Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

A load-shedding controller suitable for small to medium size loads is designed and implemented based on preprogrammed priorities and power consumption for individual loads. The main controller decides if a particular load can be switched ON or not according to the amount of available power generation, load consumption and loads priorities. When themaximum allowed power consumption is reached and the user want to deliver power to additional load, the controller will decide if this particular load should be denied receiving power if its priority is low. Otherwise, it can be granted to receive power if its priority is high and in this case lower priority loads are automatically switched OFF in order not to overload the power generation. The

Abstract

Electric arc furnace applications in industry are related to position system of its pole, up and down of pole. The pole should be set the certain gap. These setting are needed to calibrate. It is done manually. In this research will proposed smart hydraulic to make this pole works as intelligent using proportional directional control valve. The output of this research will develop and improve the working of the electric arc furnace. This research requires study and design of the system to achieve the purpose and representation using Automation Studio software (AS), in addition to mathematically analyzed and where they were building a laboratory device similar to the design and conduct experiments to stud

The current study was conducted to demonstrate the effects of air pollution on different biochemical parameters inCitrus aurantium plant and calculation the Air Pollution Tolerance Index (APTI). Five sites were selected tocollect plant leaves, four of them within the city of Baghdad, namely Al-Jadriya, Al-Andlous, Al-Doura and closeto the private generators to represent the urban areas and Abu Ghraib site to represent the rural area. Seasonalsamples were collected for the period from October 2016 to June 2017. Eleven biochemical parameters totalchlorophyll, ascorbic acid, leaf extract pH, relative water content, total nitrogen, total protein content, total sugarcontent, proline, electrical conductivity, cadmium and lead. The results of Citr

Leaching process applied for the extraction of bio active compounds from dried roots of (Elecampane) Inula helenium. Ethanol, hexane and distillated water were used as solvents. Roots were soaked with ethanol (5% w/v) with various concentration of ethanol (30 to 98%) at one day to know effect concentration of the solvent with concentration of bio active compound in Inula helenium. The same procedure was done using hexane as solvent. Also distilled water was used as solvent for extraction 5%(w/v) where plant material was soaked in water at different temperatures (25, 40, 65, 80, and 90) C. In all solvents undertaken, the effect of time duration on active ingredient (Thymol, Isoalatolactone, Alatolactone, 10-isobutyryl-oxy 8-9-epoxy thymol is

Concentrations of radon were measured in this study for twenty-four samples of soil distributed in six locations on the north part of Iraq. The radon concentrations in soil samples measured by using alpha-emitters registration that emits from Radon (222Rn) in (CR-39) track detector. The concentrations values were calculated by a comparison with standard samples. The results shows that the radon gas concentrations in Darbandikhan City varies from (16.60-34.04 Bq/m3), Halabja City (16.51-23.32 Bq/m3), Al Sulaimaniya City (17.61-32.25 Bq/m3), Koisnjaq City (22.04-35.65 Bq/m3), Shaqlaua City (21.10-29.10 Bq/m3) and Erbil City (22.30-34.63 Bq/m3). The average radon gas concentration in Al Sulaimaniya and Erbil governorate are (22.30 Bq/m3)