Power system adequacy assessment is of great significance to the planning and construction of a power system. The traditional single probabilistic indicator assessment method can no longer meet the needs of power system adequacy assessment with the increasing penetration rate of new energy, the complexity of scenarios, and the diversification of shortage events. First, the shortage events are equated to the maximum shortage of power, and based on an improved least squares method, the characteristic points of the shortage event partition are fitted, and a multi-indicator system for the shortage event set hierarchical classification of the adequacy is constructed. Then, multiple random shortage sample datasets are generated based on the Monte Carlo method. The global weights of the indicators in each partition are determined combined with the improved AHP-EW-TOPSIS method. Also a comprehensive score landing curve is obtained. Finally, the judgment interval of the comprehensive evaluation results is constructed according to the score landing curve. The algorithm is simulated and verified based on the actual operational data of a city, and the results show that the proposed method can combine the subjective requirements and the objective characteristics of different scales of adequacy events to obtain more comprehensive and transparent adequacy assessment results.