Analysis of Renewable Energy Potential Combinations in Microgrid Systems

In response to the growing global and local demand for net-zero carbon emissions, this study thoroughly explores the feasibility of implementing microgrid technology in convenience stores across Taiwan to reduce carbon emissions and enhance overall energy sustainability significantly. The research emphasizes the integration of renewable energy sources, specifically solar and wind power, aligning with Taiwan's strategic initiatives in promoting renewable energy development. Utilizing the HomerPro simulation tool, the study conducts an in-depth assessment of various energy combinations, evaluating their performance under various conditions, including different carbon pricing scenarios, grid reliability factors, and essential financial variables such as discount rates and inflation. A total of 256 system configurations were simulated to identify the most economically viable and environmentally sustainable solutions for these convenience stores. The study provides a comprehensive understanding of the impact of these variables on the financial and operational feasibility of microgrid systems. The findings are crucial for informing policymakers, energy planners, and business owners, offering practical guidance for designing and implementing effective energy strategies within Taiwan's convenience store sector. By advocating for the adoption of microgrid technology, this study contributes to Taiwan's broader goals of achieving carbon neutrality and improving energy security and plays a key role in reducing dependence on conventional grid systems. This work supports transitioning to a more sustainable, resilient, and future-proof energy infrastructure.

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Publication Details

Published
2024-11-06
DOI
https://doi.org/10.1109/rasse64357.2024.10773943
Citations
2
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
0.66
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article

Analysis of Renewable Energy Potential Combinations in Microgrid Systems

I‐Hua Chung, Mingjun Zhang, Chin-Pao Chu
2 citations
Microgrid Control and Optimization
0.66
article

Analysis of Renewable Energy Potential Combinations in Microgrid Systems

I‐Hua Chung, Mingjun Zhang, Chin-Pao Chu
article en
2 citations

Abstract

In response to the growing global and local demand for net-zero carbon emissions, this study thoroughly explores the feasibility of implementing microgrid technology in convenience stores across Taiwan to reduce carbon emissions and enhance overall energy sustainability significantly. The research emphasizes the integration of renewable energy sources, specifically solar and wind power, aligning with Taiwan's strategic initiatives in promoting renewable energy development. Utilizing the HomerPro simulation tool, the study conducts an in-depth assessment of various energy combinations, evaluating their performance under various conditions, including different carbon pricing scenarios, grid reliability factors, and essential financial variables such as discount rates and inflation. A total of 256 system configurations were simulated to identify the most economically viable and environmentally sustainable solutions for these convenience stores. The study provides a comprehensive understanding of the impact of these variables on the financial and operational feasibility of microgrid systems. The findings are crucial for informing policymakers, energy planners, and business owners, offering practical guidance for designing and implementing effective energy strategies within Taiwan's convenience store sector. By advocating for the adoption of microgrid technology, this study contributes to Taiwan's broader goals of achieving carbon neutrality and improving energy security and plays a key role in reducing dependence on conventional grid systems. This work supports transitioning to a more sustainable, resilient, and future-proof energy infrastructure.

National Kaohsiung University of Science and Technology (TW)
Affordable and clean energy
Openalex Percentile: Top 28%
Microgrid Control and Optimization
0.66
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