Capacitor Allocation Using Multiobjective Water Cycle Algorithm and Fuzzy Logic
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TL;DR: In this paper , a multi-objective water cycle algorithm is applied to determine the optimal sizes and locations of capacitors within the predefined search space using fuzzy expert rules, which is formulated with operational constraints considering fixed and switched capacitors.
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Abstract: 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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Citations
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References
A fuzzy-based approach for optimal allocation and sizing of capacitor banks
TL;DR: In this paper, a fuzzy set optimization approach for capacitance allocation in radial distribution system is proposed, where a membership function for voltage profile constraint has been used, and another membership function incorporating feeder section active power losses and total power losses constraints has been proposed.
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Capacitor placements for distribution systems with fuzzy algorithm
Hong-Chan Chin,Whei-Min Lin +1 more
- 22 Aug 1994
TL;DR: The whole problem is formulated as a fuzzy-set optimization problem to minimize the real power loss and the capacitor cost with voltage-limiting constraints.
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Multi-objective optimization of distribution network reconfiguration with capacitor and distributed generator placement
Russel John C. Gallano,Allan C. Nerves +1 more
- 01 Oct 2014
TL;DR: In this paper, the authors proposed a multi-objective optimal planning for real-time distribution system operations, based on the NSGA-II and fuzzy decision-making analysis to obtain the best system configuration with simultaneous installation of capacitors and distributed generators.
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Clone Attack Detection using Random Forest and Multi Objective Cuckoo Search Classification
P. Sherubha,P. Amudhavalli,S. P. Sasirekha +2 more
- 01 Apr 2019
TL;DR: An Adaptive random Forest based Multi-objective Cuckoo Search algorithm (RF-MOCS) is designed to identify the source of clone attack using KDD cup dataset and shows better trade off when compared to existing techniques like ANN, Naive bayes, SVM.
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Multi-objective optimal scheduling of a micro-grid consisted of renewable energies using multi-objective Ant Lion Optimizer
Kamran Hosseini,Samad Araghi,Mohamad Bagher Ahmadian,Vli Asadian +3 more
- 01 Dec 2017
TL;DR: The results have been compared with multi-objective Particle Swarm Optimization (MOPSO) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which shows that the use of the MOALO method in the presence of fuzzy technique attain the superior solutions on the operation cost and the emission of pollutant.
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