## 4 Network Reconstruction Process Based on MPGA  
During network reconstruction, multiple combinations of switches need to be provided and optimized. For a floating nuclear power plant, the optimal solution is expected to be obtained in a short time. However, an algorithm based on a single evolutionary population cannot achieve cooperative optimization among the search population, and the result may only be locally optimal.  
MPGA [32] is used in this paper. For different populations, the same objective function is set. Based on single-population genetic evolution, the crossover rate and the mutation rate are different for different populations, but the values are fixed. Thus, the optimal solution from different solution spaces can be searched. The population migration operator is used for regular information exchange between different populations to realize the collaborative optimization. Based on MPGA, the operation steps of the power system network reconstruction are as follows:  
(1) Generate the initial population. According to the operation states of the system before and after the fault, the switches that are involved in the reconstruction are determined, then the initial switch state is determined and multiple populations are generated based on the random strategy. The 0-1 encoding method is used to describe the switch state, and 0-1 state is randomly generated for the switches that can participate in the network reconstruction.  
(2) Population renewal. Multiple populations conduct the evolutionary search by selection, crossover and mutation at the same time, and different populations are endowed with different control parameters to achieve different search purposes. All kinds of groups are connected through migration operators, which periodically introduce the optimal individuals in the evolution process between and among groups. The specific way is to replace the worst individual in the target population with the best individual in the source population to realize the cooperative optimization among populations. In each generation of evolution, the optimal individuals are saved into the elite population by an artificial selection operator, and the elite population does not participate in the genetic evolution process.  
(3) Verify. The Petri net power analysis model is used to calculate the power flow distribution of each individual under the corresponding system operation mode. Then,the objective function of each individual is calculated with Equations (1)-(4), and the calculated value is defined as the individual fitness. If Petri net analysis results show that the population under the corresponding switch state exists such that the generator output exceeds the rated power, the tie line overloads or the system does not meet the constraint conditions, such as ring mode, it means that the topology structure is feasible, and the corresponding objective function is set as 0. As a result, it is eliminated in the process of model optimization solution, and once again, the individual species are updated.  
Iteration stops when the algebra number where the optimal fitness stays unchanged exceeds the maximum number of iterations. The switch state corresponding to the optimal individual is the optimal network reconstruction scheme.  
The specific process is shown in Figure 7.