Control strategy to improve load/power sharing, DC bus voltage restoration, and batteries SOC balancing in a DC microgrid

Eydi, Mohammad; Ghazi, Reza

doi:10.1049/iet-rpg.2020.0239

Cited by 9 publications

(4 citation statements)

References 35 publications

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“…For instance, in [19], the virtual resistance method is introduced, which focuses on current sharing. Its modified version is presented in [20], where, in addition to the current sharing, SOCs balancing and voltage regulation have been taken into consideration. Neglecting DC bus voltage drop and the location of loads and RESs are the main disadvantages of these methods, the subjects which highly influence the DC bus voltage deviation and proper current sharing.…”

Section: • Improper Current Sharing • DC Bus Voltage Deviation • Socs...mentioning

confidence: 99%

“…According to (20), by setting a proper value for A, the value of UCD can be limited to an acceptable range.…”

Section: Virtual Current Definitionmentioning

confidence: 99%

“…The value of A depends on the maximum of UCD when SOCs are equal, while the value of B relies on the battery characteristics. Based on (20), the UCD depends on the RESs and load currents and the DC bus voltage drop. The DC bus voltage drop depends on the location of the RESs and loads.…”

Section: Segments Range Allocationmentioning

confidence: 99%

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Mitigating voltage deviation, SOCs difference, and currents disparity in DC microgrids using a novel piecewise SOC‐based control method

Erfani Haghani Kerman,

Abavisani,

Eydi

et al. 2024

IET Generation Trans & Dist

Self Cite

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Proper current sharing, DC bus voltage deviation reduction, and SOCs balancing, along with ensuring stability are the vital challenges of DC microgrids control algorithms. Addressing these challenges without communication links and a central controller is one of the priorities of control methods. Motivated by the above mentions, this paper presents a novel communication‐free control method. In this regard, a new parameter called “virtual current” is defined according to the unit current and its SOC. Then using a piecewise droop curve and the droop curve shift technique, the virtual current for each unit is determined. The units control coefficients and the relationship of the virtual current are allocated based on the location and power of the loads and RESs such that in the worst case; 1) SOCs are converged; 2) the DC bus voltage deviation is reduced; and 3) the current is appropriately distributed. The simulation and experimental results confirm that the proposed method can balance SOCs like SOC‐based methods and share power properly like piecewise droop methods while reducing DC bus voltage deviation.

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Section: • Improper Current Sharing • DC Bus Voltage Deviation • Socs...mentioning

confidence: 99%

“…According to (20), by setting a proper value for A, the value of UCD can be limited to an acceptable range.…”

Section: Virtual Current Definitionmentioning

confidence: 99%

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Mitigating voltage deviation, SOCs difference, and currents disparity in DC microgrids using a novel piecewise SOC‐based control method

Erfani Haghani Kerman,

Abavisani,

Eydi

et al. 2024

IET Generation Trans & Dist

Self Cite

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show abstract

“…So far, lithium‐ion batteries have been widely used in electric vehicles (EV) and energy storage power stations [2]. The state of charge (SOC) representing the ratio between the available capacity and rated capacity is an important parameter to evaluate the performance of batteries used as energy storage devices [3]. Since the lithium‐ion battery is a highly time‐invariant, non‐linear, and complex electrochemical system, direct measurement of SOC is difficult and challenging.…”

Section: Introductionmentioning

confidence: 99%

MDGN: Circuit design of memristor‐based denoising autoencoder and gated recurrent unit network for lithium‐ion battery state of charge estimation

Wang

Zhang

Han

et al. 2023

IET Renewable Power Gen

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Due to the highly complex and non‐linear physical dynamics of lithium‐ion batteries, it is unfeasible to measure the state of charge (SOC) directly. Designing systems capable of accurate SOC estimation has become a key technology for battery management systems (BMS). Existing mainstream SOC estimation approaches still suffer from the limitations of low efficiency and high‐power consumption, owing to the great number of samples required for training. To address these gaps, this paper proposes a memristor‐based denoising autoencoder and gated recurrent unit network (MDGN) for fast and accurate SOC estimation of lithium‐ion batteries. Specifically, the DAE circuit module is designed to extract useful feature representation with strong generalization and noise immunity. Then, the gated recurrent unit (GRU) circuit module is designed to learn the long‐term dependencies between high‐dimensional input and output data. The overall performance is evaluated by root mean square error (RMSE) and mean absolute error (MAE) at 0, 25, and 45°C, respectively. Compared with the current state‐of‐the‐art methods, the entire scheme shows its superior performance in accuracy, robustness, and operation cost (referring to time cost).

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An SOC-Based Switching Functions Double-Layer Hierarchical Control for Energy Storage Systems in DC Microgrids

Wang,

2024

J. Electr. Eng. Technol.

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Control strategy to improve load/power sharing, DC bus voltage restoration, and batteries SOC balancing in a DC microgrid

Cited by 9 publications

References 35 publications

Mitigating voltage deviation, SOCs difference, and currents disparity in DC microgrids using a novel piecewise SOC‐based control method

Mitigating voltage deviation, SOCs difference, and currents disparity in DC microgrids using a novel piecewise SOC‐based control method

MDGN: Circuit design of memristor‐based denoising autoencoder and gated recurrent unit network for lithium‐ion battery state of charge estimation

An SOC-Based Switching Functions Double-Layer Hierarchical Control for Energy Storage Systems in DC Microgrids

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