Research on Investment Decision Model of Power Grid Engineering Based on Hybrid Multi Attribute Decision Making Technology

Under the context of the "dual carbon" goals promoting the construction of new power systems, investment decision-making for power grid engineering needs to consider multi-objective collaborative optimization, dynamic risk prevention, and multi-dimensional benefit balancing. This paper proposes a hybrid multi-attribute decision-making (MADM) model by constructing a three-dimensional evaluation indicator system that covers planning effectiveness, investment plans, and investment benefits. It combines the Best Worst Method (BWM) and Anti-Entropy Weight (AEW) methods for subjective and objective weight assignment, respectively, and introduces the gray relational projection method to quantitatively evaluate alternative solutions. The study shows that the model significantly strengthens the core position of technological benefits and economic indicators through dynamic integration of subjective and objective weights, while also balancing planning coordination and execution efficiency. Case study verification demonstrates that the model can effectively quantify the priority ranking of different solutions and enhance adaptability to technological iterations, policy adjustments, and resource constraints. The research provides power grid enterprises with a scientific and systematic investment decision-making tool, and expands the methodological path for the application of multi-attribute decision-making theory in the energy and power sector.