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By: Pavan Kumar Thatikonda and P.Lokender Reddy.
1.Lecturer, Department of Electrical and Electronics Engineering, Department of Technical Education,Telangana, India.
2. Assistant Professor, Department of Electrical Engineering, Osmania University,
Hyderabad, Telangana, India.
Providing consumers with high-quality power is the distribution operator’s primary goal. Distribution Static Compensator (DSTATCOM), Dynamic Voltage Restorer (DVR), and Unified Power Quality Conditioner (UPQC) are examples of power converter-based custom power devices (CPDs) that are well-known for enhancing the distribution system’s power quality. In order to lessen source-side supply power harmonics, DSTACOM is taken into consideration in this work. Any bespoke power device’s performance is heavily dependent on the control algorithm utilized for the gating pulse generating method and reference current estimate. In this study, a backpropagation-based control method based on artificial neural network (ANN) principles is used to recover the fundamental weighted values of active and reactive power components from distorted load currents. Even in the presence of nonlinear and unbalanced loading conditions, this intelligent control strategy allows for the precise separation of fundamental and harmonic components. The reference source currents needed for compensation are then estimated using the derived basic components. The basic weighted values of the active and reactive power components of load currents, which are necessary for estimating reference source currents, are extracted in the current work using a control technique based on back propagation. In order to produce switching pulses for the DSTATCOM , an adaptive hysteresis band current control technique is proposed. By using both combinations of techniques the DSTATCOM is developed and simulated under steady state condition. The performance of proposed back propagation control algorithm in a three-phase distribution system under non-linear loads is compared with conventional P-Q theory and superiority of the proposed algorithm is demonstrated under steady state condition.
Keywords: CPDs , DSTATCOM , Back propagation , P-Q theory , Artificial Neural Network (ANN)
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