Evolutionary Aggregation Approach for Multihop Energy Metering in Smart Grid for Residential Energy Management

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.