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Article
Publication date: 9 April 2018

Umamaheswari Elango, Ganesan Sivarajan, Abirami Manoharan and Subramanian Srikrishna

Generator maintenance scheduling (GMS) is an essential task for electric power utilities as the periodical maintenance activity enhances the lifetime and also ensures the…

Abstract

Purpose

Generator maintenance scheduling (GMS) is an essential task for electric power utilities as the periodical maintenance activity enhances the lifetime and also ensures the reliable and continuous operation of generating units. Though numerous meta-heuristic algorithms have been reported for the GMS solution, enhancing the existing techniques or developing new optimization procedure is still an interesting research task. The meta-heuristic algorithms are population based and the selection of their algorithmic parameters influences the quality of the solution. This paper aims to propose statistical tests guided meta-heuristic algorithm for solving the GMS problems.

Design/methodology/approach

The intricacy characteristics of the GMS problem in power systems necessitate an efficient and robust optimization tool. Though several meta-heuristic algorithms have been applied to solve the chosen power system operational problem, tuning of their control parameters is a protracting process. To prevail over the previously mentioned drawback, the modern meta-heuristic algorithm, namely, ant lion optimizer (ALO), is chosen as the optimization tool for solving the GMS problem.

Findings

The meta-heuristic algorithms are population based and require proper selection of algorithmic parameters. In this work, the ANOVA (analysis of variance) tool is proposed for selecting the most feasible decisive parameters in algorithm domain, and the statistical tests-based validation of solution quality is described. The parametric and non-parametric statistical tests are also performed to validate the selection of ALO against the various competing algorithms. The numerical and statistical results confirm that ALO is a promising tool for solving the GMS problems.

Originality/value

As a first attempt, ALO is applied to solve the GMS problem. Moreover, the ANOVA-based parameter selection is proposed and the statistical tests such as Wilcoxon signed rank and one-way ANOVA are conducted to validate the applicability of the intended optimization tool. The contribution of the paper can be summarized in two folds: the ANOVA-based ALO for GMS applications and statistical tests-based performance evaluation of intended algorithm.

Details

World Journal of Engineering, vol. 15 no. 2
Type: Research Article
ISSN: 1708-5284

Keywords

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Article
Publication date: 17 January 2018

Balachandar Pandiyan, Sivarajan Ganesan, Nadanasabapathy Jayakumar and Srikrishna Subramanian

The ever-stringent environmental regulations force power producers to produce electricity at the cheapest price and with minimum pollutant emission levels. The electrical…

Abstract

Purpose

The ever-stringent environmental regulations force power producers to produce electricity at the cheapest price and with minimum pollutant emission levels. The electrical power generation from fossil fuel releases several contaminants into the air, and this becomes excrescent if the generating unit is fed by multiple fuel sources (MFSs). Inclusion of this issue in operational tasks is a welcome perspective. This paper aims to develop a multi-objective model comprising total fuel cost and pollutant emission.

Design/methodology/approach

The cost-effective and environmentally responsive power system operations in the presence of MFSs can be recognised as a multi-objective constrained optimisation problem with conflicting operational objectives. The complexity of the problem requires a suitable optimisation tool. Ant lion algorithm (ALA), the most recent nature-inspired algorithm, was used as the main optimisation tool because of its salient characteristics. The fuzzy decision-making mechanism has been integrated to determine the best compromised solution in the multi-objective framework.

Findings

This paper is the first to propose a more precise and practical operational model for studying a multi-fuel power dispatch scenario considering valve-point effects and CO2 emission. The modern meta-heuristic algorithm ALA is applied for the first time to address the economic operation of thermal power systems with multiple fuel options.

Practical implications

Power companies aim to make profit by abiding by the norms of the regulatory board. To achieve economic benefits, the power system must be analysed using an accurate operational model. The proposed model integrates total fuel cost, valve-point loadings and CO2 emission, which are prevailing power system operational objectives. The economic advantages of the operational model can be observed through economic deviation indices, and the performed analysis validates that the developed model corresponds to the actual power operation.

Originality/value

The realistic operational model is proposed by considering total fuel and pollutant emission, and the ALA is applied for the first time to address the proposed multi-objective problem. To validate the effectiveness of ALA, it is implemented in standard test systems with varying generating units (10-100) and the IEEE 30 bus system, and various kinds of power system operations are performed. Moreover, the comparison and performance analysis confirm that the current proposal is found enhanced in terms of solution quality.

Details

International Journal of Energy Sector Management, vol. 12 no. 1
Type: Research Article
ISSN: 1750-6220

Keywords

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Article
Publication date: 5 June 2017

Janagaraman Radha, Srikrishna Subramanian, Sivarajan Ganesan and Manoharan Abirami

This study aims to minimize operating cost, adhere to pollution norms and maintain reserve and voltage levels subject to various operational concerns, including non linear…

Abstract

Purpose

This study aims to minimize operating cost, adhere to pollution norms and maintain reserve and voltage levels subject to various operational concerns, including non linear characteristics of generators and fuel limitation issues, which are useful for the current power system applications.

Design/methodology/approach

Improved control settings are required while considering multiple conflicting operational objectives that necessitate using the modern bio-inspired algorithm ant lion optimizer (ALO) as the main optimization tool. Fuzzy decision-making mechanism is incorporated in ALO to extract the best compromise solution (BCS) among set of non-dominated solutions.

Findings

The BCS records of IEEE-30 bus and JEAS-118 bus systems are updated in this work. Numerical simulation results comparison and comprehensive performance analysis justify the applicability of the intended algorithm to solve multi-objective dynamic optimal power flow (DOPF) problem over the state-of-art methods.

Originality/value

Optimal control settings are obtained for IEEE-30 and JEAS-118 bus systems with the objectives of minimizing fuel cost and emission in dynamic environment considering take-or-pay fuel contract issue. The fuzzy supported ALO (FSALO) is applied first time to solve the DOPF problem.

Details

International Journal of Energy Sector Management, vol. 11 no. 2
Type: Research Article
ISSN: 1750-6220

Keywords

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Article
Publication date: 24 February 2021

Syed Asif Raza and Srikrishna Madhumohan Govindaluri

The purpose of this paper is to conduct a structured literature review using advanced bibliometric tools to understand the existing knowledge base, understand the trends…

Abstract

Purpose

The purpose of this paper is to conduct a structured literature review using advanced bibliometric tools to understand the existing knowledge base, understand the trends in omni-channel (OC) research and identify emerging research topics.

Design/methodology/approach

More than 500 articles selected through a keyword combination search from reputed databases of peer-reviewed academic sources from period 2009–19 are analyzed for the purposes of this study. The study first presents an exploratory analysis to determine influential authors, sources and regions, among other key aspects. Second, several network analyses including co-citation and dynamic co-citation network analyses are conducted to identify themes. These allow identifying research clusters and emerging research topics algorithmically. Both centrality and modularity-based clustering are employed. A content analysis of the most influential groups within OC literature for each cluster is included.

Findings

The findings of this paper make unique contributions by using advanced tools from network analysis along with the standard bibliometric analysis tools to explore the current status of OC research, identify existing themes and the guidance for potential areas of future research interest in OC.

Practical implications

This research provides a comprehensive view of the range of topics of importance that have been discussed in the literature of OC management. These research trends can serve as a quick guide to researchers and practitioners to improve decision making and also develop strategies.

Originality/value

The paper employs advanced tools for the first time to review the literature of OC retailing. The sophisticated tools include co-citation and dynamic co-citation network analysis.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

Keywords

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Article
Publication date: 26 June 2020

Wogene Tesfaye and Daniel Kitaw

Plastics waste management is a critical agenda for the global community. Recycling is the most important strategy option for recovering plastics wastes. This study aims to…

Abstract

Purpose

Plastics waste management is a critical agenda for the global community. Recycling is the most important strategy option for recovering plastics wastes. This study aims to review reverse logistics (RL) implementation practices and conceptualizing it to the plastic recycling system.

Design/methodology/approach

The paper is organized after evaluating the studies related to plastics waste recycling and analyzing the available frameworks to use RL as a strategic tool.

Findings

The paper has investigated that previous research on RL implementation focused on a few stages of RL activities and did not include the most important issues. However, for successful RL implementation, taking into account the whole stage and including the most important factors is very important. To elaborate on this finding a new conceptual framework is developed.

Research limitations/implications

The paper is fully based on literature review and international reports. The developed framework is required for further empirical validation in the plastics sector.

Practical implications

The paper has considered the important issues and the applications of those factors that can improve plastics recycling performances.

Social implications

This study can enhance the active involvement of main actors (plastics producers, users, municipal and recyclers) in the plastics recycling system.

Originality/value

This paper deliberates on how RL can be conceptualized and implemented in plastics recycling systems in considering the most important factors for plastics recycling.

Details

Social Responsibility Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1747-1117

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Article
Publication date: 16 July 2019

Naresh Kumar and Ritu Rani

The purpose of this paper is to examine the regional variations in maternal and child health all over India. The Maternal and Child Health Index (MCHI) is constructed to…

Abstract

Purpose

The purpose of this paper is to examine the regional variations in maternal and child health all over India. The Maternal and Child Health Index (MCHI) is constructed to find the extent of variations in maternal and child health status for the States and Union Territories (UTs) of India.

Design/methodology/approach

The Wroclow taxonomic technique was used to construct the MCHI for the States and UTs of India. In all, 29 variables were selected for the construction of MCHI. All the variables were taken from National Family Health Survey-4 (NFHS, 2017) of India.

Findings

The findings suggest that there are wide variations in MCHI all over India. In India, Kerala topped in terms of MCHI followed by Jammu & Kashmir. Nagaland is on the bottom of the list followed by Bihar and Uttar Pradesh. High values of MCHI (> 0.4) are posing a serious concern for all States/UTs in India.

Social implications

The existence of inequality in MCHI for India is truly posing a serious inquiry regarding the healthcare system in India. The outcome of the study demands that time has come to adopt a human rights approach to the right to health in India. The findings of the study could be used by the health policy makers in India.

Originality/value

This study shows the existence of wide variations in the quality of maternal and child health all over India. The quantification of the quality of maternal and child health is needed to improve the health of the population in India. Little research has been done on the issue of quality of maternal and child health in India. This study is an important contribution to the current knowledge of quality of maternal and child health in India.

Details

International Journal of Human Rights in Healthcare, vol. 12 no. 4
Type: Research Article
ISSN: 2056-4902

Keywords

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