Hybrid Energy Storage Management in a Renewable Energy-Based Residential Nanogrid

Renewable energy resource dynamics significantly contribute to renewable energy system complexities in addition to reliability issues. Energy storage systems such as batteries are used for supply reliability in renewable energy system designs such as residential nanogrids. Factors considered in battery energy storage options in renewable energy systems include the low cost of acquisition, large-scale commercial deployment and high energy storage densities. Despite the competitive advantages of the battery systems, other energy storage facilities have advantages such as electric vehicles with significant time spent parking and hydrogen fuel cells with considerably long periods of retaining energy storage. This paper considered other technoeconomic advantages in defining a hybrid energy storage management for battery, electric vehicles and hydrogen fuel cells configured in a combined and substituted storage of a residential nanogrid. Constraints of uncertain renewable energy generation and customer demands were used for the nanogrid's optimal capacity with each of the storage configurations analyzed based on charging and discharging conditions. The objectives were to strategize energy tradeoffs between the nanogrid and the main grid for energy cost reduction and improved energy utilization. The results indicate the ranges of hourly-average available energy for tradeoffs in the main grid-interactive residential nanogrid such as 24 -115 kW in a battery system, 19 - 75 kW in an electric vehicle and 5 - 45 kW in hydrogen fuel cell from a substituted configuration and 110 - 250 kW from a combined storage configuration. The uncertain renewable energy generation and customer demands were utilized in suggesting a dynamic energy pricing for future study considerations.

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Published
2024-11-04
DOI
https://doi.org/10.1109/pecon62060.2024.10827631
Citations
1
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
0.33

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article

Hybrid Energy Storage Management in a Renewable Energy-Based Residential Nanogrid

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1 citations
Microgrid Control and Optimization
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article

Hybrid Energy Storage Management in a Renewable Energy-Based Residential Nanogrid

Chee Wei Tan, Chuen Ling Toh, Oladimeji Ibrahim, Kwan Yiew Lau, Ahmed Tijjani Dahiru, Razman Ayop
article en
1 citations

Abstract

Renewable energy resource dynamics significantly contribute to renewable energy system complexities in addition to reliability issues. Energy storage systems such as batteries are used for supply reliability in renewable energy system designs such as residential nanogrids. Factors considered in battery energy storage options in renewable energy systems include the low cost of acquisition, large-scale commercial deployment and high energy storage densities. Despite the competitive advantages of the battery systems, other energy storage facilities have advantages such as electric vehicles with significant time spent parking and hydrogen fuel cells with considerably long periods of retaining energy storage. This paper considered other technoeconomic advantages in defining a hybrid energy storage management for battery, electric vehicles and hydrogen fuel cells configured in a combined and substituted storage of a residential nanogrid. Constraints of uncertain renewable energy generation and customer demands were used for the nanogrid's optimal capacity with each of the storage configurations analyzed based on charging and discharging conditions. The objectives were to strategize energy tradeoffs between the nanogrid and the main grid for energy cost reduction and improved energy utilization. The results indicate the ranges of hourly-average available energy for tradeoffs in the main grid-interactive residential nanogrid such as 24 -115 kW in a battery system, 19 - 75 kW in an electric vehicle and 5 - 45 kW in hydrogen fuel cell from a substituted configuration and 110 - 250 kW from a combined storage configuration. The uncertain renewable energy generation and customer demands were utilized in suggesting a dynamic energy pricing for future study considerations.

University of Technology Malaysia (MY), Universiti Tenaga Nasional (MY)
Ministry of Higher Education, Universiti Teknologi Malaysia
Affordable and clean energy
Openalex Percentile: Top 37%
Microgrid Control and Optimization
0.33
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