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首页> 外文会议>PRICAI'98 : Topics in artificial intelligence >Computational Intelligence Techniques for Short Term Generation Scheduling in a Hybrid Energy System
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Computational Intelligence Techniques for Short Term Generation Scheduling in a Hybrid Energy System

机译：混合能源系统中短期发电调度的计算智能技术

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摘要

An application of computational intelligence techniques to the optimisation of a hybrid energy system operational cost is reported in this paper. The hybrid energy system is an example of the Remote Area Power Supply (RAPS) systems used in many countries in the Pacific Rim. A hybrid energy system typically comprises of a diesel generator, solar panels and a battery bank. It is used in areas where the main electricity supply grids are unavailable. In this study, a fuzzy logic algorithm is used to determine the initial generator operational schedule and the battery discharge-charge schedules for the next 24-hour period. A genetic algorithm is then used to find an optimum solution with minimal generation cost. Simulation of the algorithm has been carried on a system operating at a remote site in the Northern Territory, Australia. An average saving of 10% in fuel cost was demonstrated in the case study.
机译：本文报道了计算智能技术在混合能源系统运行成本优化中的应用。混合能源系统是环太平洋许多国家/地区使用的偏远地区电源（RAPS）系统的一个示例。混合能源系统通常包括柴油发电机，太阳能电池板和电池组。它用于主要供电网络不可用的区域。在这项研究中，使用模糊逻辑算法确定下一个24小时周期内的初始发电机运行时间表和电池放电时间表。然后，使用遗传算法找到生成成本最小的最佳解决方案。已经在澳大利亚北领地的远程站点上运行的系统上对算法进行了仿真。案例研究表明，平均可节省10％的燃料成本。

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  • 来源
  • 会议地点 Singapore(SG);Singapore(SG)
  • 作者

    C.C. Fung; V. Iyer; C. Maynard;

  • 作者单位

    School of Electrical and Computer Engineering Curtin University of Technology, GPO Box U1987, Perth 6845, Western Australia;

    School of Electrical and Computer Engineering Curtin University of Technology, GPO Box U1987, Perth 6845, Western Australia;

    School of Electrical and Computer Engineering Curtin University of Technology, GPO Box U1987, Perth 6845, Western Australia;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化系统理论;
  • 关键词

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