Search results

This paper aims to propose a novel grid current control strategy for grid-connected voltage source converters (VSCs) under unbalanced grid voltage conditions.

A grid voltage dynamic model is represented in symmetrical positive and negative sequence reference frames. A proportional controller structure with a first-order low-pass filter disturbance observer (DOB) is designed for power control in unbalanced voltage conditions. This controller is capable of meeting the positive sequence power requirements, and it also eliminates negative sequence power components which cause double-frequency oscillations on power. The symmetrical components are calculated by using the second-order generalized integrator-based observer, which accurately estimates the symmetrical components.

Proportional current controllers are sufficient in this study in a wide range of operating conditions, as DOB accurately estimates and feed-forwards nonlinear terms which may be deteriorated by physical and operating conditions. This is the first reported scheme which estimates the VSC disturbances in terms of symmetrical component decomposition and the DOB concept.

The proposed method does not require any grid parameter to be known, as it estimates nonlinear terms with a first-order low-pass filter DOB. The proposed control system is implemented on a dSPACE ds1103 digital controller by using a three-phase, three-wire VSC.

This paper aims to propose a robust cascaded controller based on proportional-integral (PI) and continuous sliding mode control.

Cascaded control structure is an attractive control scheme for DC-DC power converters. It has a two-loop structure where the outer loop contains PI controller and the inner loop uses sliding mode control (SMC). This structure thus combines the merits of both the control schemes. However, there are some issues that have prohibited its adoption in industry, the discontinuous nature of SMC which leads to variable switching frequency operation and is hard to realize practically. This paper attempts to overcome this issue by changing the discontinuous functionality of SMC to continuous by utilizing the concept of equivalent control.

The robustness of the controller designed is verified by considering various cases, namely, ideal case with no uncertainties, sudden variation of input supply voltage, load resistance, reference voltage, circuit-parameters and for noise disturbance. The controller effectiveness is validated by simulating the DC-DC boost and Cuk converters in SimPowerSystems toolbox of MATLAB/Simulink. It is shown that the performance of the proposed controller is satisfactory, and both reference output voltage and inductor current are tracked with little or no sensitivity to disturbances.

The results for various scenarios are interesting and show that the controller works quite satisfactorily for all the simulated uncertainties.

To propose an improved algorithm for the state estimation of distribution networks based on the unscented Kalman filter (IUKF). The performance comparison of unscented Kalman filter (UKF) and newly developed algorithm, termed Improved unscented Kalman Filter (IUKF) for IEEE-30, 33 and 69-bus radial distribution networks for load variations and bad data for two measurement noise scenarios, i.e. 30 and 50 per cent are shown.

State estimation (SE) plays an instrumental role in realizing smart grid features like distribution automation (DA), enhanced distribution generation (DG) penetration and demand response (DR). Implementation of DA requires robust, accurate and computationally efficient dynamic SE techniques that can capture the fast changing dynamics of distribution systems more effectively. In this paper, the UKF is improved by changing the way the state covariance matrix is calculated, to enhance its robustness and accuracy under noisy measurement conditions. UKF and proposed IUKF are compared under the cummulative effect of load variations and bad data based on various statistical metrics such as Maximum Absolute Deviation (MAD), Maximum Absolute Per cent Error (MAPE), Root Mean Square Error (RMSE) and Overall Performance Index (J) for three radial distribution networks. All the simulations are performed in MATLAB 2014b environment running on an hp core i5 laptop with 4GB memory and 2.6 GHz processor.

An Improved Unscented Kalman Filter Algorithm (IUKF) is developed for distribution network state estimation. The developed IUKF is used to predict network states (voltage magnitude and angle at all buses) and measurements (source voltage magnitude, line power flows and bus injections) in the presence of load variations and bad data. The statistical performance of the coventional UKF and the proposed IUKF is carried out for a variety of simulation scenarios for IEEE-30, 33 and 69 bus radial distribution systems. The IUKF demonstrated superiority in terms of: RMSE; MAD; MAPE; and overall performance index J for two measurement noise scenarios (30 and 50 per cent). Moreover, it is shown that for a measurement noise of 50 per cent and above, UKF fails while IUKF performs.

UKF shows degraded performance under high measurement noise and fails in some cases. The proposed IUKF is shown to outperform the UKF in all the simulated scenarios. Moreover, this work is novel and has justified improvement in the robustness of the conventional UKF algorithm.

The purpose of this paper is to propose successive-over-relaxation (SOR) based recursive Bayesian approach (RBA) for the configuration identification of a Power System. Moreover, to present a comparison between the proposed method and existing RBA approaches regarding convergence speed and robustness.

Swift power network configuration identification is important for adopting the smart grid features like power system automation. In this work, a new SOR-based numerical approach is adopted to increase the convergence speed of the existing RBA algorithm and at the same time maintaining robustness against noise. Existing RBA and SOR-RBA are tested on IEEE 6 bus, IEEE 14 bus networks and 48 bus Danish Medium Voltage distribution network in the MATLAB R2014b environment and a comparative analysis is presented.

The comparison of existing RBA and proposed SOR-RBA is performed, which reveals that the latter has good convergence speed compared to the former RBA algorithms. Moreover, it is robust against bad data and noise.

Existing RBA techniques have slow convergence and are also prone to measurement noise. Their convergence speed is effected by noisy measurements. In this paper, an attempt has been made to enhance convergence speed of the new identification algorithm while keeping its numerical stability and robustness during noisy measurement conditions. This work is novel and has drastic improvement in the convergence speed and robustness of the former RBA algorithms.

The purpose of this paper is to establish some acceptable trends in the contamination of roadside vegetation and to define a safety limit regarding the effects of metal contamination arising from various toxic metals deposited on leaves of the plants and in the bulk of the fruits.

Distribution of essential and non‐essential elements on the surface of leaves and in bulk of fruits of specific areas of Multan (Pakistan) was estimated and correlated with World Health Organization (WHO) standards. The metal concentrations are expressed as X ± SD for triplicate sub samples with the SD of ± 1.0‐1.5 per cent. The maximum metal levels in bulk of various fruits were calculated for FE, followed by Cu, Zn and Co.

In samples from roadside leaves Fe (823 mg/kg) was found to be the dominant metal, whereas the observed threshold level was found for Co (17.25 mg/kg). The non‐essential elements in various fruits, the Cr was found to be the dominate (16 mg/kg) on mean basis as compared with other metals in fruits. The increasing order of non‐essential metals on the surface of roadside leaves was Li < Ni < Sr < Pb < Cr. The results revealed that metal concentration decreases with increase in distance from roadside (10, 30 and 50 m) with negative correlation coefficient.

This paper shows that the metals concentration in case of all fruit samples fall within the permissible safe limit, whereas the metal concentrations on the surface of roadside leaves were found to surpass the safe limits laid down by the WHO. It is consequently suggested that edible portions of vegetation and fruits near highways should be consumed cautiously.

In current vista of corporate governance (CG), whistleblowing (WB) has become critical for practitioners, researchers and other stakeholders. This study aims to identify, prioritize and analyze the interrelationships of determinants of effective WB on the basis of opinion of a medium-sized panel of experts.

It is a cross-sectional descriptive study conducted in the field setting. A self-administered structured questionnaire was used to collect primary data from the respondents. This study follows an interpretive structural modeling (ISM) approach.

This study found that the factor “specific law for WB” has maximum driving power but minimum dependence and occupies bottom level (the most critical level) in the ISM model. The Matrice d’Impacts Croisés Multiplication Appliquée á un Classement analysis revealed that there is no autonomous and dependent factor in the model. There are eight linking factors and only one independent factor.

The study found that the factor “specific law for WB” has maximum driving power but minimum dependence and occupies bottom level (the most critical level) in the ISM model. The Matrice d'Impacts Croisés Multiplication Appliquée á un Classement analysis revealed that there is no autonomous and no clear-cut dependent factor in the model. There are eight linking factors out of which five have high dependence as well, and there is only one independent factor.

This study has ensued in identification of significant challenging issues in WB and in development of interrelationships to gain insights into priority of these issues. This study uses limited primary data in context of Pakistan; therefore, generalizability of the findings is limited.

This study presents a novel theoretical and conceptual model focused on effective WB. The value of the study on effective WB is highly relevant for today’s complex organizations but incipient in literature. The insights provided by the study have vital importance for corporations to embark on the regime of reforms in CG.

The key purpose of the current study is investigating the direct impact of information technology (IT) assimilations, flexible IT infrastructure, and supply chain competencies (supply side, demand side) on the supply chain performance of manufacturing firms. Meanwhile, the study has also estimated the mediating role of supply chain agility (SCA). Among 360 selected respondents for the underlying research, only 267 respondents have responded well and returned them back, thereby indicating 74% response rate for the survey. For the inferential analysis, the Partial Least Square Structural Equation Modeling was performed in Smart PLS 3.0. In context to this study, process compliance is the adherence and the execution of supply chain processes, including the processes related to distribution and production of management processes. On the basis of this theoretical background, the demand and supply-side competence are considered as the firms’ internal aspects. As a dynamic capability, the SCA enables firms to influence and respond to the firm’s external environment. Thus, the presence of such competencies allows to react against market developments. The resource-based view theory supports this argument, and states that competencies is an effective resource for developing dynamic capabilities.

The study was planned to examine the impact of subjective norms on the behavioural intentions of Thai e-banking users. Additionally, the study has also examined the mediating role of perceived usefulness of e-banking in the relationship between the subjective norms and e-banking adoption. The subjective norms construct in this study was decomposed into societal descriptive and injunctive norms, and personal descriptive and injunctive norms. It is clear from the literature review that highly inconsistent findings were reported between perceived usefulness and subjective norms because of the contradiction in the findings obtained by the researchers. This occurred may be because trivial attention was given to the relationship between subjective norm and perceived usefulness. In current research, it is argued that there are many advantages of e-banking adoption which includes mobility, convenience and 24-hour accessibility anywhere anytime with no physical limitation of location as required in old-styled e-commerce. For that reason, it is hypothesized that people who believe that these advantages would result in the improvement in their performance are expected to create a positive environment for technology adoption. In the latest quantitative research development, the partial least squares (PLS) path modelling is considered to be unsuitable in determining the validity of the model. For this purpose, a two-step process is implemented in current research. The results of the present study, argued that e-banking is adopted voluntarily and the existence of high social norms in collectivist culture greatly influences the potential adopters' attitude and behaviour by the opinions of their significant others particularly in Thai context.

This study divulges the new concept of employees' withdrawal behavior during the global pandemic (COVID-19). The study's purpose is to draw new insights into workplace stressors and employee withdrawal behavior. The study also considers the mediating role of aggression and the moderating role of COVID-19 worry and cyberloafing.

The study's statistical population consists of 384 frontline hotel employees from Pakistan's hospitality industry. Statistical analysis SPSS and AMOS were utilized to conduct Pearson's correlation and multilevel regression analysis. A Hayes process technique has been used for moderation and mediation analysis.

The results demonstrated that COVID-19 has a psychological effect on the employee's mental health and higher turnover intention during the current pandemic. Workplace stressor is significantly related to aggression and employee withdrawal behavior. Aggression mediates the relationship between workplace stressors and withdrawal behavior. The study results show that COVID-19 worry moderates between workplace stressors and aggression – notably, cyberloafing moderate aggression and withdrawal behavior.

The government and hospitality organizations need to implement crisis management strategies in response to COVID-19. This research can help management in coping with employees' mental and psychological challenges. Employees' mental health has been affected during the current global health crises. Firms should encourage their employees psychologically while going for downsizing.

This study enhances the existing literature on the COVID-19 crisis in Pakistan's hospitality industry. This study contributes to new understandings of employees' withdrawal behavior in the hospitality industry. The research shows how COVID-19 affects employees' turnover, mental health and job performance in the hospitality industry. Employees are facing mental and physiological challenges during COVID-19. The study fills a considerable gap in the hospitality industry by exploring the role organization's crisis management during a global pandemic.

This paper aims to investigate small and medium enterprises’ (SMEs) owner–managers’ awareness, willingness and perceptions concerning Islamic financing instruments as an alternative sourcing decision in SMEs’ businesses.

The research employed mixed methods to gather data. A questionnaire survey was conducted via face-to-face interviews with 385 SME owner–managers operating in Muscat, Oman’s capital city, along with face-to-face discussion on Islamic finance with 86 SME owner–managers. Descriptive and thematic analysis were used to analyse the data.

The findings indicate that SME owner–managers are aware of Islamic banking principles and have knowledge of Islamic financial instruments, despite Islamic finance being new to Oman. Interestingly, although the majority of the participants indicated their intention to adopt this new finance method, they were motivated by special requirements other than finance. Their positive perception of Islamic financing methods could play a significant role in developing the Islamic banking industry.

The research is limited in that its data came only from Omani SME owner–managers in Muscat. Future research could investigate wider samples. Secondly, the study’s findings lack generalisability to larger and public enterprises, because only SME owner–managers were surveyed.

This study will be important for policy makers concerned about SMEs’ financing, Islamic financial institutions and new entrants into the Islamic banking industry, as it provides empirically evidence of Omanis’ views, and more specifically those of Omani SME owner–managers, on the recent introduction of Islamic finance into the country. The insights this study offers should help them to develop the strategies required to attract SMEs and to construct policies and regulations to improve Oman’s Islamic banking industry.

The research is significant, as it is the first study to investigate the awareness, willingness and perceptions of Omani SMEs regarding Islamic banking in Oman. Even though all Omanis are Muslims, Oman was the last of the six-nation Gulf Cooperation Council countries to introduce Islamic finance. Thus, this emerging market provides an important basis from which to extend future research on Islamic finance to other potential Islamic finance markets.