Carbon emissions from electricity production activities account for a significant proportion of total global emissions. Therefore, the power industry has become a key stakeholder in achieving "carbon emission reduction" goals. By employing a quantitative comprehensive evaluation approach to assess national power development levels, we can not only clearly delineate the development trajectory of various countries in the power sector but also more accurately identify the gaps between China and other countries in power development. This paper conducts a comprehensive evaluation and research on national power development levels and proposes an evaluation method for power development levels based on an improved multi-objective particle swarm optimization (MOPSO) algorithm to optimize the projection pursuit model. Firstly, an improved MOPSO algorithm is proposed. Secondly, two projection pursuit models are established, and further optimized using the improved MOPSO algorithm to obtain the optimal Pareto solution set for the projection vectors. Finally, a fuzzy comprehensive evaluation is used to obtain the optimal weight compromise solution, which is then substituted into the prospect theory model to derive comprehensive scores for the power development levels of various countries. Based on these scores, an objective ranking of the power development levels of various countries is conducted. The proposed method is validated using an actual dataset of national power development levels. The experimental results demonstrate that this method can effectively rank national power development levels, with evaluation accuracy superior to existing evaluation methods for power development levels.