Cooperative Planning Of Multiple Flexible Resources In Active Distribution Network Based On Improved CS Algorithm

Large-scale development of clean energy has become a major trend of energy development.Developing clean energy according to local conditions and making it distributed to the nearest distribution network has become a mode of development of modern distribution network.This kind of distribution network with distributed power supply is called active distribution network.In the active distribution network,the reliability is higher because of the power supply.However,the uncertainty brought by the distributed power supply,especially the distributed renewable energy power supply,has a negative impact on the operation and control of the active distribution network.Therefore,in the actual active distribution network,in addition to considering DG,the access of flexible resources such as energy storage and reactive power compensation needs to be considered,so as to deal with the many impacts brought to the active distribution network.In this paper,under the above background,the active distribution network planning considering the participation of various flexible resources is studied,and two solving algorithms are proposed to solve the planning model.First of all,on the issue of active power distribution network planning model,this article from the perspective of the actual power grid,on the basis of considering each special investment funds limit,comprehensive consideration of three flexible resources:DG,energy storage,reactive power compensation equipment,set up an upper level planning model with the goal of minimizing the investment cost,comprehensive operation and maintenance cost and network loss cost,and maximizing the DG access volume,and a lower level planning model with the goal of minimizing the daily power purchase cost.The upper layer of the two-level planning model is the investment decision-making layer,the lower layer is the operation simulation layer,the upper layer provides the basic scheme for the distribution network planning,and the lower layer carries on the fine-tuning and optimization of the proposed scheme.Secondly,since the solution of the proposed model belongs to the nonlinear mixed integer programming problem,two algorithms are proposed to solve the model.First,improve the cuckoo search algorithm.Considering that the cuckoo can find the optimal flight path for the nest and improve the survival rate after abandoning the nest,the step size scaling factor is improved to improve the convergence speed of the algorithm in the search process.In view of the fact that the particle swarm optimization algorithm has better directivity than the cuckoo search algorithm at the beginning of the search,this paper puts forward another algorithm--hybrid cuckoo search algorithm.On the basis of the cuckoo search algorithm and the basic particle swarm optimization algorithm,the advantages of both are fully played,and the particle swarm optimization algorithm is used to solve the model first,after a certain number of iterations,the obtained suboptimal solution are taken as the initial value of the cuckoo search algorithm,into the cuckoo search.The algorithm keeps the advantages of fast convergence of particle swarm optimization,and increased the cuckoo search algorithm good optimization ability.Finally,using IEEE 33-node distribution system data,the proposed algorithm is used to solve the established model.The results of calculation examples show that the improved algorithm has better convergence speed than the original algorithm,and the stability is also outstanding.Compared with the two combined algorithms,the hybrid algorithm makes up for the shortcomings of the two,and the convergence speed of the model is faster,the solution time is shorter,and the optimization ability is stronger,which can converge to the optimal solution faster.