Renewable Energy Resources and Technologies
Abir Hmida; Abdelghafour Lamrani; Mamdouh El Haj Assad; Yashar Aryanfar; Jorge Luis Garcia Alcaraz
Abstract
Around the globe, a 60 % increase in energy demand is predicted to occur by the end of the year 2030 due to the ever-increasing population and development. With a registered temperature up to 50 °C in August 2020, which is classified as one of the hottest regions in the world, the demand for cool ...
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Around the globe, a 60 % increase in energy demand is predicted to occur by the end of the year 2030 due to the ever-increasing population and development. With a registered temperature up to 50 °C in August 2020, which is classified as one of the hottest regions in the world, the demand for cool temperatures in Gabes-Tunisia to achieve the thermal comfort of people ensuring the product storage has become more and more intense. Removing heat from buildings represents the most extensive energy consumption process. In this paper, an absorption-refrigeration system driven by solar energy is proposed. A parametric simulation model is developed based on the TRNSYS platform. A comparison between different models for global radiation calculation and experimental meteorological data was carried out. It has been proven that the Brinchambaut model seems to be the most convenient in describing the real global radiation, with an error of up to 3.16 %. An area of 22 m² of evacuated tube solar collector ensures the proper functioning of the generator and achieves a temperature up to 2 °C in the cold room.
Advanced Energy Technologies
Ming Hung Lin; Juin Hung Lin; Mamdouh El Haj Assad; Reza Alayi; Seyed Reza Seyednouri
Abstract
The optimal combination of distributed generation units in recent years has been designed to improve the reliability of distributed generation systems as well as to reduce losses in electrical distribution systems. In this research, the improved Genetic Algorithm has been proposed as a powerful optimization ...
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The optimal combination of distributed generation units in recent years has been designed to improve the reliability of distributed generation systems as well as to reduce losses in electrical distribution systems. In this research, the improved Genetic Algorithm has been proposed as a powerful optimization algorithm for optimizing problem variables. The objective function of this paper includes power loss reduction, hybrid system reliability, voltage profile, optimal size of distributed generation unit, and finally improvement of the construction cost of combined wind and solar power plants. Therefore, the problem variables are subject to reliable load supply and the lowest possible cost during the optimization process. In order to achieve this goal in this study, the IEEE standard 30-bus network is examined. The results of the system simulation show the reduction of total system losses after DG installation compared to the state without DG and the improvement of other variable values in this network. This loss index after installing DG in the desired bus has a reduction of about 200 kWh during the year and has a value equal to 126.42 kWh per year.