Rajib Baran Roy, Sanath Alahakoon, Piet Janse Van Rensburg, Shantha Jayasinghe Arachchillage
{"title":"Impact analysis on distribution network due to coordinated electric ferry charging","authors":"Rajib Baran Roy, Sanath Alahakoon, Piet Janse Van Rensburg, Shantha Jayasinghe Arachchillage","doi":"10.1049/esi2.12165","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"6 4","pages":"638-663"},"PeriodicalIF":1.6000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.12165","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Energy Systems Integration","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/esi2.12165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
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.
海运业是海洋生态系统中温室气体的重要排放源,促使全球转向可再生动力电动船舶,其中能源储存至关重要。作者以澳大利亚昆士兰州的格拉德斯通码头为例,研究了在当地配电网络上协调电动渡轮(EFs)充电的潜在后果。利用OpenDSS软件进行潮流分析,作者利用实际负载数据,模拟了一个由四个电池储能系统(BESSs)代表拟议充电站的网络。作者讨论了通过集成存储控制器来优化BESS充放电动态对母线电压、负载电流和功率流的影响。基于MATLAB simulink的BESS动态模型的动态链接库(Dynamic Link Library, DLL)与OpenDSS环境链接,以复制实际的电动轮渡存储。此外,用户用Python编写的DLL由存储控制器根据负载需求和BESS充电状态来调节BESS充放电,以确保网络内的有效运行。将不包含bess的电网潮流结果(称为基准情况)与协调模式下的结果进行相对比较。潮流分析表明,与可变负载的基本情况相比,母线电压上升约1%-1.5%,而负载电流消耗下降约2%-2.5%。选定的线路和变压器保持一致的功率流。值得注意的是,可以观察到总功耗和损耗的减少,特别是在负载需求增加80%的情况下。研究结果表明,基于储能控制器的协同模式能够有效地管理电池储能系统的充放电需求。此外,存储控制器确保系统参数保持在允许的范围内。bess在高峰时段对实功率和无功功率的支持验证了它们作为测试网络的削峰器的作用,这表明EFs可以在充电期间以电网到轮渡模式运行,也可以在放电期间以轮渡到电网模式运行。