Abstract: Frequent start-up and stop operation will cause repeated impact of thermal stress, mechanical stress and electrical stress on electrical equipment, and accelerate equipment aging and failure. In order to improve the operation stability of the unit, this paper designs a life cycle risk management technology based on improved genetic algorithm. This paper analyzes the damage mechanism of key electrical equipment of thermal power units under frequent start-up and shutdown conditions, and constructs a life cycle risk assessment system based on the health status of equipment. At the same time, the adaptive crossover mutation strategy, elite reservation mechanism and multi-objective optimization technology are introduced into the traditional genetic algorithm, which effectively improves the global search ability of the algorithm. The experimental results show that the proposed technology reduces the life loss and operation and maintenance cost of electrical equipment, and provides technical support for the refined operation and management of thermal power units in the electricity spot market environment.