  This paper presents a comprehensive approach to improve the daily performance
of an active distribution network (ADN), which includes renewable resources and
responsive load (RL), using distributed network reconfiguration (DNR).
Optimization objectives in this work can be described as (i) reducing active
losses, (ii) improving the voltage profile, (iii) improving the network
reliability, and (iv) minimizing distribution network operation costs. The
suggested approach takes into account the probability of renewable resource
failure, given the information collected from their initial state at the
beginning of every day, in solving the optimization problem. Furthermore, solar
radiation variations are estimated based on past historical data and the impact
of the performance of renewable sources such as photovoltaic (PV) is determined
hourly based on the Markov model. Since the number of reconfiguration scenarios
is very high, stochastic DNR (SDNR) based on the probability distance method is
employed to shrink the scenarios set. At the final stage, an improved crow
search algorithm (ICSA) is introduced to find the optimal scenario. The
effectiveness of the suggested method is verified for the IEEE 33-bus radial
distribution system as a case study.
