In this paper, a proposed electro-thermal model of cable terminations is presented. The cable terminations under study are exposed to a square-pulse voltage applied at different switching frequencies. The purpose of the model is to predict the temperature distribution inside the cable termination as a means of determining the location and value of the maximum temperature. The model is based on fundamental heat transfer mechanisms: conduction, convection, and radiation. Two different distribution classes of cable terminations have been examined. A comparison of the simulated temperature rises with actual measurements reveals good agreement.
The accuracy of characteristic the PV cell/module/array under several operating conditions of radiation and temperature mainly relies on their equivalent circuits sequentially; it is based on identified parameters of the circuits. Therefore, this paper proposes a modified interactive variant of the recent optimization algorithm of the rung-kutta method (MRUN) to determine the reliable parameters of single and double diode models parameters for different PV cells/modules. The results of the MRUN optimizer are validated via series of statistical analyses compared with five new meta-heuristic algorithms including aquila optimizer (AO) , electric fish optimizer (EFO), barnacles mating optimizer (BMO), capuchin search algorithm (CapSA), and red fox optimization algorithm (RFSO) moreover, twenty-five state-of the art techniques from literature. Furthermore, the identified parameters certainty is evaluated in implementing the characteristics of an entire system consists of series (S), and series-parallel (S-P) PV arrays with numerous dimensions. The considered arrays dimensions are three series (3S), six series (6S), and nine series (9S) PV modules. For the investigated arrays, three-dimensional arrays are recognized. The first array comprises 3S-2P PV modules where two parallel strings (2P) have three series modules in each string (3S). The second array consists of six series-three parallel (6S-3P) PV modules, and the third one has nine series-nine parallel (9S-9P) PV modules. The results prove that the proposed algorithm precisely and reliably defines the parameters of different PV models with root mean square error and standard deviation of 7.7301e −4 ± 4.9299e −6 , and 7.4653e −4 ± 7.2905e −5 for 1D, and 2D models, respectively meanwhile the RUN have 7.7438e −4 ± 3.5798e −4 , and 7.5861e −4 ± 4.1096e −4 , respectively. Furthermore MRUN provided extremely competing results compared to other well-known PV parameters extraction methods statistically as it has .
A hybrid microgrid system (HMG) is a new avenue that offers an optimal, reliable, and cost-effective solution for utilizing localized renewable energy resources over individual DC or AC microgrids. Nonetheless, the performance of the HMG varies greatly depending on the availability of renewable resources, desired services to provide, and demand system parameters. These parameters have a high impact on decision-making, reduced costs, and improved system reliability. Therefore, in this work, a reliable and robust developed multi-objective optimizer based on the hunger game search optimizer (HGSO) is proposed to attain HMG scheduling energy management schemes over a long-time horizon of 96 hours under uncertain real-time prices. The proposed strategy's main targets are retaining uninterruptible power to the load with minimal operating costs and minimal emission from the storage systems with achieving a high renewable factor. Moreover, a case study is discussed for including the battery degradation cost in the optimization process. These targets expressed via four objective functions for a HMG include grid-connected with photovoltaic and wind as renewable energy resources, besides battery, fuel cell, and supercapacitor as a storage system. The integrated system has been designed to supply the power demand for different load profiles in Egypt and the United Arab Emirates. The proposed multi-objective hunger game search optimizer (MOHGS) is compared with the recent state-of-the-art optimizers, including multi-objective versions of marine predators algorithm (MOMPA), slime mould algorithm (MOSMA), golden-eagle optimizer (MOGEO), grasshopper optimization algorithm (MOGOA), multi-verse optimizer (MOMVO), antlion optimizer (MOALO), and grey wolf optimizer(MOGWO) to evaluate the performance of the proposed power management system based MOHGS. The scheduled HMG performance is compared with the baseline system to clarify the essential outcomes for the proposed energy management approach. The obtained results confirm the proposed systems' reliability in reducing the power loss, saving the lifetime of the proposed energy storage elements, and minimizing the emissions by 43 % and 34.1 %. Furthermore, the proposed approach saves money for the customers by 184% and 4427% throughout the two studied locations via selling power for the grid compared to the baseline approach. The proposed approach achieves RF values of 86.5% and 94.2%; meanwhile, the baseline approach offers 79.3% and 93.6% for the studied locations, respectively. INDEX TERMS Energy management; Micro grid; Hunger Game Search; Multi-objective Hunger Game Search.
<span>Partial discharge is one the most important factor that leads to deteroration and failure of the power transformer transformer. Acoustic emission detection is effective method to evaluate the health index of the power transformer. Using acoustic emission (AE) sensors for partial discharge (PD) measurement is considered as one of the most promising techniques to detect and localize PD activities inside the transformer tank. On the other hand, AE waves suffer from high attenuation and reflections while traveling from the PD source to the AE sensor. The modeling of the AE wave can help to understand the behavior of the AE PD signal during its travel. In this paper, the AE PD signal is assumed to be composed of different frequencies. This work aims to investigate the influence of the frequency value on the attenuation and arrival time of the acoustic wave.</span>
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