THD and Compensation Time Analysis of Three-Phase Shunt Active Power Filter Using Adaptive Blanket Body Cover Algorithm

THD and Compensation Time Analysis of Three-Phase Shunt Active Power Filter Using Adaptive Blanket Body Cover Algorithm

S. Khalid (CCSI Airport, India)
DOI: 10.4018/978-1-5225-3129-6.ch001
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Abstract

A novel Adaptive Blanket Body Cover Algorithm (ABBC) has been presented, which has been used for the optimization of conventional control scheme used in shunt active power filter. The effectiveness of the proposed algorithm has been proved by applying this in balanced, unbalanced and distorted supply conditions. The superiority of this algorithm over existing Genetic Algorithm results has been presented by analyzing the Total Harmonic Distortion and compensation time of both the algorithms. The simulation results using MATLAB model ratify that algorithm has optimized the control technique, which unmistakably prove the usefulness of the proposed algorithm in balanced, unbalanced and distorted supply system.
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Introduction

Non-linear loads cause the harmonics into the facility arrangement and these harmonics produce copiously of issues within the system. Once application of unbalanced and nonlinear loads will increase, supply gets distorted and unbalanced. These currents foul the provision point of the utility. Therefore, it is important to compensate unbalance, a harmonic and reactive component of the load currents. Whereas once supply is unbalanced and distorted, these problems worsen the system (Chen Donghua, 2005) (Saifullah & Bharti, 2014) (Saifullah Khalid, Application of AI techniques in implementing Shunt APF in Aircraft Supply System, 2013). By the appliance of shunt active power filter within the system can eliminate harmonic, reactive and unbalanced current still as improve the ability provide performance and so the steadiness of system. Today, the soft computing techniques are used wide for optimization of the system applied or in control system; algorithms (Guillermin, 1996) (Abdul Hasib, Hew Wooi, A, & F., 2002) (Jain, Agrawal, & Gupta, 2002) (Norman, Samsul, Mohd, Jasronita, & B., 2004) used for locating the optimized values of the controllers variables, optimization of active power filter using GA (Chiewchitboon, Tipsuwanpom, Soonthomphisaj, & Piyarat, 2003) (Kumar & Mahajan, 2009) (Ismail, Abdeldjebar, Abdelkrim, Mazari, & Rahli, 2008) (Wang, Zhang, XinheXu, & Jiang, 2006), power loss diminution using particle swarm optimization (Thangaraj, Thanga, Pant, Ajit, & Grosan, 2010), neural network ANN Control (P, K, & Eduardo, 2001) (Rajasekaran, 2005) (Rojas, 1996) (Zerikat & Chekroun, 2008) (Seong-Hwan, Tae-Sik, YooJi-Yoon, & Gwi-Tae, 2001) applied in each machinery and filter devices.

In this chapter, 2 totally different soft computing techniques i.e. adaptive Blanket Body cover algorithm and Genetic algorithm are applied for reduction of harmonics and others downside generated into the balanced, unbalanced and distorted system attributable to the nonlinear loads (Chen Donghua, 2005). The results obtained with each the algorithms are far better than those of typical strategies. ABBC algorithm has given the better results as compare to GA and traditional scheme. The effectiveness of the planned scheme has been evidenced by the simulation results mentioned. The result justified their effectiveness.

In this chapter, ABBC algorithm has been wont to search the optimum value of PI controller parameters. For the case of GA, the optimum value of filter inductor has been calculated. The controlling theme has been modeled on the idea of Constant instantaneous Power control Strategy.

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