Comprehensive Optimization Of Distribution Network Reconfiguration With Solid State Transformer Based On Improved Bacterial Foraging Algorithm

As the intermediate part connecting the transmission network and the user side,the operation of distribution network has direct influence on the power quality in user side,the safety and economic operation of the network.The development of the Energy Internet has promoted the application of Solid State Transformer(SST)in distribution network,in the distribution network with SST,SST has the advantages of reactive power compensation,stabilizing voltage,improving harmonic,bi-directional power flow and the dc output of high voltage and low voltage,therefore,the distribution network with SST can achieve optimal operation relative to the traditional distribution network.However,the introduction of power electronic equipment makes the modeling of optimal operation of the distribution network more complex and more intelligent and controllable parameter variables and constraint sets should be considered in optimal operation of the distribution network with SST,which increase the complexity of model solution.With the expansion of grid scale and the access of various new energy and load,optimal operation of the distribution network with SST is a meaningful investigation topic.The cooperation and coordination of various optimization techniques should be fully considered in optimal operation of the distribution network.Distribution network reconfiguration can achieve the purpose of reducing network loss and balancing load by optimizing the network topology.SST can improve voltage quality and reduce loss through reactive power compensation and voltage adjustment.Based on these realities,in order to improve the safety、reliability and economy of distribution network,SST’s optimization combined with distribution network reconfiguration is used to optimize the distribution network comprehensively in this paper.First of all,the working principle,mathematic model and control method of SST are analyzed in detail to illustrate its principle of reactive power optimization and voltage adjustment.Considering that the distribution network power flow calculation is the basic support of the network optimization operation and traditional power flow algorithm cannot solve the problem of power flow calculation of the distribution network with SST,an alternate iteration algorithm is proposed to calculate the power flow of the distribution network with SST.By analyzing the structure and power flow calculation characteristics of each part in the distribution network with SST in detail,The overall distribution of power flow is calculated by the algorithm in which the power flow calculation of SST section is nested in the AC power flow calculation based on forward-backward sweep method,which is the basis of subsequent optimization research.Then,based on the power flow algorithm of the distribution network with SST,an Improved Bacteria Foraging Algorithm(IBFA)was proposed to solve the integrated optimization problem of distribution network reconfiguration with SST.Considering the characteristics of the reconfiguration problem,the proposed algorithm has set the transcoding rule between decimal integer coding and real coding,which solves the problem that BFA cannot deal with integer solution.For standard BFA’s defects that chemotactic step size of bacterial in each dimension is the same and bacterial turns over blindly,which results in the inefficiency of the algorithm,firstly,social learning with variable speed is introduced to make the local search of bacteria targeted through referring to the optimal individual in the population when bacteria turns over;Further,combining coding rules and evolutionary information of bacterial population,chemotactic step size of bacteria in each dimension corresponding to reconfiguration can be adjusted adaptively and respectively according to the number of switches within the ring network in each dimension and individual fitness of the bacterial,and chemotactic step size of the dimensions corresponding to the SST’s reactive power optimization can be adjusted according to individual fitness,which makes the chemotaxis operation more refined and efficient.In order to avoid the loss of elite individual causing algorithm degradation,grouped migration strategy based on the average fitness of the bacterial population is proposed,which can keep the elite individual and increase the diversity of the population.Based on the above improvements,the steps and processes of the comprehensive optimization algorithm are given.Finally,a comprehensive optimization model of distribution network reconfiguration with SST is established.Simulation analysis is operated,setting the modified IEEE33 nodes system and PG&E69 nodes system for instance.The operation states of distribution network using different optimization measures and the algorithm performance of different algorithms are compared and analyzed.In conclusion,the effect of the distribution network reconfiguration with SST is better on reducing network loss and improving power quality,which makes the distribution network’s operating status relatively optimal.Meanwhile,IBFA has good algorithm stability and ability of global optimization and solve comprehensive optimization problems quickly and effectively.