Optimal Placement Of Distributed Generation Using Improved Firefly Algorithm

Distributed Generation(DG)has the advantages of low loss,low pollution,flexible deployment and high safety performance.These characteristics make DG more and more widely used in actual power production and deployment.However,with the increasing proportion of DG in the power grid,the randomness and instability of its power supply also pose a great threat to the stable operation of the power grid.Reasonable location and capacity allocation of the connected DG can effectively solve the voltage fluctuation caused by the grid-connected DG.Therefore,it is of great significance to study the optimal allocation of DG.First of all,this paper introduces the research status and background of DG in detail,expounds the mathematical models and solving algorithms often used in the research of optimal allocation of DG,and puts forward the limitations of the existing models and algorithms.Secondly,this paper makes a detailed analysis on the influence of distributed power supply access to the grid from many aspects,and then analyzes the different influences of different access modes of DG on multiple aspects of the grid in the IEEE33-node system through the power flow calculation method of backward forward generation.Thirdly,the uncertainty model of distributed power supply,photovoltaic,grid-connected electric vehicle and random load is established.Then,the minimum network loss,optimal voltage stability and minimum investment cost are taken as the objective function,and the node power balance,line load limit,node voltage limit and DG capacity limit are taken as the constraint conditions,the multi-objective optimization model of distributed power supply is established.Aiming at the defects of weighting method in traditional multi-objective optimization problems,a new hybrid multi-objective problem decision-making method based on improved hierarchical sequence method and ideal point method is proposed in this paper.Then,aiming at the disadvantage of poor population initialization in traditional firefly algorithm,Tent chaotic mapping is introduced to initialize the population.In view of its slow convergence speed,an adaptive factor is introduced to accelerate the convergence speed.Aiming at the disadvantage that it is easy to fall into local optimality,Lévy flight is introduced to increase its global search ability.The performance is verified by several test functions in MATLAB software.Finally,taking the IEEE33-node network system as the object,the improved firefly algorithm is used to solve the optimal allocation model of distributed power supply established in this paper,and the hybrid decision scheme proposed in this paper and the traditional weighting method are respectively used to convert the multi-objective function into a single objective.By summarizing the respective calculation results,The application scenarios of the two decision methods are analyzed.