Capacitors placement by NSGA-II in distribution systems with non-linear loads

Azevedo, Manoel Socorro Santos; Abril, Ignacio Pérez; Leite, Jandecy Cabral; Medeiros, Adelson Bezerra de

doi:10.1016/j.ijepes.2016.03.025

Cited by 24 publications

(12 citation statements)

References 27 publications

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“…where Q b j,h,s and P b j,h,s show the reactive and active power through the j th branch in the h th hour and s th season, respectively. In (21), the b is an indication of the word 'branch'. The S trans i,h,s denotes the power of the transformer connected to the i th bus in h th hour and s th season.…”

Section: B Constraintsmentioning

confidence: 99%

“…Sensitivity analysis and Gravitational Search Algorithm (GSA) are utilized to find the optimal fixed capacitor location for reducing the loss and operational cost of the distribution network in [20]. Optimal location, size, and the number of fixed and switchable capacitors are discussed in [21] by executing the nondominated sorting GA II (NSGA-II). Some other heuristic methods used for optimal placement and sizing of capacitor banks are bacterial foraging solution based on fuzzy logic decision [22], integrated evolutionary algorithms [23], cuckoo search algorithm [24], fuzzy theory method [25], modified monkey search optimization technique [26], and harmony search approach [27].…”

Section: Introductionmentioning

confidence: 99%

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A Two-Loop Hybrid Method for Optimal Placement and Scheduling of Switched Capacitors in Distribution Networks

et al. 2020

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This paper presents a method to find the optimal size and place of the switched capacitors using a hybrid optimization algorithm. The objective function includes the active and reactive power of power plants, the capital and maintenance costs of capacitor banks, and the cost of active and reactive power losses in distribution lines and transformers. The impact of the load model on the optimal sizing and placement of switched capacitors is studied using three different scenarios: In the first scenario, all loads are voltage-dependent; in the second scenario, only a portion of loads are voltage-dependent; in the third scenario, all loads are voltage-independent. The proposed hybrid algorithm incorporates an outer and two inner optimization layers. The outer layer is executed by a genetic algorithm (GA), while the inner layer is performed by a GA, an exchange market algorithm (EMA), or a particle swarm optimization (PSO). The performance of GA-GA, GA-EMA, and GA-PSO hybrid schemes are compared on an IEEE 33-bus test system. Moreover, IEEE 33-bus and 69-bus networks are used to verify the effectiveness of proposed hybrid scheme against the gravitational search algorithm (GSA), a combination of PSO and GSA (PSOGSA), cuckoo search algorithm (CSA), teaching learning-based optimization (TLBO), and flower pollination algorithm (FPA). The results highlight the advantage of the proposed hybrid optimization scheme over the other optimization algorithms. INDEX TERMS Exchange market algorithm (EMA), genetic algorithm (GA), particle swarm optimization (PSO), radial distribution system (RDS), switched capacitors.

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Section: B Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Two-Loop Hybrid Method for Optimal Placement and Scheduling of Switched Capacitors in Distribution Networks

et al. 2020

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“…However, in [11], the authors solve the OCP task by considering multi‐objective non‐dominated sorting genetic algorithm (NSGA) approach considering load uncertainty. In [12], NSGA‐II method is used by the authors for solving OCP problem considering non‐linear loads.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous optimal allocation and sizing of DGs and capacitors in radial distribution systems using SPEA2 considering load uncertainty

Biswal

Shankar

2019

IET Generation, Transmission & Distribution

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“…Even so, the installation of additional shun capacitors for partial reactive compensation will increase the nonlinearity of the system components and therefore make harmonic considerations inevitable. In [23], power quality constraints such as total harmonic distortion (THD) and maximum voltage deviation were taken into account to determine the optimum placement, size, and number of both switched and fixed capacitors. The multi-objective formulation was solved by the Non-Dominated Sorting Genetic Algorithm (NSGA-II), and tested on a practical example.…”

Section: Introductionmentioning

confidence: 99%

Optimal Capacitor Placement in Wind Farms by Considering Harmonics Using Discrete Lightning Search Algorithm

Sirjani¹

2017

Sustainability

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Currently, many wind farms exist throughout the world and, in some cases, supply a significant portion of energy to networks. However, numerous uncertainties remain with respect to the amount of energy generated by wind turbines and other sophisticated operational aspects, such as voltage and reactive power management, which requires further development and consideration. To fix the problem of poor reactive power compensation in wind farms, optimal capacitor placement has been proposed in existing wind farms as a simple and relatively inexpensive method. However, the use of induction generators, transformers, and additional capacitors represent potential problems for the harmonics of a system and therefore must be taken into account at wind farms. The optimal location and size of capacitors at buses of an 80-MW wind farm were determined according to modelled wind speed, system equivalent circuits, and harmonics in order to minimize energy losses, optimize reactive power and reduce the management costs. The discrete version of the lightning search algorithm (DLSA) is a powerful and flexible nature-inspired optimization technique that was developed and implemented herein for optimal capacitor placement in wind farms. The obtained results are compared with the results of the genetic algorithm (GA) and the discrete harmony search algorithm (DHSA).

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Capacitors placement by NSGA-II in distribution systems with non-linear loads

Cited by 24 publications

References 27 publications

A Two-Loop Hybrid Method for Optimal Placement and Scheduling of Switched Capacitors in Distribution Networks

A Two-Loop Hybrid Method for Optimal Placement and Scheduling of Switched Capacitors in Distribution Networks

Simultaneous optimal allocation and sizing of DGs and capacitors in radial distribution systems using SPEA2 considering load uncertainty

Optimal Capacitor Placement in Wind Farms by Considering Harmonics Using Discrete Lightning Search Algorithm

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