This paper presents a model for designing a stand-alone hybrid system consisting of photovoltaic sources, wind turbines, a storage system, and a diesel generator. The aim is to determine the optimal size to reduce the...
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This paper presents a model for designing a stand-alone hybrid system consisting of photovoltaic sources, wind turbines, a storage system, and a diesel generator. The aim is to determine the optimal size to reduce the cost of electricity and ensure the provision of electricity at lower and more reliable prices for isolated rural areas. Three scenarios for five, fifteen, and twenty rural homes were sized and analyzed using actual weather data in the rural and pastoral area of Biskra, Algeria. The SFS and SOS algorithms were used for the first time, in addition to the commonly used PSO algorithm, to compare the performance of each algorithm and achieve the goal of meeting all energy load requirements at the lowest cost. Three factors have been taken into consideration within the proposed objective function, which are the levelized cost of energy (LCOE), loss of power supply probability LPSP, and the amount of energy consumed by the dummy load. The results of the scenarios showed that the SFS algorithm outperformed the other algorithms, with the lowest cost of electricity for each of the mentioned scenarios. The levelized cost of energy (LCOE), respectively, was 0.09138 $/kWh, 0.16588 $/kWh, and 0.24862 $/kWh.
Composite plate structures are prone to damages caused by low-velocity impacts. To locate these impacts, many impact localization methods using fiber Bragg grating (FBG) sensors have been developed. However, it is dif...
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Composite plate structures are prone to damages caused by low-velocity impacts. To locate these impacts, many impact localization methods using fiber Bragg grating (FBG) sensors have been developed. However, it is difficult to achieve the high localization accuracy when impact response signals are acquired by a FBG sensing system with a low sampling frequency in previous studies. In this paper, a two-step localization method using wavelet packet energy characteristics is proposed to address this problem. The proposed impact localization method consists of the collection of impact samples, feature extraction, and two-step localization. To collect impact samples, a FBG sensing system with a sampling frequency of 5 kHz and four FBG sensors is uti-lized to acquire the response signals induced by the low-velocity impacts on a carbon fiber reinforced plastic (CFRP) plate. Then, a new impact feature, which is sensitive to the low-velocity impacts and can eliminate the influence of the impact height, is defined according to the wavelet packet energy characteristics. Finally, a two-step localization method is designed to achieve the accurate localization for the impacts, in which the first step is the impact area identification based on a feature database and the second step is the impact localization based on the stochasticfractalsearch (SFS) algorithm. The results of four sets of experiments prove the effectiveness and satisfactory performance of the proposed impact localization method for the low-velocity impact localization on the CFRP plate.
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