International Meeting on Advanced Technologies in Energy and Electrical Engineering

Machine 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.

The 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.

Water 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.

A 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).

The 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.

This 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:

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.

The 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.

The 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.

Objective - This article concerns the integrated scheduling of tasks and maintenance activities under energy constraints. Indeed, scheduling under energy constraints and unavailability of the machine is often treated separately because of its complexity. In this paper, we present a new model for solving the energy constraint and machine downtime problem and use the CPLEX solver to solve the MILP mixed linear programming model to minimize the energy bill.

Methodology / Approach - we propose a mixed integer linear programming model proposed to solve the problem of scheduling under energy and unavailability constraints of the machine in order to minimize the energy bill using the CPLEX solver. In total, 36 instances were studied to evaluate parallel machine problems of different sizes.

Results - we note that for the cases studied in the “parallel machines” workshops, the CPLEX solver is able to solve the 24 instances out of 45 for our model. In general, the results obtained following the modeling of our model are better and optimal.

Energy efficient management is one of the main problems that the world is currently facing due to the scarcity of natural resources. In Algeria, As shown in Figure 1, most of the energy consumption is devoted to fuel energy: oil, natural gas and coal.

The residential sector represents the most energy-consuming sector in terms of its use for heating and cooling. Indeed, it is one of the main factors affecting energy expenditure and greenhouse gas emissions. In Algeria, this sector is considered as one of the most energy-intensive sectors and consumes more than 35% of the total final energy, as indicated in Figure 2.

In this context, the construction of a zero energy building has become a necessity to control energy consumption in the residential sector. Our aim is to develop alternatives to reduce this energy consumption and to minimise the use of non-renewable energies (fuel energies) which is the main factor in the Algerian economy.

Renewable energies can be a new source of energy for the country’s economy and an alternative for electricity production, especially solar photovoltaic energy, as shown in Figure 3.

Algeria has an extremely high solar potential. The quality of Algerian solar radiation allows Algeria to rank among the three countries with the best solar resources in the world, with an annual sunshine of more than 3,500 hours and an irradiation of 4 to 7 kWh/m²/day [3].

The national energy policy recommends increasing the contribution of renewable energies in the energy balance; the objective is to achieve a contribution of around 6% in the balance of electricity production by 2020 through photovoltaic, solar thermal and wind energy sectors in favour of the launch of several programmes [3].

Our objective is to define the impact of grid-connected or isolated solar photovoltaic systems on electricity production in the residential sector in Algeria. Our research will contribute to the implementation of an environmental approach to reduce energy consumption in the residential buildings in order to obtain a building that produces as much energy as it consumes by using selfconsumption and solar energy.

Millimeter wave (mm-wave) is today’s breakthrough frontier for emerging wireless mobile cellular networks, wireless local and personal area networks, simultaneous energy/data transfer, wearable networks, vehicular communications and radar. Directive antennas emerge as a key component in most of these applications driven by the requirement to meet stringent link budget specifications and/or provide good imaging resolution. Many practical scenarios, (requiring e.g. continuous service when an obstacle blocks the line of sight, tracking of mobile terminals placed on a moving vehicle or scanning within a given field of view) further poses the need for antennas with beam-steering capabilities. Coupled with commercial viability constraints, the development of mm-wave directive antenna systems with beam-steering capabilities that also maintain compatibility with low-cost mass-manufacturing process and easy integration with the front-end has emerged as a key challenge for both communication and sensing applications.

Among the traditional in-package directive antenna solutions, phased arrays involve a cumbersome feeding network which is impractical for mass-market mm-wave applications. Reflector and lens antenna architectures, although compatible with a simpler feeding network, are bulky and typically require mechanical reconfiguration to perform beam scanning, adding significant complexity and cost, increase power consumption and significantly limiting the scanning speed.

Voltage Controlled Oscillators (VCOs) are critical blocks in circuits such as the Phase Locked Loops (PLLs) used in telecommunication systems [1]. Some characteristics of a VCO, like low phase noise or high quality factor performances, depend on the characteristics of the varactors. To have powerful features, the VCO requires an optimal design of the varactors. For this purpose, we use the EKV transistor model [2] as an analytical simulation model for the C-V characteristics of the varactor and Artificial Bee Colony (ABC) algorithm [3] as an optimization tool.

Artificial Bee Colony algorithm is nature-inspired metaheuristic, which imitates the foraging behavior of bees, and we chose it over other metaheuristic because it is easy to implement, has fewer control parameters, and could be easily modified and hybridized with other metaheuristic algorithms. The ABC consists of three groups of artificial bees: employed bees, onlookers and scouts.

The onlooker bees select a food source with the probability given in (1):

In order to produce a candidate food position from the old one, the ABC uses the following expressions (2) and (3):

The circuit that we use in our work is an inversion mode NMOS varactor [4] as shown in the MOS transistor in Fig.1. Hence, in order to evaluate the quality of the varactor design, an objective function which represent the quality factor (Q) is defined in the following expression:

The total varactor capacitance can be determined by:

With W is the transistor width, L is the transistor length and N$ is the number of fingers, should be optimized in order to maximize the quality factor Q.

The following table shows the optimization results given by the ABC technique and a comparison with the already published work results. Figures 2 show the C-V characteristics of the varactor under the ADS tools for 1.0 GHz and the figure 3 the simulation of the Q factor.

The optimization values obtained using ABC method are similar to those obtained using the evolutionary algorithm (GA) [5] with a slightly higher coefficient of quality factor.