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SolarPACES Model Intercomparison and Case Studies Concerning Hybrid CSP-TES-PV-Battery Systems
Hamilton, W. et al National Energy Technology Laboratory
Dec 02, 2024
0 Resources
0 Stars
In progress
0 Resources
0 Stars
In progress
Artificial Intelligence for Robust Integration of AMI and Synchrophasor Data to Significantly Boost Solar Adoption
The overarching goal of the project is to create a highly efficient framework of machine learning (ML) methods that provide consistent and accurate real-time knowledge of system states from diverse advanced metering infrastructure (AMI) devices and phasor measurement units (PMUs) ...
Ayyanar, R. et al Arizona State University
Feb 01, 2025
13 Resources
0 Stars
In curation
13 Resources
0 Stars
In curation
Performance Analysis of a Stirling Engine Hybrid Power System
This project presents the performance analysis of a photovoltaic (PV)/Stirling battery system in terms of energy efficiency, economic feasibility, and environmental sustainability. The analysis includes the dynamic start-up and cooling phases of the system, and then compares its p...
Zabalaga, P. National Renewable Energy Laboratory
Dec 20, 2019
7 Resources
0 Stars
In curation
7 Resources
0 Stars
In curation
Error-Level-Controlled Synthetic Forecasts for Renewable Generation
Renewable energy resources, including solar and wind energy, play a significant role in sustainable energy systems. However, the inherent uncertainty and intermittency of renewable generation pose challenges to the safe and efficient operation of power systems. Recognizing the imp...
Zhang, X. et al National Renewable Energy Laboratory (NREL)
Jun 01, 2021
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Maximum demand charge rates for commercial and industrial electricity tariffs in the United States
NREL has assembled a list of U.S. retail electricity tariffs and their associated demand charge rates for the Commercial and Industrial sectors. The data was obtained from the Utility Rate Database. Keep the following information in mind when interpreting the data:
(1) These data...
McLaren. . et al National Renewable Energy Laboratory
Sep 19, 2017
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible