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These implementations not only generate excessive voltage levels to enhance the quality of power but also include a detailed investigating of the various modulation methods and control schemes for multilevel inverter (MLI) topologies. Reduced harmonic modulation technology is used to produce 11-level output voltage with the production of renewable energy applications. The simulation is done in the MATLAB/Simulink for 11-level symmetric MLI and is correlated with the conventional inverter design.

This paper is focused on investigating the different types of asymmetric, symmetric and hybrid topologies and control methods used for the modular multilevel inverter (MMI) operation. Classical MLI configurations are affected by performance issues such as poor power quality, uneconomic structure and low efficiency.

The variations in both carrier and reference signals and their performance are analyzed for the proposed inverter topologies. The simulation result compares unipolar and bipolar pulse-width modulation (PWM) techniques with total harmonic distortion (THD) results. The solar-fed 11-level MMI is controlled using various modulation strategies, which are connected to marine emergency lighting loads. Various modulation techniques are used to control the solar-fed 11-level MMI, which is connected to marine emergency lighting loads. The entire hardware system is controlled by using SPARTAN 3A field programmable gate array (FPGA) board and the least harmonics are obtained by improving the power quality.

The simulation result compares unipolar and bipolar PWM techniques with THD results. Various modulation techniques are used to control the solar-fed 11-level MMI, which is connected to marine emergency lighting loads. The entire hardware system is controlled by a SPARTAN 3A field programmable gate array (FPGA) board, and the power quality is improved to achieve the lowest harmonics possible.

This paper aims to present an improvement to the power quality of the grid by using a colliding body optimization (CBO) based proportional-integral (PI) compensated design for a grid-connected solar photovoltaic-fed brushless DC motor (BLDC)-driven water pumping system with a bidirectional power flow control. The system with bidirectional power flow allows driving the pump at full proportions uninterruptedly irrespective of the weather conditions and feeding a grid when water pumping is not required.

Here, power quality issue is taken care of by the optimal generation of the duty cycle of the voltage source converter. The duty cycle is optimally generated by optimal selection of the gains of the current controller (i.e. PI), with the CBO technique resulting in a nearly unity power factor as well as lower total harmonic distortion (THD) of input current. In the CBO technique, the gains of the PI controller are considered as agents and collide with each other to obtain the best value. The system is simulated using MATLAB/Simulink and validated in real time with OPAL RT simulator, OP5700.

It was found that the power quality of grid using the CBO technique has improved much better than the particle swarm optimization and Zeigler–Nichols approach. The bidirectional flow of control of VSC allowed for optimum resource utilization and full capacity of water pumping whatever may be weather conditions.

Improved power quality of grid by optimally generation of the duty cycle for the proposed system. A unit vector tamplate generation technique is used for bidirectional power transfer.

Non-linear power–voltage characteristics of solar cell and frequently changing output due to variation in solar irradiance caused by movement of clouds are the major issues need to be considered in photovoltaic (PV) penetration to maintain the power quality of the grid. It is important for a PV module to always function at its maximum available power point to increase the efficiency and to maintain the grid stability. A possible solution to mitigate these generation fluctuations is the use of an electric double-layer capacitor or supercapacitor energy storage device, which is an efficient storage device for power smoothing applications. This study aims to propose a power smoothing control approach to smoothen out the output power variations of a solar PV system using a supercapacitor energy storage device.

To extract the maximum possible power from a PV panel, there are several maximum power points tracking (MPPT) algorithms developed in literature. Fuzzy logic controller-MPPT method is used in this work as it is a very efficient and popular technique which responds quickly under varying ecological conditions, reduced computational complexity and does not depend on any system constraints. Fuzzy logic-based MPPT controller by Boost DC–DC converter is developed for operating the PV panels at available maximum power point. Fuzzy logic-proportional integral (PI) charge controller is implemented by Buck–Boost converter to provide the constant current and suitable voltage for supercapacitor and to achieve better power smoothing. PI charge controller is preferred in this work as it offers better outcomes and is very easy to implement.

Simulation results conclude that the proposed power smoothing control approach can efficiently smooth out the power variations under variable irradiance and temperature situations. To confirm the accurateness of the proposed system, it is validated for poly-crystalline PV module and comparison of results is done by using different case study with and without the use of an energy storage system under change in irradiance condition. The proposed system is developed and examined on MATLAB/Simulink environment.

The performance comparison between PV power output with and without the use of a supercapacitor energy storage device under different Case Studies shows that the improved performance in smoothing of power output was achieved with the use of a supercapacitor energy storage device.

This paper aims to introduce the quasi impedance source inverter (qZSI)-based static compensator (STATCOM), which is incorporated into the hybrid distributed power generation system for enhancement of power quality. The distributed power generation system includes the photovoltaic (PV), wind energy conversion system (WECS) and battery energy storage system.

The WECS is used by the self-excited induction generator (SEIG) and the flywheel energy storage system (FESS). To regulate its terminal voltage and frequency, the SEIG requires adjustable volt-ampere reactive (VAR). A combination of a STATCOM and a fixed condenser bank usually serves to satisfy the VAR demand. The maximum correntropy criterion-based adaptive filter technique (AFT) is proposed to control the qZSI-STATCOM and to guarantee that the voltage at the SEIG terminal is harmonic-free while providing non-linear three-phase and single-phase loads.

The coordinated operation of the suggested voltage control and flywheel control systems ensures that load voltage and frequency are retained in their respective values at very low harmonic distortions regardless of wind speed and load variation. The simulation and experimental studies are carried out under different load conditions to validate the efficiencies of the PV-assisted STATCOM.

To improve system stability and minimize total costs, extra load current sensors can also be avoided. This paper proposes to control the SEIG terminal voltage and harmonic elimination in the standalone WECS systems using maximum correntropy criterion-based AFT with a fuzzy logic controller.

This research introduces an innovation strategy aimed at bolstering the reliability of a renewable energy resource, which is hybrid energy systems, through the application of a metaheuristic algorithm. The growing need for sustainable energy solutions underscores the importance of integrating various energy sources effectively. Concentrating on the intermittent characteristics of renewable sources, this study seeks to create a highly reliable hybrid energy system by combining photovoltaic (PV) and wind power.

To obtain efficient renewable energy resources, system designers aim to enhance the system’s reliability. Generally, for this purpose, the reliability redundancy allocation problem (RRAP) method is utilized. The authors have also introduced a new methodology, named Reliability Redundancy Allocation Problem with Component Mixing (RRAP-CM), for optimizing systems’ reliability. This method incorporates heterogeneous components to create a nonlinear mixed-integer mathematical model, classified as NP-hard problems. We employ specially crafted metaheuristic algorithms as optimization strategies to address these challenges and boost the overall system performance.

The study introduces six newly designed metaheuristic algorithms. Solve the optimization problem. When comparing results between the traditional RRAP method and the innovative RRAP-CM method, enhanced reliability is achieved through the blending of diverse components. The use of metaheuristic algorithms proves advantageous in identifying optimal configurations, ensuring resource efficiency and maximizing energy output in a hybrid energy system.

The study’s findings have significant social implications because they contribute to the renewable energy field. The proposed methodologies offer a flexible and reliable mechanism for enhancing the efficiency of hybrid energy systems. By addressing the intermittent nature of renewable sources, this research promotes the design of highly reliable sustainable energy solutions, potentially influencing global efforts towards a more environmentally friendly and reliable energy landscape.

The research provides practical insights by delivering a comprehensive analysis of a hybrid energy system incorporating both PV and wind components. Also, the use of metaheuristic algorithms aids in identifying optimal configurations, promoting resource efficiency and maximizing reliability. These practical insights contribute to advancing sustainable energy solutions and designing efficient, reliable hybrid energy systems.

This work is original as it combines the RRAP-CM methodology with six new robust metaheuristics, involving the integration of diverse components to enhance system reliability. The formulation of a nonlinear mixed-integer mathematical model adds complexity, categorizing it as an NP-hard problem. We have developed six new metaheuristic algorithms. Designed specifically for optimization in hybrid energy systems, this further highlights the uniqueness of this approach to research.

The purpose of this study is to establish the relationship between chief executive officer (CEO) power, audit committee effectiveness and earnings quality in regulated firms in Uganda.

The authors employed cross-sectional and correlational research designs, based on a sample of 136 regulated firms in Uganda. Data were collected using a questionnaire survey from Chief Finance Officers and Chief Audit Executives. Data were analyzed using a Statistical Package for Social Sciences and Partial Least Squares Structural Equation Modeling.

Results indicate that CEO power causes negative variances in earnings quality. The results also reveal that audit committee effectiveness positively relates relatively similarly with earnings quality. In addition, CEO power and audit committee effectiveness are negative and significantly related. The results further indicate that CEO power and earnings quality are mediated by audit committee effectiveness.

CEO power creates an opaque accounting environment which may leave the stakeholders unable to evaluate the true economic reality of the firm. Audit committee effectiveness is an important enabler for reporting high-quality earnings even in the presence of a powerful CEO.

This study contributes toward a methodological stance of using perceptions to understand earnings quality in regulated firms in Uganda. This is probably the first study that has specifically explored earnings quality using only the fundamental qualitative characteristics of accounting information (as proxies) as enshrined in the Conceptual Framework for Financial Reporting 2018 particularly in Uganda since Her adoption of International Financial Reporting Standards in 1998. Second, the indirect effect of audit committee effectiveness and CEO power is tested.

After completion of the case study, the participants will be able to understand the significance of quality as a pivotal domain within project management and to analyze the issues related to quality and offer logical solutions.

In this case, the Bharat Bijlee Construction Limited (BBCL) group, with a proven track record of over five decades in the transmission and distribution business in India, decided to venture into international projects, considering the prevailing stagnant domestic power sector. They secured contracts worth $85m from the “Shariket Karhaba Koudiet Eddraouch Spa,” a state-owned company responsible for power generation, transmission and distribution in Algeria. However, during the execution phase of these projects, BBCL encountered significant challenges related to product and service quality. These challenges arose due to the tight schedule constraints and cost considerations, as well as a lack of understanding of the dynamics involved in executing international projects, especially in the demanding conditions of the sub-Saharan desert. This case study addresses the complex issue of ensuring and maintaining high-quality standards in large-scale substation projects situated in the challenging environment of the sub-Saharan desert, highlighting the importance of effective project management and international project execution expertise. The case study is from quality management knowledge area and focuses on identification of root cause of quality noncompliance and for better decision-making in projects.

The teaching case is designed for undergraduate and postgraduate courses in project management, civil engineering and architecture domain. The participants will be able to understand the application of various quality tools, statistical process tools and control charts in problem identification, categorization, root cause identification and decision-making.

Teaching notes are available for educators only.

CSS2: Built environment

This paper applies a stakeholder salience theoretical framework to facilitate the understanding of the roles salient stakeholders can have in the integration of education for sustainable development, one of the important Sustainable Development Goals (SDGs), into Jordan’s university accounting education.

We used stakeholder salience theory to inform our study. This study adopted a qualitative research method. The study used semi-structured interviews to collect qualitative, open-ended data that explored the salient stakeholders’ thoughts, beliefs and feelings about their roles in influencing the integration of education for sustainable development into the Jordanian accounting curriculum.

The results indicate that education for sustainable development in accounting is important; however, most Jordanian salient stakeholders indicate their inability to integrate sustainable education into the accounting curriculum due to their lack of power to do so. The findings show that there is currently an inappropriate distribution of power, legitimacy and urgency amongst the salient stakeholders, who indicate that a progressive education solution is required in the critical area of education for sustainable development in accounting. This research indicates that a significant number of salient stakeholders would like the Jordanian government to provide power, legitimacy and urgency to enable accounting educators to become definite stakeholders as this will enable them to integrate sustainable education into the accounting curriculum.

The study is limited to Jordan only. The paper draws attention to the need for an appropriate distribution of power, legitimacy and urgency amongst salient stakeholders in Jordan.

This paper provides evidence that the salient stakeholders in this emerging economy want to make changes in their education system to address climate change concerns, an important SDG, through a better education curriculum for sustainable development in Jordanian universities.

Accounting educators should be given the power to make changes in the accounting curriculum, such as integrating education for sustainable development.

There is an inappropriate distribution of power, legitimacy and urgency amongst the Jordanian salient stakeholders and this imbalance hinders the integration of education for sustainable development into the accounting curriculum.

Quality failures in grid infrastructure construction would cause large-scale collapses in power supply and additional expenditures by reworks and repairs. Learning from quality failures (LFQF) extracts experience from previous quality events and converts them into preventive measures to reduce or eliminate future construction quality issues. This study aims to investigate the influence factors of LFQF in the construction of grid infrastructure.

The related factors of LFQF, including quality management (QM) practices, quality rectification, and individual learning, were identified by reviewing literature about organizational learning and extracting experience from previous failures. A questionnaire survey was distributed to the grid companies in North, Northeast, Northwest, East, Central, and Southwest China. 381 valid responses collected and analyzed using structural equation modeling (SEM) to test the influence of these factors on LFQF.

The SEM results support that QM practices positively affect individual learning and LFQF. Quality rectification indirectly impacts LFQF via individual learning, while the results did not support the direct link between quality rectification and LFQF.

The findings strengthen practical insights into extracting experience from poor-quality issues and continuous improvement. The contributory factors of LFQF found in this study benefit the practitioners by taking effective measures to enhance organizational learning capability and improve the long-term construction quality performance in the grid infrastructure industry.

Existing research about the application of LFQF still stays at the explorative and conceptual stage. This study investigates the related factors of LFQF, including QM practices, quality rectification, and individual learning, extending the model development of learning from failures (LFF) in construction QM.