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Simulink Model of a New Energy EVG-005 5kW Hydropower Turbine
This dataset from the Alaska Center for Energy and Power provides a Simulink model and measurement files for a New Energy EVG-005 5kW hydropower turbine tested at the Tanana River Test Site. The package includes acoustic Doppler current profiler data, electrical output measurement...
Browning, E. et al University of Alaska Fairbanks
Oct 09, 2023
Universal Passive Synchronization Method for Grid-Forming Inverters Without Mode Transition
Power systems are transforming with increasing levels of inverter-based resources (IBRs). This transformation requires critical roles of grid-forming (GFM) inverters replacing synchronous generators for bulk power system stabilization and ancillary services, also allowing flexible...
Chang, H. et al NLR
Dec 31, 2022
Quantitative Trade-Off in Distributed Secondary Control for Autonomous AC Microgrids
In this paper, we propose to quantify the trade-off between voltage regulation and reactive power sharing in autonomous AC microgrids with distributed secondary control. It is known that voltage regulation and reactive power sharing in droop-controlled autonomous AC microgrids are...
Liu, Z. et al Purdue University
Dec 31, 2024
Hardware-in-the-Loop Test Bed and Test Methodology for Microgrid Controller Evaluation
Increasing penetration levels of distributed energy resources are making the deployment of microgrids more feasible. Controllers that operate such microgrids are key to realizing the objectives of the microgrid owner or operator and there is a need to evaluate microgrid controller...
Prabakar, K. et al NLR
Aug 16, 2018
Distributed wind-hybrid microgrids with autonomous controls and forecasting
Distributed wind-hybrid microgrids have the potential to provide key resilience and economic benefits to both the customers they serve and the utility grids they are connected to. Such microgrids will likely be a key part of the grid of the future, whether connected to large utili...
Anderson, B. et al NLR
Mar 01, 2023
Multi-Task Reinforcement Learning for Distribution System Voltage Control With Topology Changes
This letter proposes a multi-task deep reinforcement learning (DRL) approach for distribution system voltage regulation considering topology changes via PV smart inverter control. The key idea is to encode the topology as an additional state for the DRL and leverage the multi-task...
Pei, Y. et al University of Conneticut
Apr 30, 2023
Microreactor Application Research Validation and Evaluation Project (MARVEL)
Two-page overview of the MARVEL test bed approximately 85-kWth, NaK-cooled, targeting 10-20 kWe located at INL's TREAT site. The fact sheet describes objectives, configuration (fuel, coolant, and power-conversion approach), and planned research on load following, process heat deli...
, . Idaho National Laboratory
Jun 01, 2025
Cyber Security Assessment of Distributed Energy Resources
New distributed energy resource (DER) interconnection standards require communications and interoperability to provide grid operators greater flexibility for delivering voltage and frequency support. These communication channels are designed to allow utilities, aggregators, and ot...
Carter, C. et al Sandia National Laboratories
May 31, 2017
Unleashing the Frequency: Multi-Megawatt Demonstration of 100% Renewable Power Systems with Decentralized Communication-Less Control Scheme
Power systems, which range in size from small microgrids to island systems to large regional grids, are typically managed by a central controller that requires complex communication methods and can be unreliable and pose cyber security risks in certain applications, especially whe...
Koralewicz, P. et al NLR
Aug 31, 2022
Deep Reinforcement Learning for Microgrid Cost Optimization Considering Load Flexibility
This paper proposes a novel Soft-Actor-Critic (SAC) based Deep Reinforcement Learning (DRL) method for optimizing the cost of microgrid operation by leveraging load flexibility. The proposed SAC-DRL method is designed to coordinate the control of distributed energy resources (DERs...
Pei, Y. et al University of Connecticut
Dec 31, 2023
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