services and software architectures need to be formally captured in a standardized and commonly understood manner. In order to ensure this common understanding for all kinds of stakeholders, reference models have recently been developed. In this paper we present a model-driven approach for the automated assessment of such services and software architectures in the smart grid that builds on the standardized reference models. The focus of qualitative and quantitative evaluation is on privacy. For evaluation, the framework draws on use cases from the University of Southern California microgrid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2015

Increasing the resilience and security of the United States' power infrastructure

The United States' power infrastructure is aging, underfunded, and vulnerable to cyber attack. Emerging smart grid technologies may take some of the burden off of existing systems and make the grid as a whole more efficient, reliable, and secure. The Pacific Northwest National Laboratory (PNNL) is funding research into several aspects of smart grid technology and grid security, creating a software simulation tool that will allow researchers to test power infrastructure control and distribution paradigms by utilizing different smart grid technologies to determine how the grid and these technologies react under different circumstances. Understanding how these systems behave in real-world conditions will lead to new ways to make our power infrastructure more resilient and secure. Demonstrating security in embedded systems is another research area PNNL is tackling. Many of the systems controlling the U.S. critical infrastructure, such as the power grid, lack integrated security and the aging networks protecting them are becoming easier to attack.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Evaluation of Centralized Model Based FLISR in a Lab Setup

94 GMLC - Grid Modernization Laboratory Consortium↗

DOE OSTI2011

An Informatics Approach to Demand Response Optimization in Smart Grids

Power utilities are increasingly rolling out “smart” grids with the ability to track consumer power usage in near real-time using smart meters that enable bidirectional communication. However, the true value of smart grids is unlocked only when the veritable explosion of data that will become available is ingested, processed, analyzed and translated into meaningful decisions. These include the ability to forecast electricity demand, respond to peak load events, and improve sustainable use of energy by consumers, and are made possible by energy informatics. Information and software system techniques for a smarter power grid include pattern mining and machine learning over complex events and integrated semantic information, distributed stream processing for low latency response,Cloud platforms for scalable operations and privacy policies to mitigate information leakage in an information rich environment. Such an informatics approach is being used in the DoE sponsored Los Angeles Smart Grid Demonstration Project, and the resulting software architecture will lead to an agile and adaptive Los Angeles Smart Grid.

Simmhan, Yogesh↗

DOE OSTI2022

Moving Target Defense Routing for SDN-enabled Smart Grid

The increasing attack surface area in the smart grid communication networks is making the grid more susceptible to cyber attacks that can lead to instability of the grid and even blackouts. While there are multiple types of cyber attacks that can impact the grid, Denial of Service (DoS) attacks are relatively easier to inject as they require lesser knowledge about the system as compared to data integrity attacks. Various research works showcase methods to prevent or mitigate the impacts of DoS attacks in the smart grid but the research still lacks in demonstrating the feasibility and efficacy of the solutions in a real-world environment. In this paper, we propose a Moving Target Defense (MTD)-enabled Software Defined Network (SDN) for the Smart Grid communication implemented on a Hardwarein- the-Loop (HIL) Testbed. We showcase the implementation of the proposed architecture of MTD-enabled SDN using Mininet 2.3.0 which enables communication between the physical grid and the control center. The results show the advantages of using MTD based on SDN for the wide-area network (WAN) with much lower packet drop percentages in the case of MTD-based routing in the SDN WAN. Index Terms—SDN,

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

CEEP (Cyber-Energy Emulation Platform) [SWR-20-102]

NREL's Cyber-Energy Emulation Platform (CEEP) provides the capability to realize cyber-energy security and resilience through automation and orchestration of virtualized systems and software defined networks for the electric grid. CEEP enables testing and validation of grid-security and -control methodologies as the grid evolves to include smart technologies/systems, such as virtualization and containerization of grid components, software defined networking, simulation and co-simulation frameworks, and hardware in the loop. CEEP is a modular system that can be distributed and deployed across different hardware infrastructure sizes and network architectures. For example, CEEP can visualize, emulate, and/or coordinate the Smart-Grid Network Visualization, Intrusion Detection, and Network Healing system. Using CEEP, intrusion-detection and network-self-healing solutions can be deployed at grid control centers, within secure private clouds, and in cyber-energy appliances.

Vaughan, Evan↗

DOE OSTI2022

Cyber Energy Emulation Platform (CEEP) [SWR-20-102]

Rivera, Joshua↗

DOE OSTI2013

Maturity Model for Advancing Smart Grid Interoperability

Abstract—Interoperability is about the properties of devices and systems to connect and work properly. Advancing interoperability eases integration and maintenance of the resulting interconnection. This leads to faster integration, lower labor and component costs, predictability of projects and the resulting performance, and evolutionary paths for upgrade. When specifications are shared and standardized, competition and novel solutions can bring new value streams to the community of stakeholders involved. Advancing interoperability involves reaching agreement for how things join at their interfaces. The quality of the agreements and the alignment of parties involved in the agreement present challenges that are best met with process improvement techniques. The GridWise® Architecture Council (GWAC) sponsored by the United States Department of Energy is supporting an effort to use concepts from capability maturity models used in the software industry to advance interoperability of smart grid technology. An interoperability maturity model has been drafted and experience is being gained through trials on various types of projects and community efforts. This paper describes the value and objectives of maturity models, the nature of the interoperability maturity model and how it compares with other maturity models, and experiences gained with its use.

IEEE↗

DOE OSTI2014

Synchronization Algorithms for Co-Simulation of Power Grid and Communication Networks

The ongoing modernization of power grids consists of integrating them with communication networks in order to achieve robust and resilient control of grid operations. To understand the operation of the new smart grid, one approach is to use simulation software. Unfortunately, current power grid simulators at best utilize inadequate approximations to simulate communication networks, if at all. Cooperative simulation of specialized power grid and communication network simulators promises to more accurately reproduce the interactions of real smart grid deployments. However, co-simulation is a challenging problem. A co-simulation must manage the exchange of informa- tion, including the synchronization of simulator clocks, between all simulators while maintaining adequate computational perfor- mance. This paper describes two new conservative algorithms for reducing the overhead of time synchronization, namely Active Set Conservative and Reactive Conservative. We provide a detailed analysis of their performance characteristics with respect to the current state of the art including both conservative and optimistic synchronization algorithms. In addition, we provide guidelines for selecting the appropriate synchronization algorithm based on the requirements of the co-simulation. The newly proposed algorithms are shown to achieve as much as 14% and 63% im- provement, respectively, over the existing conservative algorithm.

co-simulation↗

DOE OSTI2013

Communication Simulations for Power System Applications

New smart grid technologies and concepts, such as dynamic pricing, demand response, dynamic state estimation, and wide area monitoring, protection, and control, are expected to require considerable communication resources. As the cost of retrofit can be high, future power grids will require the integration of high-speed, secure connections with legacy communication systems, while still providing adequate system control and security. While considerable work has been performed to create co-simulators for the power domain with load models and market operations, limited work has been performed in integrating communications directly into a power domain solver. The simulation of communication and power systems will become more important as the two systems become more inter-related. This paper will discuss ongoing work at Pacific Northwest National Laboratory to create a flexible, high-speed power and communication system co-simulator for smart grid applications. The framework for the software will be described, including architecture considerations for modular, high performance computing and large-scale scalability (serialization, load balancing, partitioning, cross-platform support, etc.). The current simulator supports the ns-3 (telecommunications) and GridLAB-D (distribution systems) simulators. Ongoing and future work will be described, including planned future expansions for a traditional transmission solver. A test case using the co-simulator, utilizing a transactive demand response system created for the Olympic Peninsula and AEP gridSMART demonstrations, requiring two-way communication between distributed and centralized market devices, will be used to demonstrate the value and intended purpose of the co-simulation environment.

co-simulation↗

DOE OSTI2011

Designing power system simulators for the smart grid: combining controls, communications, and electro-mechanical dynamics

Open source software has a leading role in research on simulation technology for electrical power systems. Research simulators demonstrate new features for which there is nascent but growing demand not yet provided for by commercial simulators. Of particular interest is the inclusion of models of software-intensive and communication-intensive controls in simulations of power system transients. This paper describes two features of the ORNL power system simulator that help it meet this need. First is its use of discrete event simulation for all aspects of the model: control, communication, and electro-mechanical dynamics. Second is an interoperability interface that enables the ORNL power system simulator to be integrated with existing, discrete event simulators of digital communication systems. The paper concludes with a brief discussion of how these aspects of the ORNL power system simulator might be inserted into production-grade simulation tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Software Development: A Tool for Smart Integration of Solar Power (Final Report)

As part of its SunShot funded Grid Assessor work Kevala assembled a team with deep electricity market, solar, software and product expertise to address a significant problem - reducing the risk of investing in solar by determining the inherent value of solar electricity based on the location where it is produced. Kevala’s Grid Assessor product is now in the market transforming the way solar assets are proposed, assessed, and financed, resulting in lower capital costs, the opening of new markets, and the streamlining of siting in the utility scale portion of the solar industry. Grid assessor accomplishes this by using detailed electricity infrastructure data, pricing information, GIS mapping, and proprietary algorithms to lower financial risk by providing transparency into the current and future value of projects based on their location.

14 SOLAR ENERGY↗

DOE OSTI2020

IEEE 1547-2018 Based Interoperable PV Inverter with Advanced Grid-Support Functions

Grid integration of photovoltaic (PV) inverters has been increasing in the past decade. As a result of the uncertainties introduced with high penetrations of PV, better monitoring and control of the PV inverters becomes crucial for improving overall system stability. This paper focuses on the communications capability of the inverter controller and on enabling interoperability. Multiple standards are available to enable interoperability in PV inverters. In this paper, an interoperable controller, enabled by Distributed Network Protocol 3 (DNP3) communications protocols, is developed for a grid-connected, three-phase PV inverter. The DNP3 server for the PV inverter is programmed on the real-time layer of the field-programmable gate array (FPGA)-based inverter controller. Set points for advanced inverter control functions, such as volt/VAr curves, ride-through curves, are sent from a DNP3 client, a simulated distribution management system application, to the PV inverter through DNP3. This communications capability of the inverter controller is validated using a controller-hardware-in-the-loop experimental setup. The code developed to achieve the interoperability is available in the public domain through open-source software licensing. This interoperability will enable smoother grid integration of smart PV inverters with advanced grid-support functions as well as allow better monitoring and control of PV inverters for grid stability.

14 SOLAR ENERGY↗

DOE OSTI2020

Accurate Consensus-based Distributed Averaging with Variable Time Delay in Support of Distributed Secondary Control Algorithms

We report that distributed secondary control has been widely used in hierarchical control structures, where multiple distributed generators (DGs) need to coordinate to regulate system voltage and frequency. In these systems, consensus algorithms determine the average of a group of dynamic states (e.g. voltages measured by a group of DGs). To be useful, consensus algorithms must be computationally efficient, stable and accurate. In practice, numerous practical implementation challenges significantly affect the consensus equilibrium. In this paper, we quantify the accuracy deviations of the distributed average observer algorithms proposed in the literature to demonstrate the problems with the state-of-the-art distributed averaging techniques. A novel approach is proposed that achieves accurate average tracking in the presence of time-varying communication delays among agents. In our implementation, time synchronization of all distributed controllers is enabled by a novel software platform, called Resilient Information Architecture Platform for the Smart Grid (RIAPS). The proposed distributed average observer is implemented on hardware controllers and its effectiveness is validated in a controller hardware-in-the-loop testbed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2014

PNNL Future Power Grid Initiative-developed GridOPTICS Software System (GOSS)

The power grid is changing and evolving. One aspect of this change is the growing use of smart meters and other devices, which are producing large volumes of useful data. However, in many cases, the data can’t be translated quickly into actionable guidance to improve grid performance. There's a need for innovative tools. The GridOPTICS(TM) Software System, or GOSS, developed through PNNL's Future Power Grid Initiative, is open source and became publicly available in spring 2014. The value of this middleware is that it easily integrates grid applications with sources of data and facilitates communication between them. Such a capability provides a foundation for developing a range of applications to improve grid management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗