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Multi-Objective Particle Swarm optimal sizing of a renewable hybrid power plant with storage

机译:带存储的可再生混合动力电厂的多目标粒子群优化大小

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This paper features a Multi-Objective Particle Swarm Optimization for a power plant integrated in a micro grid. The plant modeling is flexible and can be set up for a wide range of sources, storages and loads. The model contains 12 parameters representing the size of each component which are modeled with power dependent efficiencies. The optimization goals are to reduce the annualized cost of system and the imported energy without failing to supply the load. The study is carried out in two locations (Tilos and Ajaccio) to show the problem dependence on the meteorological conditions. As a result, a pattern stands out for each site with a preferred source and a plant configuration according to the energetic autonomy wanted. (C) 2018 Elsevier Ltd. All rights reserved.
机译:本文对集成在微电网中的发电厂进行了多目标粒子群优化。工厂建模非常灵活,可以针对各种来源,存储和负载进行设置。该模型包含12个参数,这些参数代表每个组件的大小,并通过功率相关效率进行建模。优化目标是在不负担负荷的情况下降低系统的年度成本和进口能源。该研究在两个地点(蒂洛斯州和阿雅克修州)进行,以显示问题对气象条件的依赖性。结果,根据所需的精力充沛的自主权,每个站点都有一个模式,具有首选的来源和工厂配置。 (C)2018 Elsevier Ltd.保留所有权利。

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