Abstract: The large-scale renovation of old equipment has become an important measure to ensure the safe and stable operation of power grid, and the intelligent upgrading of circuit breakers is the focus and difficulty of equipment renovation. Aiming at the problems of complex technology suitability evaluation and difficult optimization decision in the process of intelligent upgrading of large-scale old circuit breakers, this paper designs a research method of technology suitability based on improved particle swarm optimization algorithm. The adaptability evaluation system of circuit breaker intelligent upgrading technology is constructed, and the adaptive inertia weight adjustment strategy, dynamic learning factor and chaotic disturbance mechanism are introduced into the traditional particle swarm optimization algorithm to improve the accuracy and efficiency of the optimization solution. The algorithm is used to solve the optimization model, and the intelligent decision-making and optimal configuration of the upgrading scheme are realized. The results show that the proposed method significantly improves the efficiency of resource allocation, and has important theoretical significance and engineering application value.