Predicting Variability of High-Penetration Photovoltaic Systems in a Community Microgrid by Analyzing High-Temporal Rate Data. Shadmand, M. B., Balog, R. S., & Johnson, M. D. IEEE Transactions on Sustainable Energy, 5(4):1434–1442, October, 2014. ![Predicting Variability of High-Penetration Photovoltaic Systems in a Community Microgrid by Analyzing High-Temporal Rate Data [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Interest in renewable energy sources continues to gain popularity. However, a major fundamental limitation exists that prevents widespread adoption: variability of electricity generated. Distributed generation (DG) grid-tied photovoltaic (PV) systems with centralized battery back-up can mitigate the variability of PV systems and be optimized to reduce cost by analyzing high-temporal rate data. Thus, it is an attractive system to meet “go green” mandates, while also providing reliable electricity. The focus of this paper is to analyze the variability of a high-penetration PV scenario when incorporated into the microgrid concept. The proposed system design approach is based on high-temporal rate instead of the more commonly used hourly data rate. The methodology presented in this paper employs a technoeconomic approach to determine the optimal system design to guarantee reliable electricity supply with lowest investment. The proposed methodology is used to demonstrate that the variability of the PV resource can be quantified by determining the number of PV arrays and their corresponding distance in the microgrid and then mitigate with optimized storage.
@article{shadmand_predicting_2014,
title = {Predicting {Variability} of {High}-{Penetration} {Photovoltaic} {Systems} in a {Community} {Microgrid} by {Analyzing} {High}-{Temporal} {Rate} {Data}},
volume = {5},
issn = {1949-3029},
url = {http://ieeexplore.ieee.org/abstract/document/6891361/},
doi = {10.1109/TSTE.2014.2345745},
abstract = {Interest in renewable energy sources continues to gain popularity. However, a major fundamental limitation exists that prevents widespread adoption: variability of electricity generated. Distributed generation (DG) grid-tied photovoltaic (PV) systems with centralized battery back-up can mitigate the variability of PV systems and be optimized to reduce cost by analyzing high-temporal rate data. Thus, it is an attractive system to meet “go green” mandates, while also providing reliable electricity. The focus of this paper is to analyze the variability of a high-penetration PV scenario when incorporated into the microgrid concept. The proposed system design approach is based on high-temporal rate instead of the more commonly used hourly data rate. The methodology presented in this paper employs a technoeconomic approach to determine the optimal system design to guarantee reliable electricity supply with lowest investment. The proposed methodology is used to demonstrate that the variability of the PV resource can be quantified by determining the number of PV arrays and their corresponding distance in the microgrid and then mitigate with optimized storage.},
number = {4},
journal = {IEEE Transactions on Sustainable Energy},
author = {Shadmand, M. B. and Balog, R. S. and Johnson, M. D.},
month = oct,
year = {2014},
keywords = {Batteries, DG grid-tied PV systems, Distributed PV systems, Microgrids, PV arrays, PV system variability mitigation, PV-storage system, Photovoltaic systems, Power system reliability, Smart grids, centralized battery back-up, community microgrid, cost reduction, distributed generation, distributed power generation, electricity generation variability, electricity supply reliability, go green mandates, high-penetration photovoltaic systems, high-temporal rate data analysis, microgrid, microgrid concept, optimal system design, optimized storage, photovoltaic (PV), photovoltaic power systems, power generation reliability, renewable energy sources, secondary cells, smart grid, technoeconomic approach, variability analysis},
pages = {1434--1442}
}
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