Researches On Distribution Network Reconfiguration Based On Iterative Learning Control

In the face of a new type of modern power grid, users' requirements for the power supply reliability, voltage stability and power quality become higher and higher. That is to say, requirements for the distribution network structure optimization become higher. Distribution network reconfiguration is an effective method for distribution network optimization. In order to meet the requirements of modern distribution network, iterative learning control is applied to distribution network reconfiguration in the master's thesis. The feasibility of the algorithm is verified which contain the static reconfiguration of the distributed generation(DG) and the dynamic reconfiguration of considering load changes.Firstly, in the static reconfiguration of the distributed generation(DG), the mathematical model of distribution network reconfiguration of DG and power flow calculation model of DG are established. The static voltage stability index is used for DG interconnection location. The ring network is also adapted to code switch. Through the breadth-first search to hierarchical network, the ILC algorithm is applied in the reconstruction. In the algorithm, the combination switch is as the control variable; the current network loss is as the output variable; the current network loss difference of network loss and our expectations is as the output error. According to the open loop P-type iterative learning law, distribution network reconstruction has been continued until the convergence conditions met.Second, in the dynamic reconfiguration of considering load changes, the mathematical model and the corresponding objective function are established. According to the actual load, the method of the static load divided into the minimum load, general load and the maximum load is given. Using respectively ILC algorithm to the distribution network reconstruction in these ways, finally get the optimal network structure and the corresponding comprehensive network loss.Finally, the effectiveness of the ILC algorithm is verified in the static and dynamic reconfiguration aspects with examples of IEEE33 and PG&E69 node system.