Research On Reactive Power Optimization Of Small Hydropower Distribution Network Based On Hybrid Intelligent Algorithm

As a new type of clean energy with great development potential,small hydropower has the advantages of perfect technology and good economic benefits.However,small hydropower generation at this stage is more common in power supply systems in peripheral areas,and it is usually directly connected to the grid with 10 k V and other buses.On the other hand,in addition to changes in small hydropower grids with seasonal and geographical factors,there are also problems such as long power supply radius and small cross-sectional area of conductors.In summary,a large number of small hydropower connections will cause the stability of the normal grid voltage performance to decrease.In addition,the shortcomings in the continuous power generation capacity of the small hydropower grid will inevitably increase the difficulty of voltage output stability control,resulting in a reduction in the economic benefits of the grid system.Therefore,how to improve the reactive power optimization control of the small hydropower grid system to stabilize the system voltage,Reducing network loss has great research value and application value.This article starts with the development status of small hydropower and the status quo of reactive power optimization at home and abroad,and introduces the principles,advantages and disadvantages of the current mainstream traditional optimization algorithms and artificial intelligence algorithms.This paper focuses on the problems of voltage over-limit,unreasonable reactive power distribution and increased line loss caused by the access of small hydropower to the distribution network,and proposes to build a multi-objective reactive power optimization mathematical model based on the small hydropower distribution network.The objective function,voltage offset and reactive power compensation are penalty functions.Several distribution network parameters including generator terminal voltage are used as control variables,and the power flow calculation method of distribution network is introduced.Aiming at the time-consuming problems of traditional algorithms in solving small hydropower distribution network reactive power optimization and multi-objective problems,a hybrid intelligent algorithm is proposed.It focuses on the theoretical basis and main characteristics of genetic algorithm and multi-agent algorithm,and proposes an intelligent hybrid solution algorithm based on multi-agent and pseudo-parallel genetic algorithm.According to the inherent parallelism of genetic algorithm and the characteristics of small hydropower stations,a pseudo-parallel genetic algorithm is proposed.Research on the coordination mechanism of multi-agents.In view of the characteristics of autonomy,response,and society of multi-agents,the multi-agent coordination mechanism and grid environment are introduced into the pseudo-parallel genetic algorithm,which increases the probability of the genetic algorithm jumping out of the local optimal solution.Based on the improved genetic operator,a self-learning operator is introduced,which can reduce the amount of data transmitted by the system and enhance the diversity of the system,so that it can converge to the global optimal solution at a faster rate.Based on the MATLAB platform,this paper implements the program design work of the algorithm.The radial IEEE 13 standard node and the ring IEEE 30 standard node are used to simulate the distribution network with small hydropower connection,and the calculation results are compared with the traditional genetic algorithm.The algorithm and the multi-agent genetic algorithm are compared and analyzed.The results show that the algorithm proposed in this paper has significant advantages in reducing system loss and improving grid voltage quality,and greatly improves the calculation speed and has a stronger global optimization capability..