Computationally efficient modeling method for large water network analysis

Nowadays, unprecedented computing power of desktop personal computers and efficient computational methodologies, such as the global gradient algorithm (GGA), make large water distribution system modeling feasible. However, many network analysis applications, such as optimization models, require running numerous hydraulic simulations with modified input parameters. Therefore, a methodology that could reduce the computational burden of network analysis, and still provide the required model accuracy, is needed. This paper presents a matrix transformation approach to convert the classic GGA, which is implemented within the widely available freeware EPANET2, into a more computationally efficient enhanced global gradient algorithm (EGGA). The latter achieves the improved efficiency by reducing the size of the mathematical problem through the transformed topological representation of the original network model. By removing serial nodes and serial pipe-sections from the original topological representation, whilst preserving those elements both in energy and mass balance equations, EGGA provides a significant improvement to the model’s computational efficiency without forfeiting the hydraulic accuracy of the model. The computational efficiency and effectiveness of the EGGA approach is demonstrated on four examples of different real-life networks. Results show that the computational burden of the EGGA model is significantly lower than for its GGA counterpart particularly as the size of the network and/or number of service connections increases.