Renewable energy (RE) systems play a key role in producing electricity worldwide. The integration of RE is carried out distributed aspect via an autonomous hybrid microgrid (A-HMG) system. A-HMG concept provides series technological solutions that must be managed optimally. As solution, this paper focuses on the application recent nature-inspired metaheuristic optimization algorithm named multimodal delayed particle swarm (MDPSO). proposed applied to find minimum levelized cost (LCOE),...

The global energy demand of buildings is on the rise, driven by factors such as rapid population growth, increasing comfort, technological advances, and ongoing developments in building construction. This escalating consumption a major contributor to crisis climate change. Accurate prediction essential for gaining insight into utilization, reducing waste, enhancing comfort conditions. study aimed introduce reliable technique predicting optimizing residential buildings, with focus case...

Abstract This study proposes a hybrid Machine Learning model called PCA-LSTM to improve the prediction accuracy of indoor temperature using minimal set weather variables. In particular, this integrates an LSTM layer dedicated studying variation in time series, along with Principal Component Analysis (PCA) reduce dimensionality data. Moreover, develop n-step ahead predictive model, hourly observations seven variables collected from nearest station, including outdoor relative humidity,...

Solar systems are influenced by their functioning temperature, which is mainly a result of the ambient air temperature as well level sunlight. For this reason, we have proposed an intelligent autoregressive model based on multilayer neural networks with delayed exogenous input sequence representing Global Radiation (GSR) data to forecast Air Temperature (AT) values half hour scale in Marrakesh, Morocco, recorded during 2014. The developed will helps us monitor and overcome such problem...

Controlling the random nature of renewable energy sources such as solar radiation at ground, allows electric grid operators to better integrate it.In this paper, an intelligent datadriven model based on artificial neural network with autoregressive input sequence is developed forecast global (GSR) time series a half hour resolution in site Agdal, Marrakesh, Morocco.The database that used create was divided into two subsets.The first subset for training proposed data measured during year 2008...

Precise global solar radiation (GSR) measurements in a given location are very essential for designing and supervising energy systems. In the case of rarity or absence these measurements, it is important to have theoretical empirical model compute GSR values. Therefore, main goal this work offer, designers engineers systems, an appropriate accurate way predict half-hour (HHGSR) time series from some available meteorological parameters (relative humidity, air temperature, wind speed,...

Nowadays, the studies that address solar radiation (SR) forecasting tend to focus on implementation of conventional techniques. This provides good results, but researchers should creation new methodologies help us in going further and boost prediction accuracy SR data. The prime aim this research study is propose an efficient deep learning (DL) algorithm can handle nonlinearities dynamic behaviors meteorological data, generate accurate real-time hourly global (GSR) data city El Kelaa des...

This paper present an UHF RFID Tag wideband dipole antenna implemented on the tag, chip used in this structure is a impinj Monza electronic with real and imaginary impedance of 28 Ω -148 respectively. designed using FR4 substrate following parameters: loss tangent δ=0.025, ε r 4.3 height 1.6mm. The simulation results proposed have good performance terms gain order to 2.22 dB reflection coefficient parameter (S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML"...

Trustworthy acquaintance and accurate solar radiation measurements are a condition for designing managing energy systems. Frequently, there substantial spatial temporal lacks of measures so that predictive approaches become interest. In the present paper, an ensemble learning approach is proposed based on deep neural network technique. The suggested applied to forecast hourly time series global related Marrakech, Morocco. For purpose, developed forecasting model was trained using seven years...

This paper present a design and miniaturization of rectangular patch antenna with balanced feed. The miniaturized for passive radio frequency identification (RFID) tag witch can operate in the ultra-high (UHF), resonant is 915MHz. simulation was performed High Frequency Structure Simulator Software (HFSS). has an acceptable results terms efficiency, size, return loss (S11), Input Impedance.

The tilt angle of solar systems affect directly the conversion radiation, regardless weather conditions. To extract maximum power from panels, sunlight should fall with a sharp angle. Therefore, optimum inclination fixed panels to horizontal plane be changed regularly every month and season. prime aim this study is offer for engineers designers an efficient model based on multi-input multi output (MIMO) Elman artificial neural network (EL-ANN). predict three components hourly radiation time...

Historically, power grids have emerged as the most economical way to match diversified generation resources. After Second World War, all advanced countries chose develop a centralized electrical system transport energy throughout national territory and then distribute it various points of consumption. In this management, production is adapted an ever-increasing demand, driven by economic demographic developments. Gradually, consumption profile has changed: development uses (particularly...

A compact wide-band planar antenna is proposed using the metamaterial transmission line.The motivation of this study to overcome problem low bandwidth while designing a miniaturized antenna.The design consists rectangular patch and squareshaped split-ring resonator (SSSRR) on asymmetric ground plane.Strip lines are provided connect right plane obtain shunt inductances improve bandwidth.This has miniature physical size 20×28×1.6 mm 3 corresponding electrical 0.16λo × 0.23λo 0.013λo, where λo...

A miniaturized reconfigurable antenna with a hexagonal slot is presented. The motivation of this study to overcome the problem switching band minimum electronic components while designing antenna. property has been obtained using only two PIN diodes. suggested structure successfully permitted ability up three bands 2.36-2.81 GHz, 3.20-4.23 and 3.13-5.92 which well suitable for standard WLAN WiMAX 5.8/2.4/5.2 GHz 5.5/2.5/3.5 respectively. peck gain efficiency at resonant frequencies 2.58,...

This research presents a rigorous and intelligent techno-economic analysis of smart farm systems in the context Morocco, employing sophisticated hybrid metaheuristic framework. The primary objective is meticulous evaluation microgrid system, intricately optimizing its dimensions financial outlay to efficaciously energize situated region. comprehensive scope this study encompasses inception, optimization, scrutiny system through utilization MATLAB, versatile computational tool. Introducing an...

Occupancy detection plays a crucial role in building management, by improving living conditions and optimizing energy efficiency. So, our paper is part of this perspective divided into two parts. Initially, we delve the significance detecting occupancy buildings, emphasizing its positive impact on human well-being productivity. Subsequently, second section dedicated using Naive Bayes Classifier (NBC) to predict an office room variables like temperature, humidity, humidity ratio, light, CO 2...

This paper presents a comparative study on the prediction of energy consumption in buildings using machine learning techniques. The dataset encompasses diverse range with 8 input features and one output variable, representing consumption. primary focus is evaluating performance two prominent widely-used algorithms: Artificial Neural Networks (ANN) Random Forest (RF). results indicate promising predictive capacity both models, showcasing their effectiveness capturing intricate patterns within...

Hourly solar photovoltaic (PV) power measurements in a specific period and site are very important for designing supervising PV systems. However, most cases these measures absent. The focus of this research study is to offer systems engineers an efficient model based on Artificial Neural Network (ANN). To predict the output system installed Agadir city (320°25'39"N 9°35'53"W), Morocco. architecture has great impact convergence Network. This optimized using Genetic Algorithm (GA). aim...

In this paper., a miniaturized dual-band tag antenna has been recommended for radio frequency identification (RFID) and remote healthcare applications. This contains split-ring resonator (SRR) meanders lines that are connected with the Philips RFID/ ASIC chip. The SRR generates second resonant frequency, which helps to produce two modes of operation. Furthermore, physical volume is 16x23x1.6 mm3, equivalent circuit scheme structure extracted study its working mechanism in bands. analysis...

A novel planar antenna loaded with the dual-layer meta-surface (MS) is given in this study. The suggested structure includes a radiating element circular form of MS. main motivation study to increase radiation pattern conventional antenna. experimental results were carried out validate simulation confirm that operating frequency and band are 2.44 GHz 2.37-2.49 while gain up 7 dBi. In addition, measurement have good coherence.