Optimization of the dynamic behavior of a solar distillation cell by Model Predictive Control

Abidi, M.; Jabrallah, Sadok Ben; Corriou, Jean‐Pierre

doi:10.1016/j.desal.2011.06.033

Cited by 6 publications

(7 citation statements)

References 29 publications

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“…The steady state model was later experimentally validated by the same authors [17] and the influence of the different operating parameters on the yield was compared to theoretical predictions with a good agreement. However, in order to perform the present study along days, the previous model has been extended as a dynamic model by Abidi et al [1] composed of partial differential equations to represent the transient behaviour. In the same way as the steady state model, the model describing the dynamic behaviour of the distillation cell is divided into three parts corresponding, respectively, to the heated wall, the liquid phase, and the gas phase ( Figure 1).…”

Section: First-principles Dynamic Model Of the Distillation Cellmentioning

confidence: 99%

“…To solve it, a double sweeping method was adopted which presents the advantage to rapidly propagate the influence of the boundary conditions towards the inside of the cell and to accelerate the convergence. With the solution being searched at each time step, the boundary conditions were updated at each iteration [1]. As the dynamic model is deduced from the steady state model by use of first principles, it is also assumed that the steady state validation is sufficient for its dynamic purpose.…”

Section: Numerical Solution and Validation The Desalination Cellmentioning

confidence: 99%

“…Most autonomous desalination systems use solar radiation. The studies by [1,2] show that the production flow rate of the cell is significantly improved with the increase of the heat flux densitẏ. The solution requires the increase of the number of solar sources by means of a simple multiplication of the number of reflecting mirrors [3,4] which are used for various purposes such as energy production [5], material study at high temperatures, hydrogen production [6], and heating [7].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Design of a Solar Desalination Unit with Heliostats

Abidi

Jabrallah

Corriou

2017

International Journal of Chemical Engineering

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The objective is to improve the yield of a solar desalination cell using concentration of solar rays by means of automatically controlled heliostats. The vertical cell is orientated towards the north. It is mainly composed of two plates; the one being heated by the solar rays reflected by the mirrors is used for evaporation of a falling water film; the other one is used for water vapor condensation. Each heliostat consists of an altitude-azimuth mount having two degrees of freedom and supporting a plane mirror. The heliostat permanently follows the sun trajectory and reflects the solar rays on the cell by means of automatic control implemented in a control card based on a microcontroller. Model predictive control allows us to maximize the distilled water production.

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Section: First-principles Dynamic Model Of the Distillation Cellmentioning

confidence: 99%

Section: Numerical Solution and Validation The Desalination Cellmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal Design of a Solar Desalination Unit with Heliostats

Abidi

Jabrallah

Corriou

2017

International Journal of Chemical Engineering

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“…In this context, many mathematical models have been developed in the literature to describe the electric, dynamic and thermal behavior of photovoltaic cell/module with a different level of complexity. In particular, the solar cell can be modelled as a static model for DC/DC (direct current), or as a dynamic model for DC/AC (alternating current) with capacitance and parallel dynamic resistance, with diode and photocurrent as proposed in [9][10][11]. They can be classified globally into two categories: implicit and explicit models [12,13].…”

Section: Introductionmentioning

confidence: 99%

Metaheuristic Algorithm for Photovoltaic Parameters: Comparative Study and Prediction with a Firefly Algorithm

et al. 2018

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In this paper, a Firefly algorithm is proposed for identification and comparative study of five, seven and eight parameters of a single and double diode solar cell and photovoltaic module under different solar irradiation and temperature. Further, a metaheuristic algorithm is proposed in order to predict the electrical parameters of three different solar cell technologies. The first is a commercial RTC mono-crystalline silicon solar cell with single and double diodes at 33 • C and 1000 W/m 2. The second, is a flexible hydrogenated amorphous silicon a-Si:H solar cell single diode. The third is a commercial photovoltaic module (Photowatt-PWP 201) in which 36 polycrystalline silicon cells are connected in series, single diode, at 25 • C and 1000 W/m 2 from experimental current-voltage. The proposed constrained objective function is adapted to minimize the absolute errors between experimental and predicted values of voltage and current in two zones. Finally, for performance validation, the parameters obtained through the Firefly algorithm are compared with recent research papers reporting metaheuristic optimization algorithms and analytical methods. The presented results confirm the validity and reliability of the Firefly algorithm in extracting the optimal parameters of the photovoltaic solar cell.

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“…Dynamic optimization has been used to maximize rice quality synthesis by seeking the corresponding configuration of units and their corresponding operating conditions [2]. A reduced dynamic model for a solar cell characterized by inputs and outputs has been used in [3] to dynamically optimize the operating parameters of the cell behavior by means of model predictive control in order to maximize the mean flow rate of distilled water confronted to a variable solar radiation.…”

Section: Introductionmentioning

confidence: 99%

Double Arm Robot Design, Control and Optimization using Modelica and Optimica

Breitsprecher

Wartzack²,

Erlangen-Nürnberg³

et al. 2012

Parallel and Distributed Computing and Systems / 790: Software Engineering and Applications

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A double arm robot is analyzed using the Modelica and Optimica software tools. Modelica is a tool for modeling complex physical systems whereas Optimica is provided by Jmodelica.org and is a recent easy-to-use extensible Modelica-based source for dynamic optimization. The double arm robot was not previously optimized with Optimica. The robot system consists of two rigid arms and two motors to actuate the two arms. The optimization algorithm objective is to move the tip of the robot from one position to another in a certain time with the least energy consumption. In order to program the optimization algorithm in Optimica it is necessary to write the differential equations of motion for the system which are derived using the Lagrangian's formula. The optimization algorithm for the double arm robot is programmed in Optimica and the results are plotted and compared. Furthermore, a closed loop PID controller is implemented for each actuator in Modelica with the objective of moving the tip of the robot from one position to another. The simulation results of the controlled robot are shown and compared with those of Optimica.

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Optimization of the dynamic behavior of a solar distillation cell by Model Predictive Control

Cited by 6 publications

References 29 publications

Optimal Design of a Solar Desalination Unit with Heliostats

Optimal Design of a Solar Desalination Unit with Heliostats

Metaheuristic Algorithm for Photovoltaic Parameters: Comparative Study and Prediction with a Firefly Algorithm

Double Arm Robot Design, Control and Optimization using Modelica and Optimica

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