Coordinated Optimal Scheduling of WPHTNS Power System Based on Adaptive Improved Genetic Algorithm

In order to solve the problem of poor grid connected consumption capacity of renewable energy in power system, a multi-source coordinated optimal scheduling method of wind-PV-hydro-thermal-nuclear-storage is proposed in this paper. The optimal scheduling method comprehensively considers the constraints of system power balance, capacity and climbing rate of various power generation modes, establishes the objective function based on the system power purchase cost and renewable energy consumption, obtains the weight relationship between the objective functions by analytic hierarchy process. An adaptive improved genetic algorithm is proposed, and the objective function is solved and the results are compared by this algorithm and three algorithms such as adaptive improved particle swarm algorithm, respectively. The results show that the improved genetic algorithm can eliminate the local optimum phenomenon by normalizing the crossover and combining variances, and is more suitable for the multi-source coordinated optimization scheduling model compared with the other algorithms. After the multi-source coordination and optimal dispatch, the system renewable energy disposal is reduced from 657MWh to 208MWh, and the power purchase cost of the system load is reduced from ${\$}$ 30.077 to ${\$}$ 30.052M. It can be seen that the selected optimization method can enhance the system’s renewable energy consumption capacity while reducing the system’s power purchase cost, which reflects the effectiveness of the optimization method used in this paper. By changing the scaling parameters of the hierarchical analysis method, the scheduling scheme can be flexibly selected for different regions, reflecting the universal applicability of the optimization method used in this paper. To provide an efficient and accurate solution for multi-energy dispatching problems in power systems