A heuristic best-fit clustering approach for remote metering smart grid networks

Smart grid is a term referring to the next generation power grid in which the electricity distribution and management is upgraded by incorporating advanced two-way communications and pervasive computing capabilities for improved control, efficiency, reliability and safety. The paper proposes a heuristic best-fit clustering approach to obtain the minimum number and location of powerful nodes to fulfill the connectivity requirement of a given smart meters network. The contribution of the work includes the implementing of the novel heuristic best-fit clustering approach to obtain the optimal solution (the least number and location of the local data centres need to be built) for a smart meter network which has arbitrary number of smart meters with arbitrary transmission range in each smart meter. The simulation results demonstrate that the approach could efficiently obtain the optimal result, the connectivity of the smart meter network could be fulfilled with minimum number of the powerful nodes.