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Optimal capacity allocation of standalone wind/solar/battery hybrid power system based on improved particle swarm optimisation algorithm

机译:基于改进粒子群算法的风电/太阳能/电池混合动力系统最优容量分配

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摘要

A standalone wind/solar/battery hybrid power system, making full use of the nature complementarity between wind and solar energy, has an extensive application prospect among various newly developed energy technologies. The capacity of the hybrid power system needs to be optimised in order to make a tradeoff between power reliability and cost. In this study, each part of the wind/solar/battery hybrid power system is analysed in detail and an objective function combining total owning cost and loss of power supply probability is built. To solve the problems with non-linearity, complexity and huge computation, an improved particle swarm optimisation (PSO) algorithm is developed, which integrates the taboo list to broaden the search range and introduces 'restart' and 'disturbance' operation to enhance the global searching capability. The simulation results indicate that the proposed algorithm is more stable and provides better results in solving the optimal allocation of the capacity of the standalone wind/solar/battery hybrid power system compared with the standard PSO algorithm.
机译:充分利用风能和太阳能之间的自然互补性的独立的风/太阳能/电池混合动力系统,在各种新开发的能源技术中具有广阔的应用前景。为了在功率可靠性和成本之间进行权衡,需要优化混合动力系统的容量。在这项研究中,对风/太阳能/电池混合动力系统的每个部分进行了详细分析,并建立了将总拥有成本与供电概率损失相结合的目标函数。为了解决非线性,复杂性和计算量大的问题,开发了一种改进的粒子群优化(PSO)算法,该算法集成了禁忌列表以扩大搜索范围,并引入了“重新启动”和“干扰”操作以增强全局搜索能力。仿真结果表明,与标准的PSO算法相比,该算法更稳定,在解决独立的风/太阳能/电池混合动力系统容量优化分配方面提供了更好的结果。

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  • 来源
    《Renewable Power Generation, IET》 |2013年第5期|1-1|共1页
  • 作者

    Wang; J.; Yang; F.;

  • 作者单位

    Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, People's Republic of China|c|;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 入库时间 2022-08-17 13:27:58

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