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首页> 外文期刊>Energy Conversion & Management >Short-term hydro-thermal-wind complementary scheduling considering uncertainty of wind power using an enhanced multi-objective bee colony optimization algorithm
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Short-term hydro-thermal-wind complementary scheduling considering uncertainty of wind power using an enhanced multi-objective bee colony optimization algorithm

机译:改进的多目标蜂群优化算法,考虑风电不确定性的短期水热风互补调度

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摘要

This paper presents a short-term economic/environmental hydro-thermal-wind complementary scheduling (HTWCS) system considering uncertainty of wind power, as well as various complicated non-linear constraints. HTWCS system is formulated as a multi-objective optimization problem to optimize conflictive objectives, i.e., economic and environmental criteria. Then an enhanced multi-objective bee colony optimization algorithm (EMOBCO) is proposed to solve this problem, which adopts Elite archive set, adaptive mutation/selection mechanism and local searching strategy to improve global searching ability of standard bee colony optimization (BCO). Especially, a novel constraints-repairing strategy with compressing decision space and a violation-adjustment method are used to handle various hydraulic and electric constraints. Finally, a daily scheduling simulation case of hydro-thermal-wind system is conducted to verify feasibility and effectiveness of the proposed EMOBCO in solving HTWCS problem, The simulation results indicate that the proposed EMOBCO can provide lower economic cost and smaller pollutant emission than other method established recently while considering various complex constraints in HTWCS problem. (C) 2016 Elsevier Ltd. All rights reserved.
机译:本文提出了一种考虑风电不确定性以及各种复杂非线性约束的短期经济/环境水热热风互补调度(HTWCS)系统。 HTWCS系统被公式化为一个多目标优化问题,以优化冲突目标,即经济和环境标准。然后提出了一种改进的多目标蜂群优化算法(EMOBCO),该算法采用Elite档案集,自适应突变/选择机制和局部搜索策略,提高了标准蜂群优化(BCO)的全局搜索能力。尤其是,使用一种具有压缩决策空间的新颖约束修复策略和一种违规调整方法来处理各种液压和电气约束。最后,以水热风系统的日调度仿真为例,验证了该EMOBCO解决HTWCS问题的可行性和有效性,仿真结果表明,与其他方法相比,该EMOBCO具有较低的经济成本和较小的污染物排放量。在考虑HTWCS问题中的各种复杂约束的基础上建立的。 (C)2016 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Energy Conversion & Management》 |2016年第9期|116-129|共14页
  • 作者单位

    Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Hubei, Peoples R China|Huazhong Univ Sci & Technol, Hubei Key Lab Digital Valley Sci & Technol, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Hubei, Peoples R China|North China Elect Power Univ, State Key Lab Alternate Elect Power Syst Renewabl, Beijing 102206, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Hubei, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Hydro-thermal-wind system; Uncertainty of wind power; Bee colony optimization; Local searching method; Constraints-repairing strategy;

    机译:水热风系统;风力发电的不确定性;蜂群优化;局部搜索法;约束修复策略;

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