Analyzing the Performance Measures of Multi-Objective Water Cycle Algorithm for Multi-Objective Linear Fractional Programming Problem

Veeramani, Chinnadurai; Sharanya, S.

doi:10.1109/iccons.2018.8662923

Cited by 4 publications

(3 citation statements)

References 20 publications

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“…After the evaporation process occurs, the raining process creates new streams in different positions. The positions of the streams that are lately creating are determined by [11], [37], [46] ( ).…”

Section: Water Cycle Algorithm (Wca)mentioning

confidence: 99%

Capacitor Allocation Using Multiobjective Water Cycle Algorithm and Fuzzy Logic

El-Saeed

Abdel-Gwaad

Farahat

2022

ELEKTRON ELEKTROTECH

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Radial distribution systems are susceptible to a lack of voltage profile and increase system losses, particularly at the distant ends of the distribution feeder. This manuscript proposes an approach to solve the optimal capacitor placement problem in radial distribution networks to minimize system losses, improve the voltage profile of all buses, promote total voltage stability, and improve net savings. The optimal capacitor placement problem is solved in two stages. Firstly, normalized loss sensitivity factor and voltage magnitude are used as inputs to build fuzzy expert rules to arrange the most candidate buses for capacitor placement. Secondly, a multiobjective water cycle algorithm is applied to determine the optimal sizes and locations of capacitors within the predefined search space using fuzzy expert rules. The multiobjective function is formulated with operational constraints considering fixed and switched capacitors. To validate the effectiveness of this methodology, it is demonstrated on IEEE 33 and IEEE 94-bus radial distribution networks. Clearly, the findings show the improvement in the voltage profile and static voltage stability, the significant reduction in system losses, as well as the enhancement in overall savings. Furthermore, a comprehensive evaluation is also carried out by comparing the numerical results with other methods such as interior point algorithm, a combination fuzzy real coded genetic algorithm method, water cycle algorithm for IEEE 33-bus system and artificial bee colony algorithm for IEEE 94-bus system which prove the viability and effectiveness of the proposed methodology.

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Section: Water Cycle Algorithm (Wca)mentioning

confidence: 99%

Capacitor Allocation Using Multiobjective Water Cycle Algorithm and Fuzzy Logic

El-Saeed

Abdel-Gwaad

Farahat

2022

ELEKTRON ELEKTROTECH

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“…Once the group of paretoresults is available, the efficiency of the proposed algorithm is determined using this pareto archives. Performance metrics [13] are evaluated by MOWCA's overall performance by using the pareto archive. The performance metrics are Generational distance metric (GD), The Reverse Generational Distance (RGD), Metric of spacing (S), Delta Metric ($\Delta$).…”

Section: Multi-objective Water Cycle Algorithmmentioning

confidence: 99%

Sustainable Supplier Selection Based on Multi-Objective Water Cycle Algorithm

Sharanya¹,

Veeramani²

2021

Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, In

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Evolutionary algorithms (EA) are well-suited for optimization problems with numerous objectives. The Multi-Objective Water Cycle Algorithm (MOWCA) is a comparatively recent approach for determining the Pareto-optimal set for multi-objective optimization problems, and the Sustainable Supplier Selection Problem (SSS) plays an essential part in the optimization of SSS problem. The purpose of this study is to examine the Pareto solutions to the SSS issue using the Multi-Objective Water Cycle Algorithm. Initially, a Multi-Objective Water Cycle Algorithm (MOWCA) encouraged by the water cycle process is presented. The mathematical programming for the SSS problem is then developed. The stated Multi-Objective Programming Problem (MOPP) is then analyzed using the MOWCA to get the pareto solutions. The suggested approach's efficiency is examined utilizing performance metrics such as Generational Distance, Reverse Generational Distance, Delta Metric, and Metric of Spacing. Finally, a comparison study with various recent metaheuristic methods is performed.

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“…For example, the multi-objective NSGA-II algorithm called non-dominated sorting genetic algorithm (NSGA-III) is proposed by Jain and Deb [9], which is more efficient to solve problems with more than two objectives. The performance measures reveal that the multi-objective water cycle algorithm (MOWCA) is better than the other algorithms such as MODA, MOGA, MOEA-D. Further, MOWCA suggests a wide range of non-dominated solutions depending on the complexity of the optimization problem [10]. Bacterial Foraging Optimization Algorithm is used to identify the optimum capacity of the DG and DSTATCOM under different load is presented in [11].…”

Section: Introductionmentioning

confidence: 99%

Optimal Allocation of Hybrid Renewable Energy System by Multi-Objective Water Cycle Algorithm

et al. 2019

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This article offers a multi-objective framework for an optimal mix of different types of distributed energy resources (DERs) under different load models. Many renewable and non-renewable energy resources like photovoltaic system (PV), micro-turbine (MT), fuel cell (FC), and wind turbine system (WT) are incorporated in a grid-connected hybrid power system to supply energy demand. The main aim of this article is to maximize environmental, technical, and economic benefits by minimizing various objective functions such as the annual cost, power loss and greenhouse gas emission subject to different power system constraints and uncertainty of renewable energy sources. For each load model, optimum DER size and its corresponding location are calculated. To test the feasibility and validation of the multi-objective water cycle algorithm (MOWCA) is conducted on the IEEE-33 bus and IEEE-69 bus network. The concept of Pareto-optimality is applied to generate trilateral surface of non-dominant Pareto-optimal set followed by a fuzzy decision-making mechanism to obtain the final compromise solution. Multi-objective non-dominated sorting genetic (NSGA-III) algorithm is also implemented and the simulation results between two algorithms are compared with each other. The achieved simulation results evidence the better performance of MOWCA comparing with the NSGA-III algorithm and at different load models, the determined DER locations and size are always righteous for enhancement of the distribution power system performance parameters.

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Analyzing the Performance Measures of Multi-Objective Water Cycle Algorithm for Multi-Objective Linear Fractional Programming Problem

Cited by 4 publications

References 20 publications

Capacitor Allocation Using Multiobjective Water Cycle Algorithm and Fuzzy Logic

Capacitor Allocation Using Multiobjective Water Cycle Algorithm and Fuzzy Logic

Sustainable Supplier Selection Based on Multi-Objective Water Cycle Algorithm

Optimal Allocation of Hybrid Renewable Energy System by Multi-Objective Water Cycle Algorithm

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