Effective dynamic energy management algorithm for grid-interactive microgrid with hybrid energy storage system

Microgrids offer an optimistic solution for delivering electricity to remote regions and incorporating renewable energy into existing power systems. However, the energy balance between generation and consumption remains a significant challenge in microgrid setups. This research presents an adaptive energy management approach for grid-interactive microgrids. The DC microgrid is established by combining solar PV with a battery-supercapacitor (SC) hybrid energy storage system (HESS). The proposed approach integrates the frequency separation strategy with a rule-based algorithm to ensure optimal power sharing among sources while maintaining the safe operation of storage units. Specifically, the battery meets steady-state energy demands, the SC addresses transient power requirements, and the grid support is tailored to system needs. The method employs the dq reference frame technique to control the grid inverter (VSC). The key merits include efficient power allocation, fast regulation of the DC link voltage irrespective of load or generation variations, seamless transition between scenarios, and introduction of a straightforward battery state of charge (SOC)-based coefficient for allocating power between the battery and the grid while enhancing the power quality within the grid. Moreover, safety measures prevent the SC from overcharging, the battery from high current, overcharging, and deep discharging, potentially extending their lifespan. Validation and implementation of the method are conducted using MATLAB/Simulink.

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Publication Details

Journal
Scientific Reports
Published
2024-08-31
DOI
https://doi.org/10.1038/s41598-024-70599-w
Citations
5
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
1.64
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article

Effective dynamic energy management algorithm for grid-interactive microgrid with hybrid energy storage system

Heli Amit Shah, Yaya Kamagaté
5 citations
Scientific Reports
Microgrid Control and Optimization
1.64
article

Effective dynamic energy management algorithm for grid-interactive microgrid with hybrid energy storage system

Heli Amit Shah, Yaya Kamagaté
article en
5 citations

Abstract

Microgrids offer an optimistic solution for delivering electricity to remote regions and incorporating renewable energy into existing power systems. However, the energy balance between generation and consumption remains a significant challenge in microgrid setups. This research presents an adaptive energy management approach for grid-interactive microgrids. The DC microgrid is established by combining solar PV with a battery-supercapacitor (SC) hybrid energy storage system (HESS). The proposed approach integrates the frequency separation strategy with a rule-based algorithm to ensure optimal power sharing among sources while maintaining the safe operation of storage units. Specifically, the battery meets steady-state energy demands, the SC addresses transient power requirements, and the grid support is tailored to system needs. The method employs the dq reference frame technique to control the grid inverter (VSC). The key merits include efficient power allocation, fast regulation of the DC link voltage irrespective of load or generation variations, seamless transition between scenarios, and introduction of a straightforward battery state of charge (SOC)-based coefficient for allocating power between the battery and the grid while enhancing the power quality within the grid. Moreover, safety measures prevent the SC from overcharging, the battery from high current, overcharging, and deep discharging, potentially extending their lifespan. Validation and implementation of the method are conducted using MATLAB/Simulink.

Scientific ReportsVol. 14(1)
Parul University (IN), Parul University (IN)
Affordable and clean energy
Openalex Percentile: Top 16%
Microgrid Control and Optimization
1.64
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Effective dynamic energy management algorithm for grid-interactive microgrid with hybrid energy storage system — Heli Amit Shah, Yaya Kamagaté · Scientific Reports (2024) | TGRS Research Map | TGRS