Multi-objective and multi-period distribution expansion planning considering reliability, distributed generation and self-healing

Abstract

This study describes a methodology to solve the multi-period distribution expansion planning problem considering reliability, distributed generation (DG), capacitor and switch placement in the context of smart grids. The developed computational model is formulated as a mixed integer nonlinear optimisation problem and solved through the combination of meta-heuristics, stochastic simulation methods (Monte-Carlo simulation), and application of optimal power flow. The main objectives of this optimisation problem are defining the best choice to install power system components and determining the installation period and size of components to minimise investment cost while maximising system reliability. The proposed method was implemented in a modified version of the IEEE-RBTS bus 2 and in a 90-bus test system. The obtained results show a reduction of > 20% of the operating cost and > 70% of the average interruption time. In addition, it was performed scenarios not including DG, self-healing, and reliability analysis, individually. The analyses show the impact in the results by including a new variable in the expansion planning, increasing up to 40% in the fitness function value. Furthermore, it is presented with a discussion of the impact of the method to estimate the reliability indexes on the optimisation process.