Comparing NSGA-II and SPEA2 metaheuristics in solving the problem of optimal capacitor banks placement and sizing in distribution grids considering harmonic distortion restrictions

Onaka, J. H. D.; Lima, Athila Santos de; Kataoka, Vitor da Silva; Bezerra, Ubiratan Holanda; Tostes, Maria Emília de Lima; Vieira, Joao Paulo Abreu; Carvalho, Carminda M.

doi:10.1109/ichqp.2016.7783313

Cited by 7 publications

(2 citation statements)

References 4 publications

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“…In [27], NSGA II is also proposed to solve the proposed issue taking into account the total harmonic distortion constraint; however, there are some solutions on the Pareto front, which exceed the security boundaries in terms of voltage resonance. In [28], a comparison is made between NSGA II and Strength Pareto Evolutionary Algorithm (SPEA 2) to solve this issue taking into account the limitations of harmonic distortion. However, NSGA-II results in lower quality solutions, and SPEA 2 yields several solutions that violate voltage constraints.…”

Section: Introductionmentioning

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: Introductionmentioning

confidence: 99%

Capacitor Allocation Using Multiobjective Water Cycle Algorithm and Fuzzy Logic

El-Saeed

Abdel-Gwaad

Farahat

2022

ELEKTRON ELEKTROTECH

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“…There are three main versions: (1+1), (1+λ), and (µ+λ)-PAES[146], where (1+1)-ES means that during each iteration, one mutant is created from one parent, and their union is used in the selection.PESA2 Pareto Envelope based It uses a region based selection operator, instead of individual based ones, Selection Algorithm like NSGA-II. It requires only O(k • n) comparisons for every hyperbox [147].SPEA2Strength based SPEA-2 uses the strength based diversity operator, the calculation and Evolutionary Algorithm sorting time of which are more expensive than the case of NSGA-II; however, the diversity and convergence of the results can be better, which can be advantageous in the case of expensive optimization problems[148].IBEA Indicator BasedIt uses a flexible integration of preference information. Therefore, an arbitrary Evolutionary Algorithm performance indicator can be used for the search.…”

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confidence: 99%

Robust Design Optimization and Emerging Technologies for Electrical Machines: Challenges and Open Problems

et al. 2020

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The bio-inspired algorithms are novel, modern, and efficient tools for the design of electrical machines. However, from the mathematical point of view, these problems belong to the most general branch of non-linear optimization problems, where these tools cannot guarantee that a global minimum is found. The numerical cost and the accuracy of these algorithms depend on the initialization of their internal parameters, which may themselves be the subject of parameter tuning according to the application. In practice, these optimization problems are even more challenging, because engineers are looking for robust designs, which are not sensitive to the tolerances and the manufacturing uncertainties. These criteria further increase these computationally expensive problems due to the additional evaluations of the goal function. The goal of this paper is to give an overview of the widely used optimization techniques in electrical machinery and to summarize the challenges and open problems in the applications of the robust design optimization and the prospects in the case of the newly emerging technologies.

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