In recent years, power system uncertainties have increased due to the growing integrations
of intermittent renewable energy resources. It is imperative to introduce probabilistic load …

Time series decomposition is extensively used recently for time series forecasting. The
obtained set of relevant monocomponents using an adaptive decomposition method are …

This article proposes a probabilistic optimal reactive power planning keeping in view the
uncertainties in renewable generations (wind and photovoltaic systems), loads, and electric …

This paper proposes a Gauss-quadrature-based probabilistic load flow (PLF) keeping in
view the uncertainties and correlations in load, renewable generations (wind and PV), and …

In this paper, the risk assessment of a PV integrated power system is accomplished by
computing the over-limit probabilities and the severities of events such as under-voltage …

External weather conditions have significant effects on the operation of composite power
systems. Stochastic renewable generations, random loads, dynamic thermal ratings, and …

The probabilistic steady‐state forecasting of a PV‐integrated power system requires a
suitable forecasting model capable of accurately characterizing the uncertainties and …

Probabilistic forecasting of PV generation is crucial in uncertainty management to reinforce
PV‐integrated power systems for long‐term planning. In this context, developing a reliable …

Various probabilistic power flow (PPF) and interval power flow (IPF) methods have been
developed to deal with random and interval variables in power systems, respectively …

Renewable energy sources (RESs) and flexible loads have introduced significant
uncertainties in the operation and control of power systems especially voltage regulation at …