A Robust Optimization-Based Planning and Allocation Method for Smart Grid Technological Transformation Investment Considering Operational Uncertainties and Hierarchical Evaluation

With the continuous operation of power grid equipment, technological transformation investment has become a crucial means to ensure grid safety and enhance grid intelligence. However, the planning and allocation of investment for technological transformation are influenced by various uncertain factors such as policies, social economy, and corporate profits. Therefore, scientifically and rationally planning the future investment scale is essential for ensuring the sustainable development of power grid enterprises. This paper proposes a planning and allocation method for smart grid technological transformation investment, incorporating both Analytic Hierarchy Process (AHP) and Robust Optimization. First, a comprehensive evaluation index system is constructed, evaluating investment demand from the dimensions of grid assets, regional economic development, and corporate operational benefits. The AHP is used to determine the weights of each indicator, and comprehensive scores for technological transformation investment demand in different regions are calculated. Next, considering the impact of uncertainties on investment distribution, Robust Optimization is applied to adjust the initial allocation plan to ensure the stability and optimal outcome under worst-case scenarios. Empirical analysis using data from 11 county-level units of a municipal power grid company demonstrates that the proposed method significantly improves the accuracy of investment allocation and enhances the robustness of planning. It effectively addresses uncertainties in the external environment and ensures optimal investment distribution for power grid technological transformation. This method provides more scientific and rational decision support for power grid companies in the face of complex and changing external condition.