Research On Reactive Power Optimization Of Distribution Network Containing Distributed Generation Based On Modified Artificial Bee Colony Algorithm

Reactive power optimization can improve the system voltage level,reduce the network loss and ensure safe and stable operation of power system.Renewable energy access to distribution network can relieve the energy crisis,promote the development of energy conservation and emission reduction,but on the other hand,it would change the power flower of the distribution network,and bring new challenges to planning,operation and control of the distribution network.In this thesis,the research is on reactive power optimization of distribution network containing distributed generation,the main work is as follows:(1)In this thesis,a mathematical model for reactive power optimization of distribution network is established,which aims at reducing the loss of the system.At the same time,based on the calculation of reactive power margin value,the reactive power compensation point is determined.In this model,the reactive power output of the DG and reactive power of capacitor switching group are set as control variables,the load node voltage as the state variables,by optimizing the reactive power output of DG and the reactive power compensation of the capacitor bank,the purpose of reactive power optimization of distribution network containing DG can be achieved.(2)A power flow algorithm for different DGs is proposed.Firstly,different DGs can be equivalent to different kinds of node types.The back or forward sweep method is putting forward to calculate power flow.Aiming at the PV node,the reactive power compensation device is used for power correction,and the reactive power allocation principle is adopted to determine the initial value.The power flow calculation is finished in the IEEE 33 node distribution system with different DGs.The simulation results show that the access of DG can improve the system node voltage.(3)A MABC algorithm is proposed.By using the mutation operator of DE algorithm,the search strategy of the onlooker bee is guided by the optimal value,so that the global exploration and local mining ability of the algorithm can be balanced.Moreover,according to the deficiency of scout bees search mechanism in standard ABC algorithm,in order to preserve search experience for scout bees,the generalized opposition-based learning strategy was utilized to generate opposite solutions of the discarded food sources,which helps enhance the search efficiency.The simulation results show that the improved algorithm maintain the simple and easy to implement characteristics of the ABC algorithm,and enhances the global convergence,and improves the convergence speed and convergence precision of the algorithm.(4)IEEE33 and American PG&E69 node system are used as examples to simulate and compare with the MABC algorithm,the standard ABC algorithm and the IABC algorithm in the literature.The simulation results verify the validity of mathematical model and the proposed MABC algorithm.The scheme can reasonably optimize the reactive power distribution of the distribution network,improve the voltage level of the distribution network and the stability of the power system.