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At least 145 records · Page 8

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DOE OSTI2021

Rubik’s Cube Topology Based Particle Swarm Algorithm for Bilevel Building Energy Transaction

Following the rapid growth of distributed energy resources (e.g. renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as, reducing power loss, stabilizing the main power grid, etc. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. In addition, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush-Kuhn-Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubiks Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubiks Cube topology based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology based PSO and its scalability on larger scale applications.

Feng, Xiaochun↗

DOE OSTI2021

Multi-sensor agent devices

Apparatus, methods, and systems implementing multi-sensor agent devices are described herein. The agent devices can each include a plurality of sensors for measuring parameters of interest to an entity such as an electric power utility. The sensors can be organized in individually-IP-addressable sensor clusters, with each sensor cluster including an associated microcontroller. The agent devices can be controlled by a control center of the entity to operate in a coordinated manner, such as to gather and transmit data regarding parameters of interest. The agent devices can be transported to desired areas for data collection by unmanned aerial systems such as drones, and the collected data can be stored in a distributed blockchain ledger.

Fuhr, Peter L.↗

DOE OSTI2025

Resilient Operation of Networked Community Microgrids with High Solar Penetration

This project, funded by the US Department of Energy’s Solar Energy Technologies Office (SETO), focused on the operation of microgrids as a coordinated network. The primary objective, which was successfully achieved, was to develop both control strategies and hardware solutions to support the resilient and efficient operation of networked microgrids with high solar penetration. The work was structured around the following four main tasks: • Development of distributed and scalable optimization algorithms for AC-coupled networked microgrids. • Design and implementation of a novel DC interconnection hardware to enable precise power exchange between microgrids. • Laboratory operational validation of the developed technologies using 480 V testbeds and commercially available hardware. • Field operational validation of the complete solution in Adjuntas, Puerto Rico, interconnecting two kW-scale, split-phase microgrids of Casa Pueblo’s microgrids. This project addressed multiple technical challenges across the domains of optimization, control, hardware interconnection, and protection. One of its key contributions was delivering tangible, real-world solutions for networking microgrids. In contrast to purely theoretical or simulation-based work, this project included full-scale hardware operational validation both in the lab and in the field. The work conducted as part of this project—in collaboration with the University of Puerto Rico; the University of Tennessee, Knoxville; the University of Central Florida; and Casa Pueblo—has advanced the state of the art in networked microgrids. Key contributions include the development of distributed control strategies, practical solutions for real-world implementation challenges, and the introduction of a novel DC interlink approach for microgrid interconnection. The project featured both laboratory and field validation using commercial off-the-shelf components. The field deployment successfully validated that a group of microgrids can operate in a coordinated manner, enabling precise power flow between systems and mutual support during extreme events. This project resulted in 15 journal publications and 15 conference papers; 5 graduate students and 15 undergraduate students were supported. The codes of distributed optimization and forecasting were made open-source through OSTI.gov for distributed optimization and forecasting. All the publications are available in the ORNL-hosted project landing page. The DC interlink with state-of-charge balancing control was operationally validated in Adjuntas by interconnecting two real-world, 240 V split-phase microgrids. To the best knowledge of the team, this represents the first operational validation of AC microgrids interconnected via DC-interlinks. As a culmination of this project, a follow-on grant was awarded to support the technology transfer of the distributed optimization framework to a commercial microgrid controller, Stellar Edge, developed by the California-based company New Sun Road.

14 SOLAR ENERGY↗

DOE OSTI2026

Evaluating the Impacts of Coordination for Cascaded Hydropower Plants on the Mid-Columbia

The Mid-Columbia region in the U.S. Pacific Northwest includes seven large, cascaded hydropower plants with a combined nameplate capacity of nearly 14 GW. These plants have several different operators, and there is currently limited coordination among the operators. We develop a detailed model of the Mid-Columbia system that captures both river flow constraints and power system operations. We then place this detailed model within a production cost model of a 2030 system of the Western Interconnection to evaluate how coordination of the Mid-Columbia hydropower plants might impact operations throughout the interconnection. We find that coordination of the Mid-Columbia plants leads to more generation from the Mid-Columbia plants and increased revenues for the Mid-Columbia operators. This benefit is achieved primarily through better utilization of the storage reservoirs and decreased spill through the cascade. We also evaluate the impacts of look-ahead on production costs and find that longer look-ahead values result in lower system-wide production costs.

13 HYDRO ENERGY↗

DOE OSTI2025

The absence of ray-effects in the discrete ordinate solution to the transport equation in spherical coordinates in multi-dimensions

The streaming operator of the transport equation is derived for spherical coordinates by starting from Newton’s second law for a free particle expressed in spherical coordinates. We shall show that the partial derivatives with respect to the velocity variables of the particle, which are absent in the Cartesian coordinate formulation of the transport equation, arise in the spherical coordinate formulation of the transport equation in response to the centrifugal force which prevents a free particle from ‘falling into the origin’ of the coordinate system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Evaluation of Aggregated EV Flexibility With TSO-DSO Coordination

Electric vehicles (EVs) are becoming a promising source of grid ancillary services due to the temporal and spatial charging flexibility, quick response and storage capability. Such advantages are increasing with government policy promotion and technology improvement. However, the exploration of EV flexibility requires the coordination of both transmission system operators (TSOs) and distribution system operators (DSOs), to ensure the safe and reliable operation of power network. In this paper, we propose a coordinated evaluation method that determines the optimal utilization of EV temporal flexibility without compromising EV owners’ usage. At the distribution level, DSOs first evaluate EV aggregators’ operational boundaries to exploit distribution level services. At the transmission level, TSOs then determine EV charging schedules and ancillary service capacity simultaneously, taking into account the requirement from DSOs. Here, we validate the model in a case study using the IEEE 123 node test feeder and EV charging sessions obtained from a transportation simulation tool that uses real-world data.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Real-Time Regional PV Spinning Reserve Estimator with AGC Look-Ahead Windows

Curtailed PV generation is a zero-marginal cost spinning reserve that can be used for a number of active power control services. However, unlike the traditional spinning reserve providers, i.e., fossil-fueled generators, who have well-defined operating characteristics, e.g., available headroom or potential high limit (PHL), PV plants have by nature variable and uncertain operating characteristics. To ensure the effective coordination between PV plants and the system operator during an active power control event, accurate forecasts of the PV PHL are essential. A novel reference-control grouping based scaling method has been proposed by NREL to estimate the PV PHL in real-time. This work further enhances the methodology by: 1) improving the model accuracy through machine learning; 2) considering look-ahead windows introduced by the computation and communication latencies; 3) applying the method to regional spinning reserve estimation. A significant performance improvement, over 99% of estimation error reduction, has been observed based on real-world data collected by CAISO and PV plant operators.

potential high limit↗

DOE OSTI2024

Regional Real-Time PV Spinning Reserve Estimator

Curtailed photovoltaic (PV) generation is a zero-marginal-cost spinning reserve that can be used for a number of active power control services. Unlike traditional spinning reserve providers, however, i.e., fossil-fueled generators, which have well-defined operating characteristics, e.g., available headroom or potential high limit (PHL), PV plants have by nature variable and uncertain operating characteristics. To ensure the effective coordination between PV plants and the system operator during an active power control event, accurate knowledge of the PV PHL is essential. It ensures that enough headroom is reserved by the PV plants to deliver the award services in real time and informs feasible dispatch decisions made by the market operator. To tackle this challenge, a novel reference-control grouping-based PV plant reserve estimation method has been proposed by the National Renewable Energy Laboratory under past projects funded by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office. The estimation method separates inverters within a plant into two groups: a control group and a reference group. While the reference group is reserved to operate at its PHL, the control group can be curtailed to provide the grid services. Real-time outputs from the reference inverters are used to estimate the PHL for the whole plant based on the ratio between capacities of the reference group and of the plant. This work further enhances the methodology by (1) improving the model accuracy through machine learning; (2) automating the reference inverter selection through correlation analysis; (3) considering estimation look-ahead windows; and (4) applying to regional spinning reserve estimation. Significant performance improvement has been observed based on real-world data collected by CAISO, Southern Company, and Terabase Energy. Compared with the original scaling method, the newly proposed machine learning-based approach reduces the estimation errors by 30% and 13% at the plant level and region level, respectively. Results obtained from this project are intended to be used by grid operators, market operators, balancing authorities, and PV plant owners and operators to facilitate PV participation in ancillary service markets. Regulators, policymakers, and system planners can also consider the results of this work in their decision-making processes. In addition to the performance improvement on the existing reference-control based grouping method, we also investigated how the variability of PV generation from a single PV inverter can be used to represent the variability of PV generation at the plant level.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Real-Time Regional PV Spinning Reserve Estimator with AGC Look-Ahead Windows: Preprint

Curtailed PV generation is a zero-marginal cost spinning reserve that can be used for a number of active power control services. However, unlike the traditional spinning reserve providers, i.e., fossil-fueled generators, who have well-defined operating characteristics, e.g., available headroom or potential high limit (PHL), PV plants have by nature variable and uncertain operating characteristics. To ensure the effective coordination between PV plants and the system operator during an active power control event, accurate forecasts of the PV PHL are essential. A novel reference-control grouping based scaling method has been proposed by NREL to estimate the PV PHL in real-time. This work further enhances the methodology by: 1) improving the model accuracy through machine learning; 2) considering look-ahead windows introduced by the computation and communication latencies; 3) applying the method to regional spinning reserve estimation. A significant performance improvement, over 1.6% of estimation error reduction, has been observed based on real-world data collected by CAISO and PV plant operators.

potential high limit↗

DOE OSTI2026

A path to intelligent watersheds: coordinating the data to decision pipeline

Operations of multi-reservoir systems are challenged in-part by the interplay of complex physical processes functioning within the watershed. The employment of intelligent systems can be of aid by linking environmental sensing, information technology, data analytics, simulation and decision support to achieve a data-to-decision flow of information. A further challenge is that watershed resources are managed for multiple purposes requiring some level of coordination among numerous resource managers, asset operators and users. System intelligence in this context relies on shared community platforms (data portals, community models), and coordinated communication between decision makers. Opportunities to enrich watershed intelligence has been the subject of a roadmapping exercise for the Department of Energy’s Water Power Technologies Office which has relied on broad stakeholder engagement. Initial phases of engagement involved personal interviews and a series of virtual group meetings, which focused on identifying opportunities to improve the intelligence of the physical infrastructure within our watersheds—examples of feedback include improved sensing of snowpack and runoff, data standards for facilitated data sharing, and better forecasting tools. The latter phase of engagement involved the conduct of a case study in the Upper Colorado River basin where key stakeholders were interviewed to map how their decisions are informed by intelligence from other basin stakeholders. Our presentation will highlight the interdisciplinary flow of information in complex watershed systems and identify physical and institutional opportunities toward the strategic operation of water infrastructure.

Colorado River↗

DOE OSTI2020

Design of a Non-PLL Grid-Forming Inverter for Smooth Microgrid Transition Operation

This paper develops a controller for a grid-forming (GFM) inverter that is capable of operating as either a GFM or grid-feeding source that can improve the operation of a microgrid during on-off grid transitions through use of a novel synchronization approach. Furthermore, this controller avoids use of a phase-locked loop (PLL) and the inverter is able to synchronize with the grid with self-generated voltage and frequency. This prevents the inverter from replicating any grid voltage disturbances in its output—a key disadvantage of many grid-connected inverters that use a PLL. To enable fast synchronization, active synchronization control is adopted both during inverter start-up and microgrid reconnection operation and a method of coordinating synchronization of the inverter with a microgrid controller and grid interconnection circuit breaker is presented. Simulation results for multiple microgrid transition operations and unplanned islanding events demonstrate that the developed non-PLL grid-connected GFM inverter controller and synchronization method are effective in synchronizing the inverter and microgrid to the grid, avoiding phase jump during microgrid transition operation, and improving microgrid islanding transients versus a traditional configuration.

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2020

Conservation Voltage Reduction (CVR) via Two-Timescale Control in Unbalanced Power Distribution Systems

Voltage control devices are employed in power distribution systems to reduce the power consumption by operating the system closer to the lower acceptable voltage limits; this technique is called conservation voltage reduction (CVR). The different modes of operation for system’s legacy devices (with binary control) and new devices (e.g. smart inverters with continuous control) coupled with variable photovoltaic (PV) generation results in voltage fluctuations which makes it challenging to achieve CVR objective. This paper presents a two-timescale control of feeder’s voltage control devices to achieve CVR that includes (1)a centralized controller operating in a slower time-scale to coordinate voltage control devices across the feeder and (2) local controllers operating in a faster timescale to mitigate voltage fluctuations due to PV variability. The centralized controller utilizes a three-phase optimal power flow model to obtain the decision variables for both legacy devices and smart inverters. The local controllers operate smart inverters to minimize voltage fluctuations and restore nodal voltages to their reference values by adjusting the reactive power support. The proposed approach is validated using the IEEE-123 bus (medium-size) and R3-12.47-2 (large-size) feeders. It is demonstrated that the proposed approach is effective in achieving the CVR objective for unbalanced distribution systems.

optimal control, distributed generation, fluctuati↗

DOE OSTI2020

Power and Natural Gas Systems Interface Study

Power systems worldwide are becoming more reliant on energy from natural gas, wind, and solar, posing potential reliability and coordination challenges from the tighter coupling of these infrastructure systems. This paper proposes a framework for the market-based coordination of electricity and natural gas system operations. The proposed framework includes a power system model that accounts for flexibility in the commitment of power plants with short start-up and shut-down times, coupled with a dynamic gas model that simulates when gas cannot be delivered to generators. The capabilities of the framework are illustrated using real-world electric power and gas systems, including scenarios around wind and solar penetrations and the analysis of time-variant, “shaped flow” gas nominations. Our results indicate that coordination between power and gas systems improves total gas delivery and reduces out-of-merit order dispatch in the electricity system, and that shaped flows may reduce unserved gas in systems with high penetrations of wind and solar.

coordinated operation↗

DOE OSTI2022

Transmission-distribution long-term volt-var planning considering reactive power support capability of distributed PV

High penetration of grid-edge, inverter-based photovoltaic (PV) can cause significant voltage fluctuations not only at the distribution but also at the sub-transmission levels due to PV output intermittency. Traditional reactive power planning approaches do not consider intermittency, nor the possibility of coordinating the control of existing and future volt-ampere reactive resources. This paper proposes a reactive power planning tool for sub-transmission systems to mitigate voltage violations and fluctuations caused by high PV penetration and intermittency with a minimum investment cost. The planning tool coordinates with an optimization-based volt-var operational tool for: a) modeling the coordination of all existing var assets in both sub-transmission and distribution systems to reduce the need of new equipment, and b)selecting a set of scenarios with voltage violations, derived from PV intermittency c) testing the final investment decision. The tool obtains an investment need for each intermittency scenario with a proposed optimal power-flow framework with efficient techniques to handle a high number of discrete variables. Two options are provided for final planning decision: i) a conservative direct combination of investment need solutions and ii) a machine learning-based selection of representative investment needs at most time steps. The final investment decision options are verified using a realistic large-scale sub-transmission system and 5-minute PV and load data. The results show a significant voltage performance improvement with a lower investment cost for additional var equipment compared to conventional approaches.

14 SOLAR ENERGY↗

DOE OSTI2023

Citadels Final Report (GMLC 2.2.1: Citadels)

This is the final project report for the Grid Modernization Laboratory Consortium (GMLC) Resilient Distribution System (RDS) Citadels project. The primary goal of this GMLC project was to increase the operational flexibly of power systems by engaging microgrids distributedly, coordinated using consensus algorithms. The primary goal was successfully achieved. The primary goal was divided into three areas: Implement peer-to-peer control between microgrid controllers using the Open Field Message Bus (OpenFMB) approach; Develop and implement consensus algorithms on commercially available hardware that allows a group of microgrids to distributedly implement operational controls; Develop the architectures and controls to enable groups of microgrids to coordinate their operations to support the bulk power system during abnormal events, and end-use loads in the event the bulk power systems fail.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Universal Utility Data Exchange (UUDEX) – Security and Administration: Cybersecurity of Energy Delivery Systems (CEDS) Research and Development

A critical component of the Universal Utility Data Exchange (UUDEX) approach is the integrated security contained within its processing. This document describes how that security is designed and expected to be implemented by UUDEX Implementations (U-Implementations), including the UUDEX Server (U-Server) and UUDEX Clients (U-Clients). The UUDEX security hierarchy consists of three levels: 1. The UUDEX Instance (U-Instance) itself, which sits at the top of the hierarchy and contains the U-Server, the UUDEX Identity Authority (U-Identity Authority), and the UUDEX Administrator (U-Administrator) functions; 2. A group of one or more UUDEX Participants (U-Participants) that present “organizations” that participate in the U-Instance and contains the UUDEX Administrator Participant (U-U-Administrator Participant) function; 3. A group of one or more UUDEX Endpoints (U-Endpoints) that represent the individual UUDEX Publish Clients (U-Publish Client) responsible for supplying data to the U-Instance that is consumed by UUDEX Subscriber Clients (U-Subscriber Clients). U-Endpoints can be either autonomous devices that publish and subscribe data such as data exchange servers found in supervisory control and data acquisition and energy management systems, or they can be tied to users of applications that, for example, submit DOE OE-417 disturbance reports. U-Participants and U-Endpoints can be organized into UUDEX Groups (U-Groups). Any number of U-Participants or U-Endpoints can be members of a U-Group. A given U-Participant or U-Endpoint can be a member of multiple U-Groups, but a U-Group cannot contain other U-Groups. For example, a U-Group could be created to contain all U-Participant Transmission Operators within the purview of a Reliability Coordinator, and another U-Group could be created to contain all U-Participant Generator Operators within the purview of a Reliability Coordinator. U-Participants that are both Transmission Operators and Generator Operators would be members of both U-Groups. U-Participants, U-Endpoints, and U-Groups are used in the access control structures to provide access to individual UUDEX Subjects (U-Subjects). U-Groups are created by the U-Administrator and are managed by the U-Administrator or the designated U-Group Managers. U-Endpoints can be assigned UUDEX Roles (U-Roles) that can be used to further restrict access. U-Roles are assigned to individual U-Endpoints. For example, a U-Role of “Security Analyst” could be used to restrict which U-Endpoints can publish or subscribe security incident reports and vulnerability notifications, while a U-Role of “Transmission Planner” can be used to restrict which U-Endpoints can publish power system model updates. U-Role definitions are created by the U-Administrator, but the U-Roles are assigned to U-Endpoints by their respective UUDEX Participant Administrators (U-Participant Administrator). Because all information required to make security decisions is either included within the U-Endpoint’s X.509 digital certificate or stored in a datastore on the U-Server, all security decisions are performed and enforced within the U-Server. This reduces the complexity of the U-Client code and minimizes the chance for compromise of the integrity of the UUDEX security features.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Chapter Ten - Power, Buildings, and Other Critical Networks: Integrated Multisystem Operation

The electrifying transportation sector, the increasing grid interactivity of the built environment, the rapidly expanding number of devices within the Internet-of-Things, and the overall trend toward highly connected systems and interdependent networks is revolutionizing the operation of the electric power grid. While these changes are presenting grid operators with new challenges to ensure an efficient, reliable, and sustainable operation of the grid, they also enable a new suite of resources that can be utilized for assisting the grid in times of need. In this chapter, we explore how these recent changes and trends are affecting modern power systems and discuss the benefits and challenges of an increasingly electrified and interconnected world. We will observe how various critical infrastructure, that is, buildings, water and gas, transportation, and telecommunication networks are highly dependent on power network operations but, with improved coordination and control, can also provide valuable assets to the grid in times of need.

electricity markets↗

DOE OSTI2024

Transmission Operator Workflows for Real-Time Reliability Studies: A Review of Control Room Practices and Naturalistic Decision Making

This report provides an overview of real-time reliability study tools and their use by power system operators in the control room environment. After introducing some of the nuances of the control room environment and the differences in perspectives between power system engineers and operators, the roles and responsibilities of key entities involved in RTCA workflows are introduced. These are specifically the transmission system operator (TOP) and reliability coordinator (RC), which are required to run tools such as real-time contingency analysis (RTCA) as part of a real-time reliability assessment every 30 minutes, as dictated by a series of standards issued by the North American Electric Reliability Corporation (NERC). The process by which power systems operators operate the grid is discussed in terms of naturalistic decision making (NDM) and the recognition-primed decision-making (RPD) model. This cognitive model describe how experts working in high-risk, high-stress environments make safety-critical decisions under uncertainty and time pressure. For power system operators, the mental simulations involved in the traditional RPD model are supplemented by physics-based simulations using numerical tools, such as RTCA, to improve situational awareness and effectiveness of control actions. Next, a generic workflow is introduced to describe operator decision making for running RTCA tools and responding to system violations on a pre-contingent basis. The types of analysis performed and control actions chosen by power system operators are described in detail. The overall high-level workflow is then expanded in subsequent sections, with special attention given to high-voltage violations, low-voltage violations, and thermal overloads. Each type of violation is described in detail, with explanations of common causes, impacts on equipment and customers, and mitigation strategies. An additional workflow diagram is provided for each type of violation.

24 POWER TRANSMISSION AND DISTRIBUTION↗