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首页> 外文期刊>Engineering Applications of Artificial Intelligence >Application of fuzzy decision-making based on INSGA-Ⅱ to designing PV-wind hybrid system
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Application of fuzzy decision-making based on INSGA-Ⅱ to designing PV-wind hybrid system

机译:基于INSGA-Ⅱ的模糊决策在风电混合系统设计中的应用。

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摘要

This paper addresses the attuned design of wind and photovoltaic (PV) hybrid generation system to supply office buildings. The main target of this design is to minimize the annualized cost of the hybrid system, environmental cost related to pollutant gas emissions avoided due to the use of the hybrid generation system, and index of loss of power supply probability. System costs consist of investment, replacement, operation, and maintenance cost of each component The problem of design is formulated as a multi-objective optimization issue and solved by improved non-dominated sorting genetic algorithm-Ⅱ (INSGA-Ⅱ). The presented technique intends to offer the optimal number of system devices such that the economic and environmental profits achieved during the systems operational lifetime period are maximized. Optimizations of decision variables are the optimal number of photovoltaic modules, wind turbines, inverters, charge controllers, and storage batteries. A decision-making methodology based on fuzzy decision-making (FDM) is applied for finding the best compromise solution from the set of Pareto-optimal solutions obtained by INSGA-Ⅱ technique. Two frameworks are considered for the design procedure of hybrid generation system. In the first framework, a two-objective optimization problem is developed based on system cost and environmental cost The second framework is formulated based on three objective functions: system cost; environmental cost; and reliability index. The proposed method has been conducted on four office buildings in city of Ardabil. The comparative analysis shows the efficiency of the proposed method.
机译:本文介绍了风能和光伏(PV)混合发电系统的优化设计,以为办公楼供电。该设计的主要目标是最大程度地降低混合动力系统的年化成本,与使用混合动力发电系统所避免的与污染物排放相关的环境成本以及电源损失概率指标。系统成本包括每个组件的投资,更换,运行和维护成本。设计问题被表述为多目标优化问题,并通过改进的非支配排序遗传算法-Ⅱ(INSGA-Ⅱ)加以解决。提出的技术旨在提供最佳数量的系统设备,以使在系统运行寿命期内实现的经济和环境利润最大化。决策变量的优化是光伏模块,风力涡轮机,逆变器,充电控制器和蓄电池的最佳数量。运用基于模糊决策(FDM)的决策方法从INSGA-Ⅱ技术获得的帕累托最优解集中找到最佳折衷解。混合发电系统的设计过程考虑了两个框架。在第一个框架中,根据系统成本和环境成本开发了一个两目标优化问题。第二个框架是基于三个目标函数制定的:系统成本;环境成本;和可靠性指标。拟议的方法已在Ardabil市的四栋办公楼上进行。对比分析表明了该方法的有效性。

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