No abstract

Agricultural greenhouse is largely answered in the agricultural sphere, despite the shortcomings it has, including overheating during the day and night cooling which sometimes results in the thermal inversion mainly due to its low inertia.The glasshouse dressed chapel is relatively more efficient than the conventional tunnel greenhouse. Its proliferation on the ground is more or less timid because of its relatively high cost [14][15][16][17][18][19][20][21][22].Agricultural greenhouse aims to create a favorable microclimate to the requirements of growth and development of culture, from the surrounding weather conditions, produce according to the cropping calendars fruits, vegetables and flower species out of season and widely available along the year. It is defined by its structural and functional architecture, the quality thermal, mechanical and optical of its wall, with its sealing level and the technical and technological accompanying [12][13].The greenhouse is a very confined environment, where multiple components are exchanged between key stakeholders and them factors are light, temperature and relative humidity [8].Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 21As a result, the greenhouse growers prefer these new technologies while optimizing the investment in the field to effectively meet the supply and demand of these fresh products cheaply and widely available throughout the year.

The socio-economic evolution of populations has in recent decades a rapid and multiple changes, including dietary habits that have been characterized by the consumption of fresh products out of season and widely available throughout the year. Culture under shelters of fruit, vegetable and flower species developed from the classical to the greenhouse agro -industrial, currently known for its modernity and high level of automation (heating, misting, of conditioning, control, regulation and control, supervisor of computer etc ...). new techniques have emerged, including the use of control devices and regulating climate variables in a greenhouse (temperature, humidity, CO 2 concentration etc ...) to the exploitation of artificial intelligence such as neural networks and / or fuzzy logic. Currently the climate computer offers many benefits and solves problems related to the regulation, monitoring and controls. Greenhouse growers remain vigilant and attentive, facing this technological development. they ensure competitiveness and optimize their investments / production cost which continues to grow. The application of artificial intelligence in the industry known for considerable growth, which is not the case in the field of agricultural greenhouses, where enforcement remains timid. it is from this fact, we undertake research work in this area and conduct a simulation based on meteorological data through MATLAB Simulink to finally analyze the thermal behavior -greenhouse microclimate energy.

Currently the climate computer offers many benefits and solves problems related to the regulation, monitoring and controls. Greenhouse growers remain vigilant and attentive, facing this technological development. they ensure competitiveness and optimize their investments / production cost which continues to grow. The application of artificial intelligence in the industry known for considerable growth, which is not the case in the field of agricultural greenhouses, where enforcement remains timid. it is from this fact, we undertake research work in this area and conduct a simulation based on meteorological data through MATLAB Simulink to finally analyze the thermal behavior -greenhouse microclimate energy . In this paper we present comparison of modeling and simulation management of the greenhouse microclimate by fuzzy logic between a wetland  (Dar El Beida Algeria) and the other arid (Biskra Algeria).

The research presented in this paper is part of a more significant effort to improve the dynamic and static performance of power generation systems using solar panels under specific climatic conditions. The solar panel can produce the greatest power only at the specified voltage and electric current levels. Environmental variables, such as random atmospheric oscillations, have a significant effect on the performance of a solar system connected to the network. Irradiation and ambient temperature are the two inputs to a PV (photovoltaic) system. Because solar radiation varies in nature, the PV system efficiency is low. To improve the efficiency of a solar PV system, several maximum power point tracking (MPPT) approaches are used. The purpose of this paper is to improve the performance of DC/DC chopper controllers and PV inverters in the face of abrupt climate change. To that end, the primary goal of this paper is to compare the following maximum power point search (MPPT) algorithms: the incremental conductance (IC) algorithm, the fuzzy logic (FL) algorithm, VSI controller, and the particle swarm optimization (PSO) strategy. These algorithms were evaluated in terms of efficiency, stability, and speed. A 100 kW PV system is design using MATLAB software 2021a version.