Future electricity distribution networks with mass deployment of network equipment sensors and instrumentation, millions of smart meters, small-scale embedded generation, and responsive load will generate vast amounts of data requiring near to real-time analysis. So-called cloud and grid computing will enable scalable data mining, feature extraction, and near to real-time state estimation. These and other HPC tools and techniques have been recently developed to cost-effectively solve large scale computational challenges in areas such as genomics, biomedicine, particle physics and other major scientific and engineering fields that require similarly scalable communications, computation and data analysis. Based on such recent success it is the aim of this proposal to develop a new generation of distribution network management systems that exploit novel near to real-time HPC solutions with inherent security and intelligent communications for smart distribution network operation and management. Cost effective scalable HPC solutions will be developed and initially demonstrated for realistic distribution network data traffic and management scenarios via off-line field trials involving several distribution network owners and operators.