Abstract
This paper suggests a method based on stochastic multi-objective modeling for optimally timing, siting and sizing of sub-transmission substations and medium voltage feeders, distributed generations and capacitors, simultaneously, in order to take more pros of recent developed technologies. Regards to comprehensive impact of uncertainties including: intermittent nature of renewable energy sources, load forecasting and market price errors, some strategies must be devised in order to well incorporate them into the problem. The mentioned problem is modeled by dynamic programming which NSGA-2 is chosen for optimization purposes and then fuzzy set theory is applied to find the best compromise solution. The proposed scheme aims to minimize substations expansion and installation cost, medium voltage feeders installation and replacement cost, DG units installation and operation cost, capacitors installation cost, cost of purchased energy from the transmission network, active and reactive power losses cost, and connection cost of sub-transmission substations to the upstream network. Besides, risk based modeling of energy not-supplied as an efficient reliability index is incorporated to cost function in order to improve the reliability of the network. Also voltage deviation and voltage stability as the criterion of power quality in distribution networks and emission reduction are treated as independent objective functions
