Optimal Stochastic Scenario-based Allocation of Smart Grids’ Renewable and Nonrenewable Distributed Generation Units and Protective Devices

Abstract

The smart grid reliability is dramatically affected due to system uncertainties. Although
much efforts have been devoted to developing the Monte Carlo simulation (MCS)-
based or analytical methods for reliability-based optimal allocation distributed
generation (DGs) and protective devices (PDs), there is a research gap about
developing the probabilistic scenario-based optimization methods. This paper tries to
propose a novel stochastic scenario-based reliability evaluation method for optimal
allocation of smart grids’ PDs and DGs. The scenario reduction is applied using the kmeans
algorithm and modified system state, including the clusters of renewable-based
DGs. T he malfunction of PDs is concerned, which is one of the most important
contributions of the introduced method. The introduced clustering-based reliability
evaluation method is applied to IEEE 33-bus test system. Test results infer that around
10% inaccuracy occurs in deterministic approaches without consideration of
uncertainties of DGs and PDs. Obtained test results also imply that the impacts of
renewable DGs’ uncertainties are more considerable than eventual malfunctions of
PDs. The MCS-based methods are used to verify the precision of the introduced
method. Moreover, by comparing the introduced method with other available analytical
methods, it is shown that the obtained results are 1.2% more precise than current
analytical one