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首页> 外文期刊>ETEP-European Transactions on Electrical Power >Fuzzy multiobjective model for distributed generation expansion planning in uncertain environment
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Fuzzy multiobjective model for distributed generation expansion planning in uncertain environment

机译:不确定环境下分布式发电计划的模糊多目标模型

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Uncertainty is one of the important factors that increase risk of exact decision makings. Although power systems behavenmore probabilistic today and system risk cannot be avoided completely, it can be evaluated and managed to an acceptablenextent in planning, design, and operation activities. This paper presents a fuzzy multiobjective model for distributedngeneration planning so that uncertainties are modeled using fuzzy numbers (trapezoidal form). The proposed fuzzy modelnis based on the risk of economic, technical, and environmental objectives as well as fuzzy values of investment andnoperation cost of DG units due to technology’s progress and fuel price fluctuations in the future. This model determines thenoptimal time, location, size, and type of DG units in distribution networks, using a multiobjective genetic algorithmn(NSGA-II). The technologies which are considered in this study are photovoltaic (PV), wind turbine (WT), fuel cell (FC),nmicroturbine (MT), gas turbine (GT), and diesel engine (DE). The proposed model is applied on a typical distributionnsystem (IEEE 37 node test feeder) to assess the efficiency of the approach. Copyright # 2010 John Wiley & Sons, Ltd.
机译:不确定性是增加精确决策风险的重要因素之一。尽管当今电力系统表现出更高的概率,并且无法完全避免系统风险,但是可以在计划,设计和操作活动中对它进行评估和管理,使其达到可接受的水平。本文提出了一种用于分布式发电规划的模糊多目标模型,以便使用模糊数(梯形形式)对不确定性进行建模。提出的模糊模型基于经济,技术和环境目标的风险,以及由于技术进步和未来燃料价格波动而导致的DG机组投资和运营成本的模糊值。然后,该模型使用多目标遗传算法n(NSGA-II)确定配电网中DG单元的最佳时间,位置,大小和类型。在这项研究中考虑的技术是光伏(PV),风力涡轮机(WT),燃料电池(FC),微型涡轮机(MT),燃气轮机(GT)和柴油发动机(DE)。所提出的模型被应用在典型的分布式系统(IEEE 37节点测试馈线)上,以评估该方法的效率。版权所有©2010 John Wiley&Sons,Ltd.

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