scholarly journals Optimal placement of power factor correction capacitors in power systems using Teaching Learning Based Optimization

2017 ◽  
Vol 2 (2) ◽  
pp. 102-109
Author(s):  
Mouloud Bouaraki ◽  
Abdelmadjid RECIOUI
Keyword(s):  
Power Systems ◽  
Power Factor ◽  
Distribution System ◽  
Optimal Placement ◽  
Placement Problem ◽  
Capacitor Placement ◽  
Tlbo Algorithm ◽  
Optimal Capacitor Placement ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning

This paper presents a method to optimize the placement of capacitors in a distribution system to correct power factor and reduce losses and costs. The method uses the Teaching Learning Based Optimization (TLBO) method to solve the optimal capacitor placement problem. The combinatorial nature of the problem suggests the employment of a mixed binary and real valued TLBO algorithm. To validate the efficiency of the method, it was applied to various examples (different bus systems) and simulation results are discussed.

Optimal Placement of Power Factor Correction Capacitors Using Taguchi Optimization Method

2018 ◽  
pp. 777-812
Author(s):  
Abdelmadjid Recioui
Keyword(s):  
Power Factor ◽  
Distribution System ◽  
Distribution Systems ◽  
Power Factor Correction ◽  
Optimization Method ◽  
Optimal Placement ◽  
Placement Problem ◽  
Taguchi Optimization ◽  
Taguchi Optimization Method ◽  
Capacitor Placement

This chapter presents two methods to optimize the placement of capacitors in a distribution system and thus correcting power factor and reducing losses and costs. The first method uses ETAP software and its integrated algorithm of optimally placing power factor correction capacitors. The second uses the Taguchi Optimization method to solve the optimal capacitor placement problem in electric distribution systems. To test the efficiency of these methods, they were applied to various examples (different bus systems) and simulation results of the two methods are discussed.

scholarly journals Optimal capacitor placement in a distribution system using ETAP software

2019 ◽  
Vol 15 (2) ◽  
pp. 650
Author(s):  
M. J. Tahir ◽  
Badri. A. Bakar ◽  
M. Alam ◽  
M. S. Mazlihum
Keyword(s):  
Power System ◽  
Objective Function ◽  
Power Factor ◽  
Distribution System ◽  
Voltage Drop ◽  
Optimization Technique ◽  
Voltage Profile ◽  
Power Losses ◽  
Capacitor Placement ◽  
Optimal Capacitor Placement

<p>Mostly loads are inductive in nature in content of distribution side for any power system. Due to which system faces high power losses, voltage drop and reduction in system power factor. Capacitor placement is a common method to improve these factors. To maximize the reduction of inductive load impact, optimal capacitor placement (OCP) is necessary with the objective function of system cost minimization for voltage profile enhancement, power factor improvement and power losses minimization. As OCP is a non-linear problem with equality and inequality limitations, so the stated objective depends upon he placement and sizes of the capacitor banks. Electrical transient analyzer program (ETAP) software is used for the evaluation and modelling the power systems and genetic algorithm (GA) is used as an optimization technique for the minimization of the objective function. In this paper, to show the effectiveness of the technique IEEE 4bus,33bus system and NTDC 220KV real time grid system is modelled and evaluated in terms of objective minimization i-e maximum cost saving of the power system</p>

A Novel Method Based on Teaching-Learning-Based Optimization for Recloser Placement with Load Model Consideration in Distribution System

2016 ◽  
Vol 2 (1) ◽  
pp. 1 ◽  
Author(s):  
Sina Khajeh Ahmad Attari ◽  
Mohammad Bakhshipour ◽  
Mahmoudreza Shakarami ◽  
Farhad Namdari
Keyword(s):  
Distribution System ◽  
Network Reliability ◽  
Average Energy ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Load Model ◽  
Reliability Indices ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
System Average

<em>This paper proposed a novel technique based on teaching-learning-based optimization (TLBO) algorithm in order to find optimal placement of reclosers in the distribution networks which is applied to improve reliability. Reclosers use to eliminate transient faults, faults isolation, network management and enhance reliability to reduce customer outages. According to recloser role in network reliability, the cost for the installation and maintenance must be sustained by distribution companies. Therefore, selecting sufficient number and suitable location for reclosers are important issue. In this paper, the proposed objective function for optimal recloser number and placement has been formulated to improve three reliability indices which consists of three terms; i.e. System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI) and Average Energy Not Supplied (AENS). Besides the load model effectiveness has been considered to the simulation. To verify the efficiency of proposed method, it has been conducted to IEEE 69-bus radial distribution system. The obtained simulation results demonstrate the reliability improvement.</em>

scholarly journals Power Factor Compensation Using Teaching Learning Based Optimization and Monitoring System by Cloud Data Logger

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2172 ◽  
Author(s):  
Antonio Cano Ortega ◽  
Francisco Jose Sánchez Sutil ◽  
Jesús De la Casa Hernández
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Power Factor ◽  
Energy Savings ◽  
Data Logging ◽  
Data Logger ◽  
Cloud Data ◽  
Tlbo Algorithm ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning

The main objective of this paper is to compensate power factor using teaching learning based optimization (TLBO), determine the capacitor bank optimization (CBO) algorithm, and monitor a system in real-time using cloud data logging (CDL). Implemented Power Factor Compensation and Monitoring System (PFCMS) calculates the optimal capacitor combination to improve power factor of the installation by measure of voltage, current, and active power. CBO algorithm determines the best solution of capacitor values to install, by applying TLBO in different phases of the algorithm. Electrical variables acquired by the sensors and the variables calculated are stored in CDL using Google Sheets (GS) to monitor and analyse the installation by means of a TLBO algorithm implemented in PFCMS, that optimizes the compensation power factor of installation and determining which capacitors are connected in real time. Moreover, the optimization of the power factor in facilities means economic and energy savings, as well as the improvement of the quality of the operation of the installation.

Application of Teaching Learning-Based Optimization to the Optimal Placement of Phasor Measurement Units

2018 ◽  
pp. 407-438
Author(s):  
Abdelmadjid Recioui
Keyword(s):  
Phasor Measurement Units ◽  
Optimal Placement ◽  
Placement Problem ◽  
Electric Transmission ◽  
Phasor Measurement ◽  
Teaching Learning Based Optimization ◽  
Measurement Units ◽  
Pmu Placement ◽  
Teaching Learning ◽  
Full Network

In recent years, the placement of phasor measurement units (PMUs) in electric transmission systems has gained much attention. This chapter presents a binary teaching learning based optimization (BTLBO) algorithm for the optimal placement of phasor measurement units (PMUs). The optimal PMU placement problem is formulated to minimize the number of PMUs installation subject to full network observability at the power system buses. The efficiency of the proposed method is verified by the simulation results of IEEE14-bus, 30-bus, 57-bus-118 bus systems, respectively. The results show that the whole system can be observable with installing PMUs on less than 25% of system buses. For verification of our proposed method, the results are compared with some newly reported methods which show the method as a novel effective solution to obtain system measurements with the least number of phasor measurement units.

scholarly journals BTLBO Based SPMUs Placement Optimization for Fault Observation in Power Grid

2019 ◽  
Vol 4 (1) ◽  
pp. 18-24
Author(s):  
Abdelkader ZITOUNI ◽  
Hamid BENTARZI
Keyword(s):  
Research Work ◽  
Phasor Measurement Units ◽  
Optimal Placement ◽  
Placement Problem ◽  
Protection Scheme ◽  
Phasor Measurement ◽  
Teaching Learning Based Optimization ◽  
Measurement Units ◽  
Benchmark System ◽  
Teaching Learning

The placement of synchro-phasor measurement units in electric transmission systems has also gained much attention for enhancing the control as well as the protection scheme. In this research work, a binary teaching learning based optimization (BTLBO) algorithm for the optimal placement of synchro-phasor measurement units (SPMUs) is proposed. The optimal PMU placement problem is formulated to minimize the number of SPMUs installation subject to full network observability of the power system buses under fault conditions. The effectiveness of the proposed method is verified by the simulation of IEEE 14-bus benchmark system.

scholarly journals Ant Colony Optimization Technique in Optimal Capacitor Placement and Sizing Problem in Unbalanced Electrical Distribution System

2015 ◽  
Vol 785 ◽  
pp. 78-82 ◽  
Author(s):  
Mohd Ainor Yahya ◽  
Muhammad Murtadha Othman ◽  
Muhd Azri Abdul Razak ◽  
Zilaila Zakaria ◽  
Ismail Musirin ◽  
...  
Keyword(s):  
Ant Colony Optimization ◽  
Distribution System ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Ant Colony ◽  
Placement Problem ◽  
Electrical Distribution ◽  
Capacitor Placement ◽  
Optimal Capacitor Placement ◽  
Line Loss

The optimal capacitor placement problem involves determination on the type, number, location and size of capacitors to be placed in a distribution system for the attainment of energy efficiency. The main objectives of the capacitors placement and sizing are to reduce total line loss and energy consumption while satisfying the operational constraints. This paper presents the optimal capacitor placement and sizing problems solved by using the Ant Colony Optimization (ACO) technique with the integrated of circuitry unbalanced electrical distribution modeled in SIMULINK®MATLAB®software. The proposed technique was tested on a modified IEEE 13-bus unbalanced radial distribution system and the results revealed that the proposed technique has the merit in achieving optimal solution for addressing the problems.

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