Version 1
: Received: 29 October 2023 / Approved: 30 October 2023 / Online: 30 October 2023 (10:45:52 CET)
Version 2
: Received: 31 October 2023 / Approved: 31 October 2023 / Online: 1 November 2023 (03:08:00 CET)
Version 3
: Received: 9 November 2023 / Approved: 9 November 2023 / Online: 9 November 2023 (10:58:47 CET)
How to cite:
Argha, D. B. P.; Ahmed, M. A. Design of Photovoltaic System for Green Manufacturing by using Statistical Design of Experiments. Preprints2023, 2023101913. https://doi.org/10.20944/preprints202310.1913.v3
Argha, D. B. P.; Ahmed, M. A. Design of Photovoltaic System for Green Manufacturing by using Statistical Design of Experiments. Preprints 2023, 2023101913. https://doi.org/10.20944/preprints202310.1913.v3
Argha, D. B. P.; Ahmed, M. A. Design of Photovoltaic System for Green Manufacturing by using Statistical Design of Experiments. Preprints2023, 2023101913. https://doi.org/10.20944/preprints202310.1913.v3
APA Style
Argha, D. B. P., & Ahmed, M. A. (2023). Design of Photovoltaic System for Green Manufacturing by using Statistical Design of Experiments. Preprints. https://doi.org/10.20944/preprints202310.1913.v3
Chicago/Turabian Style
Argha, D. B. P. and Md Ashik Ahmed. 2023 "Design of Photovoltaic System for Green Manufacturing by using Statistical Design of Experiments" Preprints. https://doi.org/10.20944/preprints202310.1913.v3
Abstract
AbstractTo overcome the negative impacts on the environment and other problems associated with fossil fuels have forced many countries to inquire into and change to environmentally friendly alternatives that are renewable to sustain the increasing energy demand. Solar energy is one of the best renewable energy sources with the least negative impacts on the environment. Different countries have formulated solar energy policies to reduce dependence on fossil fuel and increasing domestic energy production by solar energy. According to the 2010 BP Statistical Energy Survey, the world cumulative installed solar energy capacity was 22928.9 MW in 2009, a change of 46.9% compared to 2008. In this study, a PV generation system has been modeled and installed considering uncertain whether based on the hourly wind speed data of New York City (NYC) of year 2014. Regression models has been used to forecast the hourly, weekly, and monthly wind speed of NYC year 2014. Design of experiment (DOE) has been used to determine the optimal panel size (area), the battery capacity size, and other levels of factors.
Keywords
Solar PV system; Regression Model; DOE; Solar energy; Fossil fuels
Subject
Engineering, Civil Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Debo Brata Paul Argha
Commenter's Conflict of Interests: Author