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首页> 外文期刊>Polish Journal of Environmental Studies >Optimizing Hierarchical Power Distribution of Multiple Local Energy Network Systems in Grid-Connected Mode
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Optimizing Hierarchical Power Distribution of Multiple Local Energy Network Systems in Grid-Connected Mode

机译:并网模式下多个本地能源网络系统的分层配电优化

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摘要

This paper focuses on the hierarchical power distribution optimization of multiple local energy network (LEN) systems that are formed in three levels and can be operated in six typical modes. The decentralized optimal model for each LEN (the first level) and LENs (the second level) as well as the concentrated optimal model for the top level of the system are built, respectively. For each LEN, all the basic unities such as power generated by wind turbines and photovoltaic, and their upper nodes are considered. For LENs, the aggregated results (e.g., supply-demand requirements) from each LEN are dispatched. Furthermore, in the concentrated optimal control model (the third level), the ultimate supply-demand requirements of networked LENs together with other resources such as electric vehicles are considered. Due to the large number of control resources, the whole system is formulated as a large-scale global optimization (LSGO) problem. The self-adaptive differential evolution with neighborhood search method (SaNSDE) modified with the Lagrange multiplier method is used to solve the problem. The algorithm is firstly examined on 10 constrained benchmark functions, then it is applied to our problem. Experimental results show that the proposed model and algorithm are effective and efficient.
机译:本文着重于在三个级别上形成并可以在六种典型模式下运行的多个局部能源网络(LEN)系统的分层配电优化。分别建立了每个LEN(第一级)和LEN(第二级)的分散式最优模型,以及系统顶层的集中式最优模型。对于每个LEN,都将考虑所有基本单位,例如风力涡轮机和光伏发电所产生的能量,及其上层节点。对于LEN,将调度每个LEN的汇总结果(例如,供需需求)。此外,在集中式最优控制模型(第三级)中,考虑了网络化LEN的最终供需需求以及其他资源,例如电动汽车。由于大量控制资源,整个系统被表述为大规模全局优化(LSGO)问题。用拉格朗日乘数法修正的自适应差分进化邻域搜索法(SaNSDE)解决了该问题。该算法首先在10个约束基准函数上进行了检验,然后将其应用于我们的问题。实验结果表明,该模型和算法是有效的。

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