Abstract Renewable energy has unpredictable intermittency and variability, increasing the complexity of grid dispatch. Fuzziness theory is introduced under uncertainty large-scale intermittent power supply. characterized by fuzziness parameters. Meanwhile, conventional deterministic unit commitment model transformed into a chance-constraint with The explicit equivalence classes chance constrain...

In this paper, we propose to use spectral proximal method solve sparse optimization problems. Sparse refers an problem involving the ι 0 -norm in objective or constraints. The previous research showed that gradient is outperformed other standard unconstrained methods. This due replaced full rank matrix by a diagonal and memory decreased from Ο(n 2 ) Ο(n). Since term nonconvex non-smooth, it can...

Random search methods are successfully implemented for variety of discrete optimization NP-hard problems when any exact solution approaches cannot be implemented due to large computational demands. Initially designed for unconstrained optimization, the probability changing method gives an approximate solution for various linear and non-linear pseudo-Boolean optimization problems with constraint...

in this study, the optimization of energy consumption and reduction of greenhouse gas emissions of irrigated lentil production in esfahan province were conducted using data envelopment analysis (dea) method. the used data were collected randomly from 140 lentil producers using a face to face questionnaire method in the cropping season of 2014-2015. based on two dea models of constant returns to...

reliability evaluation of a large-scale composite power system faces to numerous events/outage and consequently imposes an extensive burden of calculations. in order to simplify the problem, determination of an equivalent system for large-scale power system is inevitable. this paper proposes a framework as reduction technique to separate a composite power system to three areas: external area, o...