Browsing by Author "Mahmmadsufiyan, S."

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Probabilistic Optimal Power Flow in the Presence of Uncertainties Related with Load Wind and PV Considering Different Load Models
    (Institute of Electrical and Electronics Engineers Inc., 2022) Mahmmadsufiyan, S.; Gaonkar, D.N.
    The conventional Power Flow and Optimal Power Flow (OPF) consider the Power System variables as certain quantities. But the uncertain nature of real time power system variables and the increased integration of renewable energy generation lead the modern power systems to account these uncertainties in their planning and operation. This paper presents the handling of uncertainties in solving the Probabilistic Optimal Power Flow (POPF) problem in the context of operating cost minimization, by using Point Estimate Method (PEM). In this work the uncertainties related with load power, Wind and Photovoltaic (PV) are considered. And to analyze the impact of the voltage dependency nature of loads, constant current and constant impedance load models are also considered. The POPF problem is solved for IEEE-9 bus and IEEE-57 bus test systems by using PEM and the results are compared against Monte Carlo Simulation (MCS). © 2022 IEEE
  • No Thumbnail Available
    Item
    Probabilistic Reactive Power Reserve Assessment in the Presence of Load and Wind Uncertainties Considering Correlation
    (Institute of Electrical and Electronics Engineers Inc., 2021) Mahmmadsufiyan, S.; Gaonkar, D.N.
    Voltage stability plays a crucial role in the reliable operation of power systems. The Reactive Power Reserve (RPR) available at the sources is one of the parameters that represent the voltage stability margin of the power system. In the modern power systems, the existence of highly uncertain reactive power demand by the wind power generating units affects the RPR which in turn affects voltage stability. This paper considers the uncertainties related with load and wind to determine the stochastic information of system RPR. The stochastic RPR assessment problem is solved by using Two Point Estimate Method (2PEM) for IEEE-9 bus and IEEE-118 bus test systems, and the results are compared against Monte Carlo Simulation (MCS). Correlation between system loads and wind speeds is also considered to analyze the effect of correlation of uncertain input variables on system RPR. © 2021 IEEE.