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The maritime industry is a significant emitter of greenhouse gases in marine ecosystems, prompting a global shift towards renewable‐powered electric vessels, where energy storage is pivotal. The authors examine the potential ramifications of coordinating the charging of Electric Ferries (EFs) on local distribution networks, with Gladstone Marina in Queensland, Australia, serving as a case study. Employing OpenDSS software for power flow analysis, the authors utilise actual load data and simulate a network with four Battery Energy Storage Systems (BESSs) representing proposed charging stations. The authors discuss the impact on bus voltage, load current, and power flow by integrating a storage controller to optimise BESS charging and discharging dynamics. The Dynamic Link Library (DLL) of MATLAB Simulink‐based BESS's dynamic model is linked with OpenDSS environment to replicate the actual electric ferry storage. Additionally, a user‐written DLL in Python regulates BESS charging and discharging by the storage controller according to load demand and BESS State of Charge for ensuring efficient operation within the network. The power flow results without inclusion of BESSs to the network, referred to as the base case, are used for relative comparison with the results in the coordinated mode. The power flow analysis suggests that bus voltages rise by approximately 1%–1.5%, while load current consumption decreases by around 2%–2.5% compared to the base case with variable load. Selected lines and transformers maintain consistent power flows. Notably, a reduction in total power consumption and losses is observed, particularly under an 80% load demand increase. These findings indicate that the coordinated mode with a storage controller effectively manages BESS charging and discharging according to demand. Moreover, the storage controller ensures system parameters remain within permissible limits. The support of real and reactive power by BESSs during peak hours validates their role as peak shavers for the test network, suggesting that EFs can operate in either Grid to Ferry mode during charging and Ferry to Grid mode during discharging.
The maritime industry is a significant emitter of greenhouse gases in marine ecosystems, prompting a global shift towards renewable‐powered electric vessels, where energy storage is pivotal. The authors examine the potential ramifications of coordinating the charging of Electric Ferries (EFs) on local distribution networks, with Gladstone Marina in Queensland, Australia, serving as a case study. Employing OpenDSS software for power flow analysis, the authors utilise actual load data and simulate a network with four Battery Energy Storage Systems (BESSs) representing proposed charging stations. The authors discuss the impact on bus voltage, load current, and power flow by integrating a storage controller to optimise BESS charging and discharging dynamics. The Dynamic Link Library (DLL) of MATLAB Simulink‐based BESS's dynamic model is linked with OpenDSS environment to replicate the actual electric ferry storage. Additionally, a user‐written DLL in Python regulates BESS charging and discharging by the storage controller according to load demand and BESS State of Charge for ensuring efficient operation within the network. The power flow results without inclusion of BESSs to the network, referred to as the base case, are used for relative comparison with the results in the coordinated mode. The power flow analysis suggests that bus voltages rise by approximately 1%–1.5%, while load current consumption decreases by around 2%–2.5% compared to the base case with variable load. Selected lines and transformers maintain consistent power flows. Notably, a reduction in total power consumption and losses is observed, particularly under an 80% load demand increase. These findings indicate that the coordinated mode with a storage controller effectively manages BESS charging and discharging according to demand. Moreover, the storage controller ensures system parameters remain within permissible limits. The support of real and reactive power by BESSs during peak hours validates their role as peak shavers for the test network, suggesting that EFs can operate in either Grid to Ferry mode during charging and Ferry to Grid mode during discharging.
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