Power grid simulation applications developed using the GridPACK™ high performance computing framework
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Jin, Shuangshuang↗
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Vehicle-to-grid Simulator
Vehicle-to-grid Simulation Platform (V2G-Sim) -- A recent activity at LBNL has begun to create a simulation platform to generate temporarily--and spatially--resolved predictions of grid impacts and opportunities from increased plug-in vehicle (PEV) deployment. Currently in the prototype stage, the V2G-Sim models for: a) driver behavior, b) automated generation of trip specific drive cycles (velocity-time profiles), c) vehicle powertrain models of energy usage during a trip, d) vehicle charging, and e) vehicle response to managed charging algorithms.
Saxena, Samveg↗
A Micro-Grid Simulator Tool (SGridSim) using Effective Node-to-Node Complex Impedance (EN2NCI) Models
This paper presents a micro-grid simulator tool useful for implementing and testing multi-agent controllers (SGridSim). As a common engineering practice it is important to have a tool that simplifies the modeling of the salient features of a desired system. In electric micro-grids, these salient features are the voltage and power distributions within the micro-grid. Current simplified electric power grid simulator tools such as PowerWorld, PowerSim, Gridlab, etc, model only the power distribution features of a desired micro-grid. Other power grid simulators such as Simulink, Modelica, etc, use detailed modeling to accommodate the voltage distribution features. This paper presents a SGridSim micro-grid simulator tool that simplifies the modeling of both the voltage and power distribution features in a desired micro-grid. The SGridSim tool accomplishes this simplified modeling by using Effective Node-to-Node Complex Impedance (EN2NCI) models of components that typically make-up a micro-grid. The term EN2NCI models means that the impedance based components of a micro-grid are modeled as single impedances tied between their respective voltage nodes on the micro-grid. Hence the benefit of the presented SGridSim tool are 1) simulation of a micro-grid is performed strictly in the complex-domain; 2) faster simulation of a micro-grid by avoiding the simulation of detailed transients. An example micro-grid model was built using the SGridSim tool and tested to simulate both the voltage and power distribution features with a total absolute relative error of less than 6%.
43 PARTICLE ACCELERATORS↗
Bus.py: A GridLAB-D Communication Interface for Smart Distribution Grid Simulations
As more Smart Grid technologies (e.g., distributed photovoltaic, spatially distributed electric vehicle charging) are integrated into distribution grids, static distribution simulations are no longer sufficient for performing modeling and analysis. GridLAB-D is an agent-based distribution system simulation environment that allows fine-grained end-user models, including geospatial and network topology detail. A problem exists in that, without outside intervention, once the GridLAB-D simulation begins execution, it will run to completion without allowing the real-time interaction of Smart Grid controls, such as home energy management systems and aggregator control. We address this lack of runtime interaction by designing a flexible communication interface, Bus.py (pronounced bus-dot-pie), that uses Python to pass messages between one or more GridLAB-D instances and a Smart Grid simulator. This work describes the design and implementation of Bus.py, discusses its usefulness in terms of some Smart Grid scenarios, and provides an example of an aggregator-based residential demand response system interacting with GridLAB-D through Bus.py. The small scale example demonstrates the validity of the interface and shows that an aggregator using said interface is able to control residential loads in GridLAB-D during runtime to cause a reduction in the peak load on the distribution system in (a) peak reduction and (b) time-of-use pricing cases.
24 POWER TRANSMISSION AND DISTRIBUTION↗
15 MW HArdware-in-the-loop Grid Simulation Project
The 15MW Hardware-in-the-loop (HIL) Grid Simulator project was to (1) design, (2) construct and (3) commission a state-of-the-art grid integration testing facility for testing of multi-megawatt devices through a ‘shared facility’ model open to all innovators to promote the rapid introduction of new technology in the energy market to lower the cost of energy delivered. The 15 MW HIL Grid Simulator project now serves as the cornerstone of the Duke Energy Electric Grid Research, Innovation and Development (eGRID) Center. This project leveraged the 24 kV utility interconnection and electrical infrastructure of the US DOE EERE funded WTDTF project at the Clemson University Restoration Institute in North Charleston, SC. Additionally, the project has spurred interest from other technology sectors, including large PV inverter and energy storage testing and several leading edge research proposals dealing with smart grid technologies, grid modernization and grid cyber security. The key components of the project are the power amplifier units capable of providing up to 20MW of defined power to the research grid. The project has also developed a one of a kind solution to performing fault ride-through testing by combining a reactive divider network and a large power converter into a hybrid method. This unique hybrid method of performing fault ride-through analysis will allow for the research team at the eGRID Center to investigate the complex differences between the alternative methods of performing fault ride-through evaluations and will ultimately further the science behind this testing. With the final goal of being able to perform HIL experiments and demonstration projects, the eGRID team undertook a significant challenge with respect to developing a control system that is capable of communicating with several different pieces of equipment with different communication protocols in real-time. The eGRID team developed a custom fiber optical network that is based upon FPGA hardware that allows for communication between the key real-time interfaces and reduces the latency between these interfaces to acceptable levels for HIL experiments.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Advanced Grid Simulator for Multi-Megawatt Power Converter Testing and Certification
Grid integration testing of inverter-coupled renewable energy technologies is an essential step in the qualification of renewable energy and energy storage systems to ensure the stability of the power system. New types of devices must be thoroughly tested and validated for compliance with relevant grid codes and interconnection requirements. For this purpose, highly specialized custom-made testing equipment is needed to emulate various types of realistic grid conditions that are required by certification bodies or for research purposes. For testing multi-megawatt converters, a high power grid simulator capable of creating controlled grid conditions and meeting both power quality and dynamic characteristics is needed. This paper describes the new grid simulator concept based on ABB's medium voltage ACS6000 drive technology that utilizes advanced modulation and control techniques to create an unique testing platform for various multi-megawatt power converter systems. Its performance is demonstrated utilizing the test results obtained during commissioning activities at the National Renewable Energy Laboratory in Colorado, USA.
17 WIND ENERGY↗
NREL and DONG Energy Collaboration for Grid Simulator Controls and Testing: Cooperative Research and Development Final Report, CRADA Number CRD-13-527
The National Renewable Energy Laboratory (NREL) and DONG Energy are interested in collaborating for the development of control algorithms, modeling, and grid simulator testing of wind turbine generator systems involving NWTC's advanced Controllable Grid Interface (CGI). NREL and DONG Energy will work together to develop control algorithms, models, test methods, and protocols involving NREL's CGI, as well as appropriate data acquisition systems for grid simulation testing. The CRADA also includes work on joint publication of results achieved from modeling and testing efforts. Further, DONG Energy will send staff to NREL on a long-term basis for collaborative work including modeling and testing. NREL will send staff to DONG Energy on a short-term basis to visit wind power sites and participate in meetings relevant to this collaborative effort. DOE has provided NREL with over 10 years of support in developing custom facilities and capabilities to enable testing of full-scale integrated wind turbine drivetrain systems in accordance with the needs of the US wind industry. NREL currently operates a 2.5MW dynamometer and is in the processes of commissioning a 5MW dynamometer and a grid simulator (referred to as a 'Controllable Grid Interface' or CGI). DONG Energy is the market leader in offshore wind power development, with currently over 1 GW of on- and offshore wind power in operation, and 1.3 GW under construction. DONG Energy has on-going R&D projects involving high voltage DC (HVDC) transmission.
17 WIND ENERGY↗
Hardware-in-the-loop grid simulator system and method
A hardware-in-the-loop (HIL) electrical grid simulation system and method that combines a reactive divider with a variable frequency converter to better mimic and control expected and unexpected parameters in an electrical grid. The invention provides grid simulation in a manner to allow improved testing of variable power generators, such as wind turbines, and their operation once interconnected with an electrical grid in multiple countries. The system further comprises an improved variable fault reactance (reactive divider) capable of providing a variable fault reactance power output to control a voltage profile, therein creating an arbitrary recovery voltage. The system further comprises an improved isolation transformer designed to isolate zero-sequence current from either a primary or secondary winding in a transformer or pass the zero-sequence current from a primary to a secondary winding.
17 WIND ENERGY↗
Impedance Measurement of Wind Turbines using a Multimegawatt Grid Simulator: Preprint
This paper presents the impedance measurements of a 4 MW wind turbine conducted using a multimegawatt grid simulator at the National Renewable Energy Laboratory in Colorado, United States. This paper describes different systems, including a 7 MVA grid simulator, a 5 MW dynamometer, a medium-voltage measurement system, and a real-time control system used for the automated impedance measurement of a utility-scale wind turbine. Different aspects of impedance measurement are discussed, including the selection of the magnitude of injected perturbation, measurement of frequency cross-coupling between the sequence impedance responses, and the alignment of the reference frame for sequence impedance measurement. The paper also demonstrates high-fidelity validation of an EMT simulation model of the wind turbine using impedance measurements.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Characterization of a Power Electronic Grid Simulator for Wind Turbine Generator Compliance Testing
This paper presents the commissioning results and testing capabilities of a multi-megawatt power electronic grid simulator situated in National Renewable Energy Laboratory's (NREL's) new testing facility. The commissioning is done using a commercial type 4 multi-megawatt sized wind turbine generator (WTG) installed in NREL's new 5 MW dynamometer and a kilowatt sized type 1 WTG connected to the existing 2.5 MW dynamometer at NREL. The paper demonstrates the outstanding testing capability of the grid simulator and its application in the grid code compliance evaluation of WTGs including balanced and unbalanced voltage low and high fault ride-through. Furthermore, the paper provides insight into the performance of commercial WTGs during both normal and abnormal operating conditions.
17 WIND ENERGY↗
Dynamic Power Grid Simulation
GridDyn is a part of power grid simulation toolkit. The code is designed using modern object oriented C++ methods utilizing C++11 and recent Boost libraries to ensure compatibility with multiple operating systems and environments.
Top, Philip↗
Dynamic Power Grid Simulation
GridDyn is a part of power grid simulation toolkit. The code is designed using modern object oriented C++ methods utilizing C++11 and recent Boost libraries to ensure compatibility with multiple operating systems and environments.
Top, Philip↗
Impedance Measurement of Inverter-Coupled Generation Using a Multimegawatt Grid Simulator
This presentation provides an overview of interver-coupled generation using a multimegawatt grid simulator.
17 WIND ENERGY↗
Dynamic Modeling and Validation of Electrolyzers in Real Time Grid Simulation
Dynamic Modeling and Validation of Electrolyzers in Real Time Grid Simulation
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Parallel Power Grid Simulation Toolkit
ParGrid is a 'wrapper' that integrates a coupled Power Grid Simulation toolkit consisting of a library to manage the synchronization and communication of independent simulations. The included library code in ParGid, named FSKIT, is intended to support the coupling multiple continuous and discrete even parallel simulations. The code is designed using modern object oriented C++ methods utilizing C++11 and current Boost libraries to ensure compatibility with multiple operating systems and environments.
Smith, Steve↗
Smart-PGSim: Using Neural Network to Accelerate AC-OPF Power Grid Simulation
In this work we address the problem of accelerating complex power-grid simulation through machine learning ( ML). Specifically, we develop a framework, Smart-PGSim,which generates multitask-learning (MTL) neural network (NN)models to predict the initial values of variables critical to the problem convergence. MTL models allow information sharing when predicting multiple dependent variables while including customized layers to predict individual variables. We show that,to achieve the required accuracy, it is paramount to embed domain-specific constraints derived from the specific power-grid components in the MTL model. Smart-PGSim then employs the predicted initial values as a high-quality initial condition for the power-grid numerical solver (warm start), resulting in both higher performance compared to state-of-the-art solutions while maintaining the required accuracy. Smart-PGSim brings 2.60×speedup on average (up to 3.28×) computed over 10,000 problems, without losing solution optimality.
machine learning, neural networks↗
First International Workshop on Grid Simulator Testing of Wind Turbine Drivetrains: Workshop Proceedings
This report summarizes the proceedings of the First International Workshop on Grid Simulator Testing of Wind Turbine Drivetrains, held from June 13 to 14, 2013, at the National Renewable Energy Laboratory's National Wind Technology Center, located south of Boulder, Colorado. The workshop was sponsored by the U.S. Department of Energy and cohosted by the National Renewable Energy Laboratory and Clemson University under ongoing collaboration via a cooperative research and development agreement. The purpose of the workshop was to provide a forum to discuss the research, testing needs, and state-of-the-art apparatuses involved in grid compliance testing of utility-scale wind turbine generators. This includes both dynamometer testing of wind turbine drivetrains ('ground testing') and field testing grid-connected wind turbines. Four sessions followed by discussions in which all attendees of the workshop were encouraged to participate comprised the workshop.
17 WIND ENERGY↗
Machine learning from RANS and LES to inform coarse grid simulations
Nuclear system thermal hydraulic analysis has historically relied on computationally inexpensive 1D codes. However, such tools are unable to capture multiscale multidimensional effects in large nuclear reactor enclosures. On the other hand, simulations with higher fidelity can be too expensive for such purposes. One of the ways to reduce computational cost is to perform simulations on a coarse grid, which, unfortunately, introduces large discretization errors. In this paper, two high-to-low data-driven approaches are investigated: (1) a coarse grid turbulence model to predict eddy viscosity and (2) correction of errors in coarse grid velocity fields. The approaches aim to reduce grid- and turbulence model-induced errors in coarse grid Reynolds-averaged Navier–Stokes (RANS) simulations. Two sources of high-fidelity data, RANS and large eddy simulations (LES), are explored. To extract the eddy viscosity from the LES data, an inverse optimization problem is solved. However, the LES eddy viscosity is shown to be comparable to the RANS eddy viscosity in terms of error reduction. Therefore, the directly available RANS eddy viscosity was used to develop a coarse grid data-driven turbulence model. Additionally, error correction in velocity is used to reduce the remaining uncertainties and bring the results closer to reality. In conclusion, the performance of the frameworks is demonstrated for a scaled upper plenum of a gas-cooled reactor facility.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗