Active Distribution Network Expansion Planning considering the Uncertainty of Electric vehicles’ load

Abstract

Integrating Electric vehicles into distribution systems introduce new challenges both in operation and planning of electric distribution systems. In the planning process, these vehicles mainly affect load uncertainty in the grid. A new method for Active Distribution Network (ADN) expansion planning is proposed considering the uncertainty of bus loadings because of electric vehicles (EVs) integration. The approach taken in this paper includes the initial cost of investment and operation. A probabilistic model is proposed for extracting the effect of electric vehicles integration on future loading of network buses. Different scenarios are defined based on electric vehicle entrance time, charging delays and their overall penetration level. Particles colony algorithm is used for handling the proposed mixed integer and nonlinear optimization model. Also, a graph theory based method for detecting radial structures is implemented for faster convergence. Finally, the effectiveness of the proposed algorithm is examined by implementing it on the modified IEEE 33 bus standard distribution network.