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A comprehensive method for optimal power management and design of hybrid RES-based autonomous energy systems

机译：基于RES的混合型自主能源系统的最优电源管理和设计的综合方法

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摘要

The power management strategy (PMS) plays an important role in the optimum design and efficient utilization of hybrid energy systems. The power available from hybrid systems and the overall lifetime of system components are highly affected by PMS. This paper presents a novel method for the determination of the optimum PMS of hybrid energy systems including various generators and storage units. The PMS optimization is integrated with the sizing procedure of the hybrid system. The method is tested on a system with several widely used generators in off-grid systems, including wind turbines, PV panels, fuel cells, electrolyzers, hydrogen tanks, batteries, and diesel generators. The aim of the optimization problem is to simultaneously minimize the overall cost of the system, unmet load, and fuel emission considering the uncertainties associated with renewable energy sources (RES). These uncertainties are modeled by using various possible scenarios for wind speed and solar irradiation based on Weibull and Beta probability distribution functions (PDF), respectively. The differential evolution algorithm (DEA) accompanied with fuzzy technique is used to handle the mixed-integer nonlinear multi-objective optimization problem. The optimum solution, including design parameters of system components and the monthly PMS parameters adapting climatic changes during a year, are obtained. Considering operating limitations of system devices, the parameters characterize the priority and share of each storage component for serving the deficit energy or storing surplus energy both resulted from the mismatch of power between load and generation. In order to have efficient power exploitation from RES, the optimum monthly tilt angles of PV panels and the optimum tower height for wind turbines are calculated. Numerical results are compared with the results of optimal sizing assuming pre-defined PMS without using the proposed power management optimization method. The comparative results present the efficacy and capability of the proposed method for hybrid energy systems.
机译：电源管理策略（PMS）在优化设计和有效利用混合能源系统中起着重要作用。混合系统可提供的功率和系统组件的整体寿命受PMS的影响很大。本文提出了一种确定混合能源系统（包括各种发电机和存储单元）的最优PMS的新方法。 PMS优化与混合系统的大小调整过程集成在一起。该方法在离网系统中具有数个广泛使用的发电机的系统上进行了测试，包括风力涡轮机，光伏面板，燃料电池，电解槽，氢罐，电池和柴油发电机。考虑到与可再生能源（RES）相关的不确定性，优化问题的目的是使系统的总体成本，未满足的负载和燃料排放最小化。通过分别基于Weibull和Beta概率分布函数（PDF）使用风速和太阳辐射的各种可能情景对这些不确定性进行建模。结合模糊技术的差分进化算法（DEA）用于处理混合整数非线性多目标优化问题。获得了最佳解决方案，包括系统组件的设计参数和适应一年中气候变化的每月PMS参数。考虑到系统设备的操作局限性，这些参数表征了用于服务于赤字能量或存储剩余能量的每个存储组件的优先级和份额，这都是由负载和发电之间的功率不匹配导致的。为了从RES获得有效的电力利用，计算出了光伏板的最佳每月倾斜角和风力涡轮机的最佳塔高。在不使用建议的电源管理优化方法的情况下，将数值结果与假定预定义PMS的最佳尺寸调整结果进行比较。比较结果表明了该方法在混合能源系统中的功效和能力。

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  • 来源
    《Renewable & Sustainable Energy Reviews》 |2012年第3期|p.1577-1587|共11页
  • 作者

    S. Abedi; A. Alimardani; G.B. Gharehpetian; G.H. Riahy; S.H. Hosseinian;

  • 作者单位

    Renewable Energy Lab, National Center of Excellence in Power Engineering, Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box: 15875-4473,424 Hafez Ave.. Tehran, Iran;

    National Center of Excellence in Power Engineering, Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box: 15875-4413, 424 Hafez Ave., Tehran, Iran;

    National Center of Excellence in Power Engineering, Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box: 15875-4413, 424 Hafez Ave., Tehran, Iran;

    Renewable Energy Lab, National Center of Excellence in Power Engineering, Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box: 15875-4473,424 Hafez Ave.. Tehran, Iran;

    National Center of Excellence in Power Engineering, Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box: 15875-4413, 424 Hafez Ave., Tehran, Iran;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    hybrid energy systems; optimum power management strategy; differential evolution algorithm; fuzzy multi-objective optimization; resource uncertainty;

    机译：混合能源系统;最佳电源管理策略;差分进化算法;模糊多目标优化;资源不确定性;

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