A novel method for solving multi-stage distribution substation expansion planning

This paper presents a new methodology for solving multi -stage distribution substations expansion planning (MSDSEP) problem. The proposed method can determine the optimal location, capacity, associated service area and construction timing of substations with aiming to the maximum profit for supplying the forecasted demand. The objective function is of the difference between benefit and cost of expansion. The present worth of revenue from selling energy is considered as the expansion benefit while the present worth of cost from purchased energy, investment cost for installing and/or upgrading substations and the construction cost of medium voltage (MV) feeders are considered as the expansion cost. Moreover, the technical constraints consist of network radiality, voltage drop, expansion capacity and operation capacity of substations. The developed method generates the binary variables for deciding connection between load points to substations and the integer variables for deciding expansion capacity of substations. While the dynamic bacterial foraging algorithm (DBFA) process is used for searching the best binary variable and the best integer variable. The effectiveness of proposed method is demonstrated on the distribution system of Tabriz city Iran which compared with single -stage distribution substations expansion planning DSEP (SSDSEP). The results showed that MSDSEP can provide more economical solution than SSDSEP. (C) 2019 The Authors. Published by Elsevier Ltd.