Probobalistic Optimal Power Flow considering wind and load uncertainties using 2m+1 point estimation method

Due to electrical demand variations and wind speed uncertainties, many scholars have focused on probabilistic optimal power flow (POPF) analysis of large-scale power systems. Hence, this paper aims to implement 2m+1 point estimation method on POPF problem for modeling the uncertainties associated with electrical demand and wind product. Meanwhile, the wind speeds are not independent in adjacent areas. This affects the optimum operating point of the interconnected energy networks. This problem also exists between the neighbor loads. Hence, it is important to consider these correlations in POPF. Therefore, Nataf transformation is utilized for making these uncertain variables independent and using uncorrelated input random variables in PEM algorithm. Simulations are conducted on 24-bus IEEE standard power system and solved under generalized algebraic mathematical modeling system (GAMS) optimization package using COUENNE tool. Total fuel cost of conventional thermal power plants is minimized as objective function in stochastic power flow analysis. The optimum generation schedules of thermal units, bus voltage angle, transmission active power, electrical demand of each load bus, and the wind generation of each wind farm are selected as decision variables.

کلیدواژه ها:

Probabilistic Optimal power flow (POPF) ، wind speed uncertainty ، point estimation method (PEM) ، Nataf transformation ، generalized algebraic mathematical modeling system (GAMS)