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Stochastic multi-objective optimization for economic-emission dispatch with uncertain wind power and distributed loads

机译：不确定风能和分布式负荷的经济排放调度的随机多目标优化

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摘要

This paper proposes a stochastic multi-objective optimization method for solving the Security-Constrained Optimal Power Flow (SCOPF) problem with uncertain wind power and distributed load variations. The dispatch objectives are formulated to not only minimize the expectation of fuel costs and the deviation of the fuel cost distribution, but also to maximize wind power penetration while also considering variations in wind speed and distributed loads. The computational complexity of the stochastic optimization is a crucial issue that is considered when using a Paired-Bacteria Optimization (PBO) algorithm, which is simpler than most Evolutionary Algorithms (EAs). This paper reports the simulation results obtained using an IEEE 30-bus system, including a comparison between the results achieved using the proposed method and those obtained from deterministic dispatch. The trade-off relationships between fuel cost, wind power penetration, and emissions are analyzed based on the Pareto set of feasible solutions resulted from PBO. This analysis allows for the determination of the optimal dispatch actions that simultaneously minimize all of the objectives while considering uncertainties in wind power and distributed loads.
机译：本文提出了一种随机多目标优化方法，用于解决具有不确定风能和分布式负荷变化的安全约束最优潮流（SCOPF）问题。制定调度目标不仅要使对燃料成本的期望和燃料成本分布的偏差最小，而且要使风能渗透率最大化，同时还要考虑风速和分布式负荷的变化。随机优化的计算复杂性是使用配对细菌优化（PBO）算法时要考虑的关键问题，该算法比大多数进化算法（EA）更简单。本文报告了使用IEEE 30总线系统获得的仿真结果，包括使用建议的方法获得的结果与从确定性调度获得的结果之间的比较。基于PBO产生的帕累托可行方案集，分析了燃料成本，风力发电渗透和排放之间的权衡关系。该分析允许确定最佳调度动作，该最佳调度动作同时将所有目标最小化，同时考虑风力和分布式负载的不确定性。

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  • 来源
    《Electric power systems research》 |2014年第11期|367-373|共7页
  • 作者

    M.S. Li; Q.H. Wu; T.Y. Ji; H. Rao;

  • 作者单位

    School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China;

    School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China,Department of Electrical Engineering and Electronics, The University of Liverpool, Liverpool L69 3GJ, UK;

    School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China;

    Electric Power Research Institute, China Southern Power Grid Company, Guangzhou 510000, 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

    Stochastic dispatch; Wind power; Paired-bacteria optimizer; Distributed loads; Emission; Multi-objective optimization;

    机译：随机调度;风力;配对细菌优化器;分布式负载;发射;多目标优化;

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