## 1 Introduction  
At present, in order to solve the problem of environmental protection and energy exhaustion, renewable clean energy has a high proportion of access. This also brings many new challenges, such as the low energy density of new energy, the need for suitable sites for high-power power generation, power instability, and so on. The microgrid technology provides an important technical direction for the efficient use of these new energy sources [1; 2; 3; 4]. However, in the evaluation of microgrid planning, besides satisfying certain reliability of power supply, it also requires comprehensive consideration of investment costs, power quality, and environmental protection and other factors. Therefore, for such a planning problem with a large number of uncertainties, it is necessary to establish a comprehensive technical and economic evaluation system. In the aspect of comprehensive evaluation methods, traditional comprehensive evaluation methods mostly use subjective expert evaluation decision-making methods based on analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method. In [5] the authors present a risk-based vulnerability assessment method for microgrids. It uses AHP and the fuzzy comprehensive evaluation method to calculate the comprehensive vulnerability of microgrids. This method relies too much on the subjective judgment of experts to determine the evaluation weight and lacks sufficient objectivity. In [6] the authors use a multi-operator model to construct a hierarchical fuzzy evaluation model. Using the idea of analytic hierarchy process and fuzzy evaluation, the weight of the index system is analyzed, and the calculation method of the index is obtained. This method still has the problem of overweight subjectivity. The multi-operator model cannot fundamentally solve the shortcoming of the lack of objectivity of the fuzzy evaluation method. In [7] the authors propose a comprehensive evaluation index system of an AC and DC microgrid based on the Improved Analytic Hierarchy process. However, the improved analytic hierarchy process (AHP) only improves the method of judgment matrix generation. In essence, it still adopts the subjective method of AHP, which has the disadvantage of strong subjectivity of evaluation index weight. In [8] the authors use the analytic hierarchy process and fuzzy comprehensive evaluation method to determine the weight of the evaluation index. In [9] the authors construct the fuzzy evaluation vector of power grid risk by the method of fuzzy comprehensive evaluation. Then, the grid risk level is output according to the principle of maximum membership degree. In [10] the authors establish a fuzzy comprehensive evaluation model for the upgrade demand of smart grid functional form. Then, it uses the fuzzy comprehensive evaluation method to determine the index weight. In [11] the authors establish the evaluation model of power grid equipment utilization rate by using an analytic hierarchy process. In [12] the authors establish a comprehensive evaluation index system for power grid science and technology projects by using the principle of analytic hierarchy process. All the methods used in the above literature are subjective evaluation methods. Although there are some improvements in the process of implementation, it is still unable to overcome the problem of insufficient objectivity of subjective methods in determining the weight of indicators. In order to solve the problem of insufficient objectivity of traditional methods, objective empowerment methods have been introduced into the comprehensive evaluation of planning schemes in recent years. In [13] the authors combine information entropy theory with principal component analysis theory and apply this method to comprehensive evaluation of thermal power units. It establishes a comprehensive evaluation model of unit state based on information entropy and principal component analysis.