Application of Data Analysis and Visualization Tools for U.S. Renewable Solar Energy Generation, Its Sustainability Benefits, and Teaching In Engineering Curriculum

Ben D Radhakrishnan; James Jay Jaurez; Nelson Altamirano

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Conference: 2024 ASEE Annual Conference & Exposition
Location: Portland, Oregon
Publication Date: June 23, 2024
Start Date: June 23, 2024
End Date: June 26, 2024
Conference Session: DSA Technical Session 2
Tagged Topics: Diversity and Data Science & Analytics Constituent Committee (DSA)
Page Count: 29
DOI: 10.18260/1-2--46586
Permanent URL: https://peer.asee.org/46586
Download Count: 188

Paper Authors

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Ben D Radhakrishnan National University

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Ben D Radhakrishnan is a Professor of Practice, currently a full time Faculty in the Department of Engineering, School of Technology and Engineering, National University, San Diego, California, USA. He is the Academic Program Director for MS Engineering Management program. He develops and teaches Engineering courses in different programs including engineering and business management schools. His research includes application of AI for project management, sustainability and data center energy.

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James Jay Jaurez National University

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Dr. Jaurez is a dedicated Academic Program Director and Associate Professor in Information Technology Management at National University where he has served since 2004. Dr. Jaurez is also a FIRST Robotics Head Coach since 2014 and leads outreach in roboti

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Nelson Altamirano National University

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Abstract

The advancement of Data Analysis technologies with visualization has gained significant ground in the industries and they are also gaining ground in higher education curriculum. This research will focus on the application of these techniques to the energy industry – in particular, solar renewable energy generation in all the States in the United States (US). One strong opposing action against the progression of climate change is the use of renewable energy. The objective of the research is to develop a case study on renewable solar energy and its impact on abating or preventing CO2 emissions to help reduce the severe impacts of climate change in the United States and demonstrate how it supports the 3Es of sustainability at the same time. This research paper will specifically explore the past production of solar energy in all the states in the US, and with the use of data analysis tools will predict the production to the year 2030. The reduction of CO2 emissions with the use of renewable solar energy is in direct support of the three elements of sustainability, namely the 3Es: Environment, Economics, and Equity (or social justice). This research will quantify the past benefits already realized in all these three areas for solar energy, and project them up to 2030. Cluster analysis technique will be applied to solar generation across all US States to identify group(s) at distinct levels of production. This can help States to follow the leading State(s) policy and process to increase their solar generation and thus help manage climate change. Solar energy generation challenges and recycling issues of solar equipment will also be addressed. This case study approach will fill a gap that currently exists in engineering education when it comes to exploring renewable energy and its sustainability benefits with modern data analysis tools. This research will use publicly available data sources (e.g., NREL, EIA), ubiquitous Excel, and open-source data analytics and prediction tool Orange (for K-Means clustering analysis), so this type of case study approach could be taught and engage engineering students without any barrier. For highly effective visualization, the use of Tableau is also demonstrated.

Citation
Format

Radhakrishnan, B. D., & Jaurez, J. J., & Altamirano, N. (2024, June), Application of Data Analysis and Visualization Tools for U.S. Renewable Solar Energy Generation, Its Sustainability Benefits, and Teaching In Engineering Curriculum Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--46586

TY - CPAPER
AB - The advancement of Data Analysis technologies with visualization has gained significant ground in the industries and they are also gaining ground in higher education curriculum. This research will focus on the application of these techniques to the energy industry – in particular, solar renewable energy generation in all the States in the United States (US). One strong opposing action against the progression of climate change is the use of renewable energy.
The objective of the research is to develop a case study on renewable solar energy and its impact on abating or preventing CO2 emissions to help reduce the severe impacts of climate change in the United States and demonstrate how it supports the 3Es of sustainability at the same time. This research paper will specifically explore the past production of solar energy in all the states in the US, and with the use of data analysis tools will predict the production to the year 2030. The reduction of CO2 emissions with the use of renewable solar energy is in direct support of the three elements of sustainability, namely the 3Es: Environment, Economics, and Equity (or social justice). This research will quantify the past benefits already realized in all these three areas for solar energy, and project them up to 2030.
Cluster analysis technique will be applied to solar generation across all US States to identify group(s) at distinct levels of production. This can help States to follow the leading State(s) policy and process to increase their solar generation and thus help manage climate change. Solar energy generation challenges and recycling issues of solar equipment will also be addressed.
This case study approach will fill a gap that currently exists in engineering education when it comes to exploring renewable energy and its sustainability benefits with modern data analysis tools. This research will use publicly available data sources (e.g., NREL, EIA), ubiquitous Excel, and open-source data analytics and prediction tool Orange (for K-Means clustering analysis), so this type of case study approach could be taught and engage engineering students without any barrier. For highly effective visualization, the use of Tableau is also demonstrated.

AU - Ben D Radhakrishnan
AU - James Jay Jaurez
AU - Nelson Altamirano
CY - Portland, Oregon
DA - 2024/06/23
PB - ASEE Conferences
TI - Application of Data Analysis and Visualization Tools for U.S. Renewable Solar Energy Generation, Its Sustainability Benefits, and Teaching In Engineering Curriculum
UR - https://peer.asee.org/46586
DO - 10.18260/1-2--46586
ER -