The communication infrastructure is an important part to provide the reliability for energy management in the smart grid environment. With the aim of reducing the infrastructure cost for residential energy management, this article introduces a more complex multihop wireless remote metering network model. A novel evolutionary aggregation algorithm (EAA) is proposed to obtain the minimum number and locations of the local data centers (powerful nodes) in a 2-hop wireless remote metering network which has an arbitrary number of smart meters (ordinary nodes) with arbitrary transmission ranges. In the novel 2-hop EAA, the article designs and implements two novel adaptive operations (the switch operation and the shuffle operation) to improve the algorithm performance. Then the article extends the 2-hop EAA method to a more generic n -hop EAA which could obtain the optimal result in an n -hop ( n > 2) smart meter network. Comprehensive case studies and numerical statistical analyses demonstrate that the EAA could efficiently achieve the optimal results in an n -hop ( n > = 2) smart meter network environment; and the novel switch and shuffle operations could efficiently improve the performance of the evolutionary algorithm. The connectivity of the smart meter network could be fulfilled with the minimum number of the powerful nodes, from which the infrastructure cost for residential energy network could be minimized.

中文翻译：

---

用于住宅能源管理的智能电网中多跳电能计量的进化聚合方法

通信基础设施是为智能电网环境中的能源管理提供可靠性的重要部分。为了降低住宅能源管理的基础设施成本，本文介绍了一种更复杂的多跳无线远程计量网络模型。提出了一种新颖的进化聚合算法（EAA），以获取具有任意数量的智能电表（普通节点）和任意传输的2跳无线远程计量网络中本地数据中心（功能强大的节点）的最小数量和位置。范围。在新颖的2跳EAA中，本文设计并实现了两种新颖的自适应操作（切换操作和混洗操作），以提高算法性能。然后，本文将2跳EAA方法扩展为更通用的方法ñ 跳EAA可以在 ñ -跳（ ñ> 2）智能电表网络。全面的案例研究和数值统计分析表明，EAA可以有效地实现最佳结果。ñ -跳（ ñ > = 2）智能电表网络环境；并且新颖的切换和随机操作可以有效地提高进化算法的性能。智能电表网络的连通性可以通过最少数量的强大节点来实现，从而可以将住宅能源网络的基础设施成本降至最低。