Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method

Comparative performance of an elitist teaching-learning-based optimization algorithm for solving unconstrained optimization problems

“…The TLBO algorithm has already been successfully applied by various researchers for solving complex benchmark functions and difficult engineering problems (Azizipanah-Abarghooee et al 2012, Hosseinpour et al 2011, Krishnanand et al 2011, Nayak et al 2011, Niknam et al 2012a, Rao and Kalyankar 2012a, Rao and Savsani 2012, Rao and Patel 2012a2012d, Satapathy and Naik 2011, Satapathy et al 2012, Toğan 2012. Contrary to the opinion expressed by Črepinšek et al (2012) that TLBO is not a parameter-less algorithm, this paper has clearly explained that TLBO is an algorithm-specific parameter-less algorithm and this was already stated by Rao and Patel (2012a).…”

Optimal power flow based TU/CHP/PV/WPP coordination in view of wind speed, solar irradiance and load correlations

“…This reduces the accuracy of the 2m PEM when the total number of IRVs increases [17], [38]. According to (5) of [17], (13) of [37] and (6) of [38], the position of each of the 2m PEM concentrations depends on the number of IRVs m; as m increases, concentrations are taken further away from the mean of the corresponding IRVs [17]. Concisely, the idea behind using 2m + 1 PEM in this study is to efficiently and accurately estimate the uncertainty concerned with the ORV of the POPF problem [38].…”

Short-term hydro-thermal-wind complementary scheduling considering uncertainty of wind power using an enhanced multi-objective bee colony optimization algorithm

“…Ref. [16] presents a probabilistic approach based on 2 m point estimated method to analyze uncertainties of load demand and wind speed which are considered as random input variables of wind-thermal system. Moreover, Ref.…”