An optimal sizing model for an off-grid hybrid micro-grid system (HMGS) consisting of solar photovoltaic (PV), wind turbine (WT), diesel generator (DG) and battery (BAT) is developed. A tri-objective formulation, considering techno-socio-economic factors, is employed for finding the optimal...

Solving non-linear parabolic partial differential equations (PDEs) in high dimension becomes an interest for its curse of dimensionality problem. Recently, a deep learning method associated with a backward stochastic differential equation (deep-BSDE) to solve the PDEs draws intensive discussions...

Prediction of nonlinear dynamic process remains a challenging and active research topic. In this paper, adaptive nonlinear prediction based on a Hammerstein-modeling approach is investigated. Motivated by the desire to represent the best fit to the nonlinear dynamical plant with the Hammerstein...

This study presents a novel approach for wind farm micro-siting in complex terrain based on an improved Genetic Algorithm (GA). The proposed approach is used for optimizing the layout of wind turbines in a real terrain in Changsha, China. Firstly, a combination of computational fluid dynamics...

Purpose: The research studies the production system having multiple items being processed on the same production line. The objectives are to (1) investigate the influence of production sequence on the optimal value of production run size, (2) explore the effect of production sequence on the...

This work presents a potent multiobjective multiverse algorithm to solve the highly complicated dynamic economic emission dispatch problem. Solving the dynamic economic dispatch problem with power balance equality constraint, valve point constraints, and ramp limit constraints not only minimizes...

This work aims to reconcile theory and practice, proposing a dynamic model of asset allocation that allows the creation, with the help of genetic algorithms, of reasonable portfolios for investors chasing a variety of objectives over multiple time horizons. Our results are interesting and...