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• This work proposes a multi-objective voltage control for multiple Electric Springs (ESs) in active unbalanced distribution systems. • This multi-objective voltage control relies on a robust ES model, a modified backward/forward solution method (BFSM), and a continuous genetic algorithm (CGA). • The proposed ES model is suitable for unbalanced conditions and can be implemented at any network location in single-, two-, and three-phase connections. • It considers the self and mutual effects of the distribution line and the power flow of the elements connected at the point of common coupling (PCC) to determine the ES output voltage. This work proposes a multi-objective voltage control for multiple Electric Springs (ESs) in active unbalanced distribution systems, where the goal is to provide a suitable simulation scheme to control the ESs in real-time applications. This multi-objective voltage control relies on a robust ES model, a modified backward/forward solution method (BFSM), and a continuous genetic algorithm (CGA). The proposed ES model is suitable for unbalanced conditions and can be implemented at any network location in single-, two-, and three-phase connections. Also, it considers the self and mutual effects of the distribution line (DL) and the power flow of the elements connected at the point of common coupling (PCC) to determine the ES output voltage. The ES model is adapted to the BFSM to quickly and reliably solve the power flow in the distribution network. Besides, the CGA simultaneously solves the mode of operation and the amount of reactive power exchange of the ESs to minimize power losses, voltage unbalance, and voltage deviation. The proposed voltage control is evaluated on an active distribution network based on a modified IEEE 13-bus for considering both load variations and power intermittences. [ABSTRACT FROM AUTHOR]

The application of signal processing techniques is a fundamental step for fault diagnostic methodologies. The application of empirical mode decomposition (EMD)-based methods such as classic EMD, ensemble EMD (EEMD), and complete EEMD (CEEMD) is presented in this work for the analysis of inrush current signals. This analysis leads to the detection of short-circuited turns in transformers. Results show that CEEMD provides the best performance, as it readily extracts the information related to the fault, requiring of acceptable computational resources. Actual inrush current signals of a transformer with short-circuited turns are also considered. The number of short-circuited turns ranges from 5 to 40. Useful indices, such as the Shannon Entropy, Energy, and root-mean-square value, are obtained from the information provided by the CEEMD approach. These indices are analyzed for both the transient state and the steady state of the current signals, providing the proper quantification of the fault severity. [ABSTRACT FROM AUTHOR]

[Display omitted] • Novel solar assisted fixed bed reactor was designed to be used for torrefaction. • Ashe Juniper wastes was thermally treated to produce energy densified solid fuel. • Highest energy yield was at 210 °C and highest energy densification was at 360 °C. • Numerical model was derived based on the experimental results. • Carbon footprint analysis indicated 1.3 ∼ 1.6 tCO 2 /ton-AJ reduction effect. In this work, designs a novel solar-driven thermochemical conversion reactor to torrefy biomass waste (Ashe Juniper) for further pyrolysis applications. The effect of torrefaction temperature and residence time on the properties of biomass waste was investigated and results showed that torrefaction temperature dominates the properties of product compared to the effect of residence time. The highest energy yield (over 90%) was obtained at 210 ℃ while the highest energy densification (∼1.51) was achieved at 360 ℃. In addition, a two-step kinetic numerical model was used to analyze and predict the experimental process (kinetic rates) and results (C, H, and O contents) based on the experimental results. The analysis results showed that the predicted results are in good agreement with the practical results after torrefaction, indicating the feasibility of this numerical model for torrefaction and pyrolysis applications. The carbon footprint analysis showed that reduction effect of 1.3 ∼ 1.6 tCO 2 /ton-AJ can be obtained by torrefaction of Ashe Juniper. Finally, the prospects for future industrial applications of solar-driven torrefaction reactors discussed as one of affordable and clean energy. [ABSTRACT FROM AUTHOR]

Induction motors (IMs) are one of the most commonly used rotating machines in industry. In order to avoid downtimes and economical losses, development of condition monitoring systems is of paramount importance. Inter-turn short circuit (ITSC) faults are one of the most commonly occurring faults in IMs. In this regard, motor current signature analysis (MCSA) is a low cost and noninvasive technique, requiring only the current signal to perform the condition monitoring. Also, the development of tools that emulate IM faults, allow the design, calibration and validation of MCSA based techniques. In this work, a multilayer neural network-based model to reproduce the current signatures associated with ITSC fault conditions is presented. The model considers both five severities of ITSC faults and four torque levels. This model is also implemented on a power hardware in the loop scheme to provide a novel tool to test condition monitoring systems of IMs. [Display omitted] [ABSTRACT FROM AUTHOR]