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Optimal scheduling of intelligent parking lot using interval optimization method in the presence of the electrolyser and fuel cell as hydrogen storage system

机译:电解槽和燃料电池作为储氢系统的区间优化方法对智能停车场的优化调度

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These days, a new concept called intelligent parking lot (IPL) has been extensively paid consideration to be used in power system industry. Using charge/discharge of electric vehicles (EV), IPLs attempt to exchange power with the upstream grid. In addition to IPL, studied model involves non-renewable and renewable units such as wind turbine, photovoltaic (PV) system, local dispatchable generator (LDG) like micro-turbine and hydrogen storage system (HSS) which are used all together to satisfy energy demand. In this work, optimal scheduling of an IPL has been studied under time-of-use (TOU) rate of demand response program (DRP) in which price of upstream gird is set to be uncertain which uncertainty is modeled via interval optimization technique. This technique trans- forms uncertainty based model into a deterministic multi-objective model with deviation and average costs as the inconsistency objective functions. Then, applying epsilon-constraint technique and fuzzy approach, mentioned multi-objective problem is solved. Obtained Pareto results as well as selected trade-off results in various case studies have been compared to prove efficiency of employed techniques. Obtained results revealed that due to positive influence of DRP, increase of average cost of IPL has been reduced up to 2.46% while deviation cost of IPL has been decreased up to 12.49%. (C) 2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
机译:如今,人们广泛考虑了一种称为智能停车场(IPL)的新概念,可用于电力系统行业。 IPL使用电动汽车(EV)的充电/放电来尝试与上游电网交换电力。除IPL之外,研究模型还涉及不可再生和可再生单元,例如风力涡轮机,光伏(PV)系统,像微型涡轮机这样的本地可调度发电机(LDG)和储氢系统(HSS),它们一起用于满足能源需求需求。在这项工作中,已经研究了使用时间(TOU)需求响应程序(DRP)下IPL的最佳调度,其中上游网格的价格设置为不确定,哪些不确定性是通过间隔优化技术建模的。该技术将基于不确定性的模型转换为确定性的多目标模型,其中偏差和平均成本为不一致的目标函数。然后,运用ε约束技术和模糊方法,解决了所提到的多目标问题。已比较了各种案例研究中获得的帕累托结果以及选定的权衡结果,以证明所采用技术的效率。所得结果表明,由于DRP的积极影响,IPL的平均成本降低了2.46%,而IPL的偏差成本降低了12.49%。 (C)2019氢能出版物有限公司。由Elsevier Ltd.出版。保留所有权利。

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