Critical Cluster Mining and Optimal Allocation for Power Grid Projects Based on Complex Networks and Multidimensional Metrics

With the increasing complexity of grid project systems, it is difficult for an individual project management perspective to meet the macro management needs of the project, unapplicable to overall project layout management. However, the current grid project portfolio management (PPM) configuration lacks systematic methodological support, and the synergistic relationships between projects in terms of resources, strategy, and other aspects have not been effectively utilized, making it difficult to optimize the effectiveness of management and investment schemes. Therefore, in this paper, we propose a method called CNMI-PGPC, which combines complex networks and multidimensional indicators to explore the correlations among grid projects, deeply mines the key grid project clusters and the optimal allocation strategy, and is devoted to improving the comprehensive efficiency of grid projects. The methodology was validated on data derived from the Grid Multi-Category Reserve Project (including grid infrastructure, production technology improvement, and grid digitization). The results show that the proposed method can effectively provide a scientific basis for configuring and managing grid projects, support the preferential decision-making tasks of projects, and optimize the layouts of grid projects. We shift from single-project optimization to global synergy, quantify the comprehensive benefits of the project team in terms of economics, strategy, and other dimensions, bridge the gap between the previous individual project assessment perspectives, and provide a systematic decision-making basis for grid project portfolio planning.