Maximizing renewable energy penetration through distribution network reconfiguration using mixed-integer conic programming

This paper presents a model to maximize the renewable energy penetration level in reconfigurable radial distribution system when renewable generation and load profile are hardly matched. By means of variable substitution and relaxation method, the original mixed-integer nonlinear programming model can be transformed into a mixed-integer conic programming model, which could guarantee a global optimal solution with better computational efficiency. Different sizes of DG units under different load levels are considered to evaluate the performance of the proposed model and method, and two distinct types of system have been tested. Case study results show the efficiency of the method and an optimal renewable energy penetration level is obtained.