Investigation of simultaneous effect of demand response and load uncertainty on distribution feeder reconfiguration
Ali Reza Abbasi
Abstract
Distribution feeder reconfiguration (DFR) and demand response (DR) are the common energy consumption management methods to enhance the operation quality of distribution networks (DNs). Moreover, DFR and DR may lead to system improvement through different aspects such as reliability, total cost, and power quality. Nevertheless, the high complexity of the new smart grids has caused a lot of uncertainty in the reconfiguration problem. Given that, the use of an adequate probabilistic framework is necessary to deal with such issues. Hence, the current study investigates the effect of DR on the DFR strategy in a stochastic environment as a single‐period and multiple‐objective model at peak load. A parametric probabilistic analysis is administrated based on unscented transform (UT) method to capture the load and generation uncertainties. High‐precision results and low computational burden are the outstanding features of the UT method. Furthermore, an improved version of Cuckoo search Algorithm (CSA) as an optimizing tool is proposed. The effectiveness of the suggested method is tested on the modified IEEE 32‐ and 69‐bus systems. Moreover, PDF and CDF functions of random output variables are plotted and compared to verify the proposed stochastic method. The results confirm the efficient operation of the proposed algorithms.