Search results

The purpose of studying the low voltage direct current (DC) microgrid, which uses computerised control system techniques, an orderly coordination control stratagem considering optimisation of a hybrid energy storage system (HESS) was projected in this paper.

The projected control stratagem was divided into three levels: topmost power dispatch level, transitional bus voltage regulation level and bottommost converter control level.

At the topmost power dispatch level, the cost of system stability was introduced, which is related with state of charge and discharging power of HESS.

Furthermore, the cost of system stability and HESS depreciation was compared with commercial price, and HESS switches its operating mode to discharge more at higher price or charge more at lower price to ensure the DC microgrid in economic operation. At the transitional bus voltage regulation level, DC bus gesturing is used as a control signal to achieve an autonomous decentralised operation of DC microgrid. The Matlab/Simulink simulation inveterate that the economical and autonomous decentralised operation can be achieved through the control stratagem.

A DC-DC converter plays a major role in many applications such as fuel cell, hybrid electric vehicle, renewable energy system, etc. Among these converters, the bidirectional DC-DC fly-back converters are more attractive because of their simple structure and easy control. However, the power devices present in this converter are subjected to high-voltage stresses due to the leakage inductor energy of the transformer. In order to recycle the leakage inductor energy and to minimise the voltage stress on the power devices, the purpose of this paper is to focus on the transformer less bidirectional DC-DC converter with high efficiency.

In order to reduce the switching loss, a few passive elements are added. The auxiliary circuit consists of a resonant inductor and resonant capacitors. This auxiliary circuit affords zero voltage switching function and cancels out the ripple component present in the main inductor current irrespective of the power flow direction.

In this work three topologies of bidirectional converters for BLDC motor are investigated and are compared in terms of mechanical power output and THD.

The paper presents enhanced versions of the converters.

The purpose of this paper is to analyze the Luo super boost converter coupled fragmented source inversion system (LC-FSIS) and the progress of a controller structure for energy stored. The inversion system is characterized by a diode arm structure and can be easily amassed into a conversion system for high/medium- power conversion systems.

The investigation is based on the practice of a simplified circuit established as common anode/common cathode, where all the diodes in each arm are connected to a renewable DC voltage source. In this proposed work, a novel fuzzy digital logic switching technique (FDLST) for three-phase fragmented source inversion (FSI) for enhancement in power excellence is measured to enterprise the novel fuzzy digital logic switching technique to authorize operative voltage utilization and enhanced harmonic spectrum.

Sequential circuit design using flip-flops is used in the analysis of fuzzy digital logic switching technique.

The three-phase fragmented source configuration is designed using a split DC source which is obtained from the Opto-electric source and is implemented using MOSFET. The procedure of novel FDLST reduces the Statistical Harmonic Reduction (SHR). Simulation and results are carried out to prove the dominance of designed FDLST.

According to bidirectional ability, wind application are having variable acceleration which connected large quantity of wind ability bearing system with doubly-fed induction generator (DFIG) fed by the two-stage cast converter (TSMC) system, the accentuation action for TSMC and arithmetic standard for DFIG are all deduced. The purpose of this study is for, stator accelerated action in Doubly fed induction generator and controlled by the Two Stage Cast Converter for better control.

The purpose of this study is for, stator accelerated action in Doubly fed induction generator and controlled by the Two Stage Cast Converter for better control.

Then, the beginning ancestor was set up to verify this system; the allotment of the filigree beginning after-effects are offered beneath no-load and the three plan states.

These after-effects apparent by the fact that the arrangement fed by TSMC-DFIG could apprehend the safe ability bearing accumulated to the filigree in the sub-synchronous, synchronisation and super-synchronous state; meanwhile generated sinusoidal describes the displacement factor.

Investment decisions hold immense significance for investors and eventually affect their portfolio performance. Investors are advised to weigh the costs and benefits associated with every decision in order to make rational investment decisions. However, behavioral finance research reveals that investors' choices often stem from a blend of economic, psychological and sociological factors, leading to irrationality. Moreover, environmental, social and corporate governance (ESG) factors, aligned with behavioral finance hypotheses, also sway opinions and stock prices. Hence, this study aims to identify how individual equity investors prioritize key determinants of investment decisions in the Indian stock market.

The current research gathered data from 391 individual equity investors through a structured questionnaire. Thereafter, a fuzzy analytic hierarchy process (F-AHP) was used to meet the purpose of the research.

Information availability, representative heuristics belonging to psychological factors and macroeconomic indicators falling under economic factors were discovered to be the three most prioritized criteria, whereas environmental issues within the realm of ESG factors, recommendations of brokers or investment consultants of sociological factors, and social issues belonging to ESG factors were found to be the least prioritized criteria, respectively.

Only active and experienced individual equity investors were surveyed in this study. Furthermore, with a sample size of 391 participants, the study was confined to individual equity investors in one nation, India.

This research has implications for individual investors, institutional investors, market regulators, corporations, financial advisors, portfolio managers, policymakers and society as a whole.

To the best of the authors' knowledge, no real attempt has been made to comprehend how active and experienced individual investors prioritize critical determinants of investment decisions by taking economic, psychological, sociological and ESG factors collectively under consideration.

Over the past decade, plant extracts are ultimate green candidatures to substitute the expensive and noxious synthetic corrosion inhibitors. In this regard, this study aims to focus on evaluating anti-corrosion properties of green inhibitor Cyperus rotundus (C. rotundus), a perennial herb found throughout India.

The biocompatible components present in C. rotundus extract was analyzed by gas chromatography–mass spectroscopy analysis. The corrosion inhibitory effect of C. rotundus was assessed by impedance, polarization and surface morphometric study [atomic force microscopy (AFM)]. Density functional theory (DFT) study was carried using DFT/B3LYP, and basis set used for calculations was 6-31G (d, p) using Gaussian 03 program package.

Predominant components such as octadecanoicacid, ethylester, n-hexadecanoic acid, pentanoicacid-4-oxoethyl ester, cyclotrisiloxane, hexamethyl, cyclotetrasiloxane and octamethyl were identified from the extract of C. rotundus. Impedance study demonstrated that the addition of inhibitor reduces the double-layer capacitance and increases the charge transfer resistance. Furthermore, polarization studies indicated that the extract of C. rotundus acted as a mixed-type inhibitor with decrease in corrosion current density with increase in concentration. AFM study evinced the formation of inhibitor film on mild steel surface. The donor–acceptor interactions of active sites of predominant phytoconstituents were substantiated by computational analysis (DFT).

This paper deals with the inhibition effect of extract of C. rotundus on mild steel in 0.5M H₂SO₄. C. rotundus has a capability to adsorb on the metal surface, thus hindering corrosion.

The authors examine the impacts of corporate announcements on stock returns during the pandemic stress.

The authors employ the event study methodology with the market model on a sample of 90 events (announcement and ex-date).

The authors find that all the corporate announcements do not impact the stock returns in a similar pattern. While the bonus announcement, ex-bonus and ex-split events led to positive significant abnormal returns on the event date, the rights issue and stock-split announcements failed to influence the stock returns. The findings suggest that before making such announcements, the corporates should wait until the market recovers because even the positively impacting events result in negative market responses during pandemic stress.

This study will guide the policymakers to stimulate share prices during such pandemics with the help of various corporate announcements. The investors will be assisted in understanding the stock market mechanism and making wise decisions before reacting to corporate actions during a pandemic or emergency period. While the policymakers are concerned with influencing the share prices, the investors are concerned with the composition of the risk-return parameters in their portfolio. This study will act as an essential investment tool for both.

To the best of the authors’ knowledge, the authors conduct the first-ever study to examine the impacts of corporate announcements during a pandemic stress period that significantly contributes to the literature. The authors examine the announcement effects in India and accurately anticipate that this study will be a pioneer in this field. This study also paves the way for future researches in this area.

The purpose of this paper is to clarify the relationship between an individual investor’s personality trait and his perceived investment performance. It proposes a novel conceptual framework that integrates social influence (as a moderating construct) and outlines the role of personality in determining the perceived investment performance during the investment decision-making process.

A questionnaire-based survey was conducted to collect responses from 396 individual investors through stratified and quota sampling approach. The collected data were then analysed using both hierarchical regression analysis and structural equation modelling to evaluate the strength of the relationship between the constructs, namely, personality trait, perceived investment performance and social influence.

This study suggests that social influence positively moderates the relationship between extraversion-perceived investment performance, whereas it negatively moderates the relationship between agreeability-perceived investment performance.

This study has certain limitations. First, this work follows a modelling approach which is more centred towards the prediction of relationships. Second, because of choosing a research approach (since the study has been conducted in one country, i.e. India), the results of the study may lack generalisability. Therefore, further studies could be encouraged to test the proposed hypotheses.

Insights from this study suggest that investors should look in for their personality traits while making an investment decision. In fact, psychologically modified portfolios should be developed as per the personality traits of the investors.

The study, perhaps, is the only study to apply social influence in a framework using Big Five personality traits as a possible factor to understand the individual differences in terms of perceived investment performance.

Based on the positive features of the shark smell optimization (SSO) algorithm, the purpose of this paper is to propose a method based on this algorithm, dynamic voltage and frequency scaling (DVFS) model and fuzzy logic to minimize the energy consumption of integrated circuits of internet of things (IoT) nodes and maximize the load-balancing among them.

Load balancing is a key problem in any distributed environment such as cloud and IoT. It is useful when a few nodes are overloaded, a few are under-loaded and the remainders are idle without interrupting the functioning. As this problem is known as an NP-hard one and SSO is a powerful meta-hybrid method that inspires shark hunting behavior and their skill to detect and feel the smell of the bait even from far away, in this research, this study have provided a new method to solve this problem using the SSO algorithm. Also, the study have synthesized the fuzzy logic to counterbalance the load distribution. Furthermore, DVFS, as a powerful energy management method, is used to reduce the energy consumption of integrated circuits of IoT nodes such as processor and circuit bus by reducing the frequency.

The outcomes of the simulation have indicated that the proposed method has outperformed the hybrid ant colony optimization – particle swarm optimization and PSO regarding energy consumption. Similarly, it has enhanced the load balance better than the moth flame optimization approach and task execution node assignment algorithm.

There are many aspects and features of IoT load-balancing that are beyond the scope of this paper. Also, given that the environment was considered static, future research can be in a dynamic environment.

The introduced method is useful for improving the performance of IoT-based applications. We can use these systems to jointly and collaboratively check, handle and control the networks in real-time. Also, the platform can be applied to monitor and control various IoT applications in manufacturing environments such as transportation systems, automated work cells, storage systems and logistics.

This study have proposed a novel load balancing technique for decreasing energy consumption using the SSO algorithm and fuzzy logic.