基于改进鲸鱼算法的并网型微网能量管理
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TM71

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河北省自然科学基金(E2018202282);天津市自然科学基金重点项目(19JCZDJC32100);河北省教研课题(2017GJJG020)


Grid-connected Micro-grid Energy Management Based on Improved Whale Algorithm
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    摘要:

    为解决并网型风/光/柴/储微电网的能量管理问题,以经济性和环保性为目标函数,考虑各发电设备安全稳定运行 作为约束条件,构建并网型微网容量优化配置模型;采用差分排序和差分变异的优化策略且引入levy飞行轨迹的机制来改善 标准鲸鱼算法( whale optimization algorithm, WOA)的收敛精度和收敛速度;基于所提的风-光-储-网-柴的调度策略,采用改进鲸 鱼算法求解配置模型。挑选某地一年四季4个典型日进行案例分析。结果表明:本文所提出的调度策略和配置模型具有合理 性;改进的WOA算法能够有效地解决微网能量管理问题,在全局搜索和寻优能力方面具有优势。

    Abstract:

    In order to solve the problem of energy management of grid-connected wind-solar-diesel-battery microgrid, the optimal capacity allocation model of grid-connected microgrid is constructed, taking economy and environmental protection as objective functions and considering the safe and stable operation of all power generation equipment as constraint conditions. The convergence accuracy and speed of the typical whale algorithm (WOA) were improved by using the optimization strategies of difference sorting and difference variation and introducing the Levy flight path mechanism. Based on the wind-PV-storage-grid-diesel scheduling strategy proposed in this paper, an improved whale algorithm was used to solve the configuration model. Four typical days in a certain place were selected for case analysis. The results show that the proposed scheduling strategy and configuration model are reasonable. The improved WOA algorithm can effectively solve the problem of microgrid energy management, and has advantages in global search and optimization.

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谢姿,张惠娟,刘琪,等. 基于改进鲸鱼算法的并网型微网能量管理[J]. 科学技术与工程, 2020, 20(15): 6087-6093.
Xie Zi, Zhang Huijuan, Liu Qi, et al. Grid-connected Micro-grid Energy Management Based on Improved Whale Algorithm[J]. Science Technology and Engineering,2020,20(15):6087-6093.

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历史
  • 收稿日期:2019-09-03
  • 最后修改日期:2020-06-14
  • 录用日期:2019-11-11
  • 在线发布日期: 2020-06-24
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