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- Conference Proceeding
International Meeting on Advanced Technologies in Energy and Electrical Engineering
- Conference date: 22–23 Nov 2018
- Location: Fez, Morocco
- Volume number: 2020
- Published: 17 January 2020
1 - 20 of 28 results
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Solar integrated energy efficient systems for waste heat recovery of power generation industry using different eco-friendly energy materials
Authors: Radhey Shyam Mishra and Kaushalendra Kumar DubeyThe major issues of global warming and energy crisis are being discussed globally these days. The toxicity in the environment due to elevated CO2 concentrations in the atmosphere is increasing day after day. All promising savings of reducing CO2 generation, fossil fuels depletion, and control in energy price increments are achievable by the adaptation of eco-friendly energy-efficient material-based technology. The un-arrested heat (waste heat) discharge from energy-intensive industries like captive power plants, cement production, steel industry and oil-refineries has tremendous potential for multiple energy generation (heating-power & cooling) for further industrial process with dumped heat recovery. This paper explores an eco-friendly material (R134a), activated carbon-methanol based organic Rankine model and solar integrated vapor adsorption cooling system for waste heat utilization of a condenser unit in a steam power plant. The results of the proposed model analysis investigate the environmental parameters of the used material, the effect of the operating parameters and the cooling-power output.
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Soil temperature evaluation based on meteorological data
Authors: Redouane Mihoub and Sidi Mohammed El Amine BekkoucheThis study investigates soil temperature in Ghardaia based on the actual soil temperature as provided by the local meteorological data. The limestone soil is the most predominant type in the center and the east of Ghardaïa, whereas the western part is dominated by sandstone soil.The determination of soil temperature requires knowledge of the nature of the soil. It was found that if air temperature was used as an inputparameter, that would yield results of high accuracy compared with the actual measured soil temperature. The nature of the soil affects its temperature, as well as the dephasing and the penetration of the temperature signal. The proposed methodology was validated and tested on limited data set recorded over three years of soil temperature evaluated in a semi-arid climate, In this regard, measurements of climate data have been taken into consideration to estimate the soil temperature. The objective of this study is to compare the results predicted and calculated based on the measured meteorological data (solar radiation, humidity, etc.), and compare the results with those of soil temperature at the unit of application. The experimental results show that the model was highly qualified for estimating soil temperature with high performance accuracy.
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Mathematical models of classification algorithm of Machine learning
Authors: Nabanita Dutta, Umashankar Subramaniam and Sanjeevikumar PadmanabanMachine learning algorithm has brought the augmenting change in the field of artificial intelligence, which espoused human discerning power in a splendid manner. The algorithm has various categories among which classification is the most popular part. Support vector machine algorithm, logistic regression, naïve bays algorithm, decision tree, boosted tree, random forest and k nearest neighbor algorithm are all under classification of algorithms. Classification process needs some pre-defined method, which leads for choosing the train data from the sample data given by the user. Decisionmaking is the heart of any classification algorithm as supervised learning stands out on the decision of the users. Hence, a strong mathematical model based on conditional probability lies behind each algorithm. This paper is a study of those mathematical models and logic behind various classification algorithms, which help to create strong decision criteria for users to make the training dataset based on which machine can predict the proper output.
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Power management based on fuzzy controller of the stand-alone hybrid photovoltaic/wind system
Authors: Ahmed Saidi, Benachaiba Chellali and Samia BenyahiaIn this paper, a kind of management strategy based on artificial intelligence control with the fuzzy logic controller consists of a “smart” power-sharing between the electrical and hydraulic networks. It can be applied in the battery state of charge and compared with the way they share the hybrid power sources between the storage devices and the electrical/hydraulic loads. A dynamic simulator of the hybrid energy system has been developed and tested using a MATLAB environment. Several tests are carried out using real meteorological data of the ADRAR region and a practical load demand profile. The simulation results show that the “coupled strategy” clearly outperforms the classical management strategies.
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Real-time distributed systems control and energy management using multi-agent technologies
Authors: Mohamed Azeroual, Tijani Lamhamdi, Hassan El Moussaaoui and Hassane El MarkhiThe microgrid distribution systems are a promising means for a broadly distributed energy resource (DER) systems integration. However, the optimal energy management and control of many energy generators, loads, and local storage units of microgrid present an important challenge. The concept with multi-agent intelligent control may become a viable solution for smart grid and microgrid architecture. In this paper, the implementation of the distributed energy management and control strategy of a smart microgrid by an intelligent multi-agent system (MAS) approach to achieve multiple objectives in real-time is proposed. The proposed MAS is built with a co-simulation platform in which the microgrid model is simulated using MATLAB/Simulink, and controlled by a MAS implemented in JADE through a middleware MACSimJX. The main purpose of this study is to develop a new approach, to control the microgrid during the fault in the main grid and to manage the energy output.
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Overview about techniques for extracting information from manuscripts
Authors: Manal Boualam, Youssef Elfakir, Ghizlane Khaissidi and Mostafa MrabtiThis paper reviews two types of writing recognition and details the phases incorporated on the online phase, which includes pretreatment, segmentation, characteristics extraction, recognition and decision.
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Concentrated photovoltaic (CPV) water pumping systems for agricultural uses: Sizing process, simulation and economic evaluation
Authors: Zineb Aqachmar, Amine Allouhi and Abdelmagid JamilWater resources are necessary for agricultural uses. During years of drought, water for grand water is used for irrigation, which is recognized as an environmentally and sustainable solution. Many works were proposed to study water pumping using photovoltaic panels, but almost none has presented a configuration using concentrated photovoltaic panels. This paper proposes a new methodology to pump water for agricultural uses based on concentrated photovoltaic technology. The objective of this work is examining a CPV system configuration that is able to supply a solar pump system to answer the needs of three isolated farms located in middle Atlas in Morocco. A detailed methodology for the design of a CPV water pumping system based on real water needs is proposed.
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Model-based strategies for fault detection and diagnosis in grid connected photovoltaic plants
More LessThe need of sustainable energy solutions is a demand nowadays due to the high electricity consumption in combination with the desired environmental friendly solutions for power production development. Photovoltaic (PV) energy, which has gained a central place in the governments’ energy policies, is a promising solution to address the aforementioned concerns. Despite the advanced tools for PV power generation, several factors can significantly affect the PV system performance by decreasing its efficiency. Indeed, PV systems are frequently exposed to different sources of faults and failures that affect the power generated by the PV modules. These faults can considerably reduce its production efficiency and the lifespan of PV arrays. This is mainly due to external interferences or faults resulting from dust accumulation on PV modules, aging of PV modules, shading, MPPT error, and inverters faults. PV plants, especially its DC side might be subject to defects and anomalies causing a drop of the overall system performance or even their total unavailability. Therefore, a real time early fault detection and diagnosis procedure is crucial, not only for lowering maintenance cost and time, but also to avoid any energy losses, damage to equipment and safety hazards.
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Comparison between Sliding Mode Control and perturb & observe MPPT methods for photovoltaic systems
Authors: Fatima Cheddadi, Youssef Cheddadi, Fatima Errahimi and Najia Es-sabiThe productivity of a photovoltaic system depends mainly on temperature and illumination. Hence, the photovoltaic system must be correctly sized to deliver the maximum energy. Several algorithms were proposed in literature to maximize the power generated by a photovoltaic panel [1,2] which allow to seek and track the maximum power point (MPP) in each value of temperature and irradiance. The principle of the MPPT command is based on the variation of duty cycle for a DC/DC converter.
In this work, we describe the operating principle of a photovoltaic PV cell. Moreover, we present an equivalent electrical model, after determining the five unknown parameters, to simulate the performance of a photovoltaic generator PVG in order to see the effect of climate change on the energy produced by the PV module through graphics. In addition, we show how we were able to optimize the power supplied by the PVG through an interface of adaptation fitted with the two famous commands of tracking the point of maximum power MPPT: perturb & observe (P&O) and Sliding Mode Controller (SMC). All the PV system is designed using Matlab/Sumilink. To analyze the performance of these two algorithms, we compare them and present the strong points of each of them for a robustness speed and performances.
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Vision-based control of a flying spherical inverted pendulum on a Quadrotor
Authors: Soukaina Krafes, Zakaria Chalh and Abdelmjid SakaA spherical inverted pendulum represents an example of a nonlinear and unstable dynamical system. It has the property of the impossibility of measurement at the ball joint. The control of under-actuated systems is currently a field of research that is very active due to their vast applications in robotics, aerospace and marine vehicles. Furthermore, the interest of the scientific community to the theme of controlling the spherical inverted pendulum has continued to increase where most of researchers have developed strategies to control the spherical inverted pendulum by applying two planar forces fx and fy along the x-axis and y-axis, respectively. However, they were all discussed in terms of decoupled techniques which means that they have considered the spherical inverted pendulum as two simple inverted pendulums which has made the region of stability limited [1]. From an application point of view, such limitations can be removed by enlarging the region of stability via adding a vertical force fz along the z-axis. In this way, the base will become capable of moving in the space in order to control the pendulum. In order to achieve this goal, this paper proposes an inverted pendulum that is attached by a ball joint to a Quadrotor such that the last enables the control of the spherical inverted pendulum in its unstable equilibrium upright position [2-3]. However, most of this research was discussed either in terms of decoupling or was considered a simple inverted pendulum with different initial conditions of the angle and angular velocity of the pendulum. In other terms, in order to control an inverted pendulum in real life, the angular positions and angular speeds must be measured using an encoder at the bearing. The thing that is impossible for the case of the spherical inverted pendulum. In this paper, the visual servoing of a spherical inverted pendulum on a Quadrotor (Fig.1) is treated. This technique will control the spherical pendulum in the vertical position based on visual information from a camera placed over the Quadrotor. The camera records images from the environment and on the basis of certain characteristic points of the observed image, the current position of the pendulum will, therefore, be derived from the desired position as shown in (Fig.2). This difference in image characteristics between the current location and the desired location is then used to generate a back stepping-based control which will cause the Quadrotor to move in order to adjust the position of the spherical pendulum in its equilibrium position (Fig.3).
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Dynamic control of a unicycle robot with double flywheels using linear quadratic regulator and linear matrix inequality
Authors: Boutaina Elkinany, Mohammed Alfidi and Zakaria ChalhUnicycle robot is a highly nonlinear system that has less number of points of contact with the floor. Accordingly, it represents a special topic for researchers to study the stability and the balancing control. This work considers the motion control of the unicycle robot with double flywheels since this construction raises issues such as highly instability on the roll, the pitch and the yaw directions. Chantarachit et al. [1] have proposed a dynamic model of a unicycle robot with double flywheels where they used a linear quadratic regulator in order to stabilize the current model. Hence, based on this model, we shall investigate the gain matrix using the LMI algorithm and compare the results with the LQR control method which is already designed by [1].
The below figures show a comparison between two linear controllers which are the LQR approach and the LMI approach. The aim of this work is to prove the effectiveness and the robustness of LMI.
Figure 2 shows that the gain found by the LMI method is able to stabilize the model within [0 ; 12] s. Hence, it is considered more effective and robust over the gain found by the LQR method.
As a perspective, a proper unicycle system model will be introduced and designed in order to achieve the main objective which is the stability control by formulating this model mathematically, then studying the stability by using the linear, nonlinear and intelligent control algorithm.
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Spatial distribution of air temperature and solar radiation in the Canarian photovoltaic greenhouse in arid climates
Authors: Kabira Ezzaeri, Hicham Fantassi, Lahcen Bouirden and Ahmed AharouneThe distribution of solar radiation and air temperature in a greenhouse are two of the main factors influencing the growth and yield of plant [1]. For this reason, studying the spatial distribution of the internal air temperature and solar radiation is very important to provide useful information for knowing the effect of the shading of photovoltaic panels on the climate parameters inside the greenhouse. In addition, the distribution of the air temperature and solar radiation depends on various factors, such as changes in external climate, the presence of the plants, covering and photovoltaic panels, solar radiation intensity, ventilation methods, the thermo physical and optical properties of the covering material, and the shape and dimensions of greenhouse [2]. However, the solar radiation significantly affected photosynthesis, growth and yield of plants.
Our work consists of studying the influence of flexible photovoltaic panels on the climate of the Moroccan Canarian greenhouse. We have installed two identical greenhouses: one greenhouse without any system of shade and the second greenhouse with a photovoltaic panels that occupied 30% of their east-west roofs in checkerboard format (Fig.1).
The dimensions of each greenhouse were (15 m length, 11 m wide, and 5 m height) in the middle and gutter height of 4 m at a roof slope of 10°. The greenhouses cover material was a plastic polyethylene (PE) film with the thickness 200 μm and light transmittance of 75%.
The inside solar radiation was measured using CMP3 pyranometers (Kipp & Zonen), having a time response of 18 μs, a maximum error of ±1.5%, a sensitivity of 5-20 μV W-1 m-2. A working temperature range of -40 to +80°C and a wavelength range of 300 to 2 800 nm. The solar radiation sensors was placed of 3 m height above the ground level, one point of measurement in the control greenhouse and nine measurement points in the photovoltaic greenhouse. However, the air temperature was measured in three levels at the center of each greenhouse. Values of solar radiation and air temperature were measured at 5 s intervals, averaged at each 10 min and recorded in a data logger (CR3000).
The results of the spatial distribution of air temperature and solar radiation comparison in the two greenhouses show that a 30% occupation of the roof of a Canarian agricultural greenhouse with flexible photovoltaic panels does not have a significant effect on the internal air temperature and solar radiation, In addition, the analysis of results showed that the internal temperature inside the photovoltaic greenhouse was decreased by 3.24°C compared to the internal temperature of control greenhouse, while the solar radiation decreased by 55% under the photovoltaic greenhouse.
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Performance improvement of partially shaded PV array using magic square view topology to mitigate the mismatching power losses
Authors: Lahcen El Iysaouy, Mohammed Lahbabi and Abdelmajid OumnadPartial Shading Conditions (PSCs) decreases the output power from photovoltaic (PV) arrays and represents multiple Maximum Power Points (MPPs) on output characteristics P-V, due to mismatching power losses between the PV panels. The main aim of this paper is to model, simulate, and enhance the performance of two PV array configurations. The two configurations are: Total Cross Tied (TCT) and a proposed configuration: Magic Square View (MSV), both of the size of 9 x 9 PV array [1-3] which is 81 PV modules in the total considered for this study under Short Wide shading patterns in order to extract the maximum power. The investigation of the enhancement of PV array configurations is carried out with regard to the comparison of the Global peak of outlet power (GP) of the proposed topology and TCT configuration. The parameters of the PV array configurations are performed in MATLAB/Simulink software.
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Design of system-on-chip for real-time nanosatellite photovoltaic curves telemetry
Authors: Smail Chtita, Saad Motahhir, Aziz Derouich and Abdelaziz El GhzizalThis work presents a design of a system-on-chip for the telemetry of photovoltaic curves of a nanosatellite in real time, based on the work reported by Gutiérrez et al. [1]. In this type of application, the limitation of memory and communication bandwidth makes it difficult to store and transmit the whole I-V characteristic curve of any solar section in real time. The proposed solution is based on the real-time calculation of the equivalent single diode model of the solar section. Thus, once the parameters calculated, recorded and transmitted, regardless of the operating conditions, the specific curve could be reproduced later. The system is based on a 32-bit LEON3 microprocessor core implemented in a FPGA. LEON microprocessors were originally designed by the European Space Agency for use in space projects requiring high reliability. Moreover, in order to design the system as simple and reliable as possible, among all the methods available in the literature to extract the five parameters of the equivalent model (Iph, Is, n, Rs and Rsh), the method Asymptote Oblique (OA) [2] was chosen for its simplicity and precision. These parameters (Iph, Is, n, Rs, Rsh) are recorded and transmitted to the ground for later reproduction using the following equation:
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1) LEON3 microprocessor, as shown in Figure 1, which executes the OA method to obtain
PV characteristic values from the detected values.
2) Electronic load, as shown in Figure 2 to set the PV output voltage to a value defined by SoC LEON3.
3) Acquisition interface, as shown in Figure 3 which allows to obtain the value of the voltage and the current of a pilot cell and to adapt them to values that can be acquired by the digital system.
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Nature-inspired algorithms for optimal active band pass filter design
Authors: Asmae El Beqal, Loubna Kritele, Bachir Benhala and Izeddine ZorkaniThe basic purpose in active filters design is to calculate the filter transfer function in order to find the adequate discrete components values (resistors and capacitors) forming those filters to provide the best performance. The selection of the component values must be from industrial series so as to reduce costs and make the design more feasible. The next step would be to investigate the optimal set of component values from the numerous possible combinations which is considered an exhausting and time consuming process. Hence, this research aims at diverting the attention towards the application of the metaheuristics, which combines high efficiency with minimal computational time.
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Observer-Based to Fault Detection and Isolation for Robot Manipulator
Authors: Khaoula Oulidi Omali, Mohammed Nabil Kabbaj and Mohammed BenbrahimThe aim of this study is to design and analyze a fault detection and isolation technique (FDI) for a class of affine nonlinear systems using observer-based technique. The observer is applied for robot manipulator in order to detect and isolate sensor fault. The simulations results prove the effectiveness, performances and the robustness of the approach.
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Backstepping approach applied to the DFIG-WECS
Authors: Hala Alami Aroussi, ElMostafa Ziani and Badre BossoufiThe growing need for energy in the world and the depletion of classical energy resources (fuels) have led researchers to develop new means of producing abundant and inexhaustible energies called “renewable energies”. In this context, we propose the study of a Wind Energy Conversion System (WECS) driven by a Doubly Fed Induction Generator (DFIG). This non-linear system is controlled by a recent approach called “Backstepping” based on Lyapunov’s theory. Hence, this work would focus on the structure of this control to reach the convergence of errors towards zero and to ensure the stability of the system. Finally, we will present the results obtained from the simulation.
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Innovative building materials for energy performance in buildings
Authors: Basma M’lahfi, Mostafa El Qandil and Driss AmegouzThe notion of sustainable development is mainly based on innovation in order to keep the life cycle of the domain under study alive, by involving new requirements that will change the methods and practices of the various stakeholders. The construction sector, whether being commercial or residential, is also integrated in the sustainable development approach since its implementation until its exploitation by the occupants.
Several countries around the world, including Morocco, are engaged in the sustainable construction process to build energy-efficient buildings capable of offering thermal comfort, a considerable reduction in energy expenditure and a significant decrease in emissions. The building sector is considered to be the most energy intensive and the second largest source of CO2 emissions after transport. The main sources of energy consumption in buildings can be due to lighting, ventilation, air conditioning, heating and hot water sanitary.
A house with low energy consumption must be planned from its conception stage and must be submitted to modifications for its energy consumption patterns by the choice of its orientation and the types of energies used in order to limit the energy consumption. In addition, energy savings can be further gained with the proper choice of innovative building materials evolved by building and civil engineering companies capable of providing thermal inertia in buildings. This is achieved by either incorporating new materials into the usual building products or by changing their basic formulas. These materials are able to provide buildings with thermal inertia since they have a low thermal conductivity able to keep lime buildings in winter and cold in summer without resorting to other energy-consuming means namely ventilation and heating.
In this context, several materials that have been proposed by previous researchers are discussed. These materials are considered sustainable solutions to ensure thermal insulation of tomorrow and can be either mineral or synthetic. Examples of mineral materials that can be used for thermal insulation are the natural basalt fiber for panels insulation and the use of pozzolan in building materials. On the other hand, examples of synthetic materials can be the corrugated cardboard panels recycled from packaging industries and hemp fibers, flax, rapeseed, date palm wood that can be used for reinforcement in building materials.
The general objective of this project is mainly to propose solutions to ensure a good thermal comfort to the buildings which can be through the development of innovative building materials based on natural fibers with focus on the date palm leaflets which are very abundant in Morocco. In this context, several analysis are possible on the leaflets and on the construction materials prepared in order to study their behavior vis-à-vis the energy efficiency in the buildings.
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An experimental comparison of supervised classifiers on two real datasets for pattern recognition
Authors: Mohammed Ngadi, Aouatif Amine, Bouchra Nassih and Hanaa HachimiIn this paper, we present a comparative study between Support Vector Machine (SVM) and Adaboost, as being two decision-based classification tools in the field of shape recognition. The aim of this work is to study their theoretical foundations, their learning algorithms and to investigate their performance in classification capacity. To compare their performance, we apply them to two famous training datasets, is widely used by the community, namely the CBCL- MIT face and Wisconsin diagnosis breast cancer (WDBC). The quality of decision of each classifier depends on the choice of its parameters and its implementation.
The field of pattern recognition [1] has witnessed a revolution since the mid-90s with the statistical learning theory and the advent of the Support Vector Machines [4] (SVM) for the resolution of detection problems, classification and regression. In recent years, a set of interdependent disciplines, concerning the information treatment, decision theory and methods of pattern recognition, Boosting methods [7] has emerged. The applications of pattern recognition are extended to include several areas such as shape recognition, the approximation of functions, image processing, speech recognition, and classification. The objective of this paper is to compare their performance in the field of the supervised classification.
The term may refer to two classes of distinct methods: the supervised classification and unsupervised classification. Non supervised methods are intended to constitute examples groups (or groups of instances) based on the observed data, without a priori knowledge. On the other hand, supervised methods use a priori knowledge on the belonging of a sample to a class to build a recognition system based on these classes. In this paper we focus on supervised classification.
The goal of supervised classification is to build, using a set of training data (training set), a classification procedure which allows predicting membership of a new example to a class. Our goal in the near future is to continue the study of SVM and Adaboost in order to test the relationships that exist between them.
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