Batch distillation processes are very attractive for the recent development of the chemical industry: multipurpose, flexible plants and fine chemistry. For many separations of high-added value products, even a modest change in operating conditions has a significant economic impact-there is an important challenge for optimizing such processes.Short-cut and dynamic models are the two classical approaches to the simulation of batch distillation columns. For problems without holdup, an intermediate procedure based on a decoupling method is validated.For a multifraction separation problem with fixed final time, the reflux policies for each period and the period switching times constitute the set of decision variables. For predefined reflux policies, we apply an engineering approach to the solution of a such constrained variational problem, based on its transformation into a nonlinear programming problem. In this computer-implementable algorithm, the gain in distillate for the optimal linear or exponential reflux policies is significant (about 1O0/o) compared with the optimal constant reflux policy.

In order to maximize the electric energy production of a photovoltaic generator (PVG), the maximum power point tracking (MPPT) methods are usually used in photovoltaic systems. The principle of these techniques is to operate the PVG to the maximum power point (MPP), which depends on the environmental factors, such as solar irradiance and ambient temperature, ensuring the optimal power transfer between PVG and load. In this paper, we present the implementation of two digital MPPT commands using the Arduino Mega type. The two proposed MPPT controls are based on the algorithm of perturb and observe (P&O), the first one with fixed perturbation step and the second one with two perturbations step varying with some conditions. The experimental results show that the P&O algorithm with variable step perturbation gives good results compared to the P&O algorithm with fixed perturbation step in terms of the time response and the oscillations around the MPP.

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This paper deals with analysis, modeling, and simulation of a Photovoltaic (PV) system with an intelligent Maximum Power Point Tracking (MPPT) controller based on fuzzy logic and to compare the dynamic performances: rapidity and stability of a fuzzy controller with the traditional controller based on the “Perturb and Observe” algorithm (P&O). The system is simulated under Simulink/Matlab environment. The simulation results show that the fuzzy MPPT controller is faster and more stable during abrupt changes in irradiation values.

This paper describes a MPPT control of the stator powers of a DFIG operating within a wind energy system using the backstepping control technique. The objective of this work consists of providing a robust control to the rotor-side converter allowing the stator active power to be regulated at the maximum power extracted from the wind turbine, as well as maintaining the stator reactive power at zero to maintain the power factor at unity, under various conditions. We have used the Matlab/Simulink platform to model the wind system based on a 7.5 kW DFIG and to implement the MPPT control algorithm in a first step, then we have implemented the field-oriented control and the backstepping controller in a second step. The simulation results obtained were very satisfactory with a fast transient response and neglected power ripples. They furthermore confirmed the high robustness of the approach used in dealing with the variation of the internal parameters of the machine.