Computationally Efficient Modeling Method for Large Water Network Analysis

Abstract

Nowadays, the 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 can 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 EPANET 2, into a more computationally efficient enhanced global gradient algorithm (EGGA). The latter achieves 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 while preserving those elements in both energy and mass balance equations, EGGA significantly improves the model’s computational efficiency without forfeiting its hydraulic accuracy. The computational efficiency and effectiveness of the EGGA approach are demonstrated on four real-life networks. Results show that the computational burden of the EGGA model is significantly lower than that of its GGA counterpart, particularly as the size of the network and/or number of service connections increases.