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基于改进RWCE算法的海岛微电网双层优化方法

Double-layer optimization of island micro-grid based on improved RWCE algorithm

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【作者】 郭佳; 潘磊; 苏莽; 谢宜轩; 肖子平; 崔国民;

【Author】 GUO Jia;PAN Lei;SU Mang;XIE Yixuan;XIAO Ziping;CUI Guomin;School of Energy and Power Engineering, University of Shanghai for Science and Technology;

【通讯作者】 崔国民;

【机构】 上海理工大学能源与动力工程学院;

【摘要】 建设兼顾电力和淡水供应的分布式综合能源系统,提高系统的经济性和可靠性,促进可再生能源的消纳,对海岛开发具有重要意义。针对融合海水淡化装置的海岛微电网系统,构建了容量配置与运行调度的双层优化模型,以年综合费用最低为目标函数,综合考虑发电功率、负荷可靠性、可再生能源丢弃率等约束条件,并通过跟踪逐时净负荷进行运行调节,采用带有高精度精细搜索策略的改进强制进化随机游走(RWCE)算法求解。结果表明,基于改进RWCE算法的微电网双层优化模型,实现了系统容量配置与运行调度的同步优化,能够平衡全局搜索与局部搜索能力,提高搜索精度,避免早熟收敛,保护最优解,获得更优的规划方案。将海水淡化作为一种可时移的负荷纳入“风-光-柴-储”微电网系统,可有效提高对可再生能源发电的消纳能力,显著降低综合费用。

【Abstract】 It is of great significance to island development by building a distributed integrated energy system with power and fresh water supply, which can improve the system economy and reliability and promote the penetration of renewable energy. For the island microgrid system integrated with seawater desalination equipments, a double-layer optimization model for capacity configuration and operation scheduling was developed. The annual comprehensive cost was used as the objective function. The constraints such as power generation power, load reliability, and renewable energy discard rate were comprehensively considered. The operation was adjusted by tracking the hourly net load. The improved random walk algorithm with compulsive evolution(RWCE) algorithm was used to solve the problem with high-precision fine search strategy. Results show that the double-layer optimization model of microgrid based on the improved RWCE algorithm can achieve the synchronous optimization of system capacity configuration and operation schedule, balance global and local search capabilities, improve search accuracy, avoid premature convergence, protect the optimal solution, and get better planning scheme. Incorporating seawater desalination into the "wind-solar-diesel-storage" microgrid system as a time-shiftable load can effectively improve the ability to absord the renewable energy power and significantly reduce the comprehensive cost.

  • 【文献出处】 能源研究与信息 ,Energy Research and Information , 编辑部邮箱 ,2024年04期
  • 【分类号】TM73;TP18
  • 【下载频次】32
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