The two-loop thermal system of a nuclear power unit is the key part that converts thermal energy into mechanical energy and generates electricity,and it is of great significance to improve its efficiency on the basis of ensuring safety.In this regard,firstly,a mathematical model of the thermal system is established based on the heat balance method.Secondly,an improved multi-population genetic algorithm is proposed on the basis of multi-population genetic algorithm by adding parallel mechanism and collaborative strategy and combining with adaptive strategy,and its optimization-seeking performance is tested by using test function.Finally,the improved algorithm is used to optimize the thermal system under the constraints with the thermal efficiency of the unit cycle as the objective function and the return heat and reheat steam flow rate as the decision variable.The results show that the improved multi-population genetic algorithm is more efficient and has higher convergence accuracy than the standard genetic algorithm with multi-population genetic algorithm;the thermal efficiency of the unit cycle is improved by1.18%.
nuclear power thermal systemimproved multi-population genetic algorithmparameter optimizationcirculation thermal efficiency
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