{"title":"Pareto based optimal sizing and energy storage mix in ship power systems","authors":"A. Elsayed, N. Elsayad, O. Mohammed","doi":"10.1109/IAS.2016.7731851","DOIUrl":null,"url":null,"abstract":"The weight of onboard equipment represents a major concern in transportation systems. In ship power systems, in addition to weigh concerns, some loads are frequently demanding high power for short time durations. Thus, adding energy storage is mandatory to smooth the effect of these loads. This paper introduces a methodology based on Pareto concept to optimally size and select the mix of different energy storage technologies. The problem is formulated as a multi-objective Optimization (MOO), where two objectives are considered. The first is to minimize the voltage fluctuations on the buses and the second is to minimize the total weight of the Energy Storage System (ESS). Three candidate energy storage technologies were considered; lead acid, lithium ion batteries and Super-capacitors. The Pareto Front (PF) was obtained using Non-dominated Sorting Genetic Algorithms II (NSGA-II). The results show the feasibility and computational efficiency of the proposed methodology.","PeriodicalId":306377,"journal":{"name":"2016 IEEE Industry Applications Society Annual Meeting","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Industry Applications Society Annual Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAS.2016.7731851","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
The weight of onboard equipment represents a major concern in transportation systems. In ship power systems, in addition to weigh concerns, some loads are frequently demanding high power for short time durations. Thus, adding energy storage is mandatory to smooth the effect of these loads. This paper introduces a methodology based on Pareto concept to optimally size and select the mix of different energy storage technologies. The problem is formulated as a multi-objective Optimization (MOO), where two objectives are considered. The first is to minimize the voltage fluctuations on the buses and the second is to minimize the total weight of the Energy Storage System (ESS). Three candidate energy storage technologies were considered; lead acid, lithium ion batteries and Super-capacitors. The Pareto Front (PF) was obtained using Non-dominated Sorting Genetic Algorithms II (NSGA-II). The results show the feasibility and computational efficiency of the proposed methodology.
机载设备的重量是运输系统的一个主要问题。在船舶动力系统中，除了重量问题外，一些负载经常需要短时间内的高功率。因此，增加能量存储是必须的，以平滑这些负载的影响。本文介绍了一种基于帕累托概念的方法来优化不同储能技术的规模和选择组合。该问题被表述为一个多目标优化(MOO)，其中考虑了两个目标。首先是尽量减少母线上的电压波动，其次是尽量减少储能系统的总重量。考虑了三种候选储能技术;铅酸、锂离子电池和超级电容器。采用非支配排序遗传算法II (NSGA-II)获得Pareto Front (PF)。结果表明了该方法的可行性和计算效率。
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