Rahul Kumar Agarwal

Abstract: This paper proposes the use of a least mean fourth (LMF)-based algorithm for single-stage three-phase grid-integrated solar photovoltaic (SPV) system. It consists of an SPV array, voltage source converter (VSC), three-phase grid, and linear/nonlinear loads. This system has an SPV array coupled with a VSC to provide three-phase active power and also acts as a static compensator for the reactive power compensation. It also conforms to an IEEE-519 standard on harmonics by improving the quality of power in the three-phase distribution network. Therefore, this system serves to provide harmonics alleviation, load balancing, power factor correction and regulating the terminal voltage at the point of common coupling. In order to increase the efficiency and maximum power to be extracted from the SPV array at varying environmental conditions, a single-stage system is used along with perturb and observe method of maximum power point tracking (MPPT) integrated with the LMF-based control technique. The proposed system is modeled and simulated using MATLAB/Simulink with available simpower system toolbox and the behaviour of the system under different loads and environmental conditions are verified experimentally on a developed system in the laboratory.

Abstract: This paper proposes an application of a least mean-square (LMS)-based neural network (NN) structure for the power quality improvement of a three-phase power distribution network under abnormal conditions. It uses a single-layer neuron structure for the control in a distribution static compensator (DSTATCOM) to attenuate the harmonics such as noise, bias, notches, dc offset, and distortion, injected in the grid current due to connection of several nonlinear loads. This admittance LMS-based NN structure has a simple architecture which reduces the computational complexity and burden which makes it easy to implement. A DSTATCOM is a custom power device which performs various functionalities such as harmonics attenuation, reactive power compensation, load balancing, zero voltage regulation, and power factor correction. Other main contribution of this paper involves operation of the system under abnormal conditions of distribution network which means noise and distortion in voltage and imbalance in three-phase voltages at the point of interconnection. For substantiating and demonstrating the performance of proposed control approach, simulations are carried on MATLAB/Simulink software and corresponding experimental tests are conducted on a developed prototype in the laboratory.

Abstract: The main intent of this study is to integrate a solar photovoltaic (SPV) generating system to three-phase grid and to provide a clean and uninterrupted flow of power at abnormal and peak load conditions. To establish such an interface, a reliable, secure and high-performance control algorithm is the necessity. This study presents a three-phase single-stage grid tied SPV energy conversion system (SPECS) using phase locked loop-less (PLL-less) fast character of triangle function (CTF) control technique. This system configures an SPV array, voltage-source inverter (VSI), ripple filters and three-phase grid with connected linear and non-linear loads. Apart from supplying active power to the grid and connected loads, SPECS also provides functionalities of an active shunt filter such as reactive power compensation, harmonics attenuation, power factor correction, load balancing and zero voltage regulation. This system uses a single-stage perturb & observe approach for maximum power point tracking. Moreover, the VSI control is based on PLL-less fast CTF technique which enhances the functioning of SPECS. The presented system is modelled, designed and simulated on MATLAB/Simulink platform as well as its functioning is validated experimentally on a developed laboratory prototype.

Abstract: This paper proposes a three-phase single-stage grid integrated solar photovoltaic distributed static compensator (SPV-DSTATCOM) system using a leaky least mean fourth (LLMF) control algorithm. The prime contributions of this paper include: 1) the SPV generating system, which fulfills the active power requirement of connected loads and supplies the excess power to the grid; 2) the voltage-source converter (VSC) acts as a dc–ac inverter and DSTATCOM, which provides reactive power compensation, harmonics filtering, load balancing, power factor correction, zero voltage regulation, and mitigates several other power quality issues; 3) even when the SPV power is unavailable, the VSC operates as a DSTATCOM, which enhances the utilization factor of devices; and 4) the LLMF-based control approach for fundamental component extraction from load currents for good harmonics compensation as well as to keep the overall system stable and to achieve rapid response at changing conditions. The proposed system is modeled and simulated using MATLAB/Simulink as well as its performance is verified experimentally on a developed prototype.

Abstract: In this paper, an adaptable dual-mode single-stage solar photovoltaic (PV) tied to a three-phase voltage-weak distribution network is proposed using a multilayer perceptron (MLP) neural network control structure. The system operates in dual modes: First, it performs as a PV supplying active power with distributed static compensator (DSTATCOM) capability thereby improving power quality simultaneously; and second, it works as a DSTATCOM alone during unavailability of the solar PV generation. The system is adaptable as it continues to operate satisfactorily for voltage-weak distribution grid that has frequent voltage fluctuations and flickers. A single-stage converter based system is utilized here, which incorporates an incremental conductance based approach for maximum power point tracking and MLP neural network structure for the extraction of fundamental components of load currents. The main advantages of MLP are its simplicity, generic nature, and ease of implementation. The system and the control algorithm are validated by using MATLAB-based simulation results and test results are achieved on a laboratory prototype.

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Abstract: A new control approach of integrating a solar photovoltaic (PV) with a battery storage is presented to a single-phase grid for residential and electric vehicle application. The main purpose of the proposed work is to feed a continuous power to the grid, thereby enhancing the viability of the battery energy storage support connected to the system. The charging and discharging of the battery achieve power leveling and load leveling along with increased reliability of the system. The multifunctional voltage-source converter acts as an active power filter and performs the harmonics mitigation along with reactive power compensation. In the proposed system, a unique control is developed for resynchronization of the grid during reconnection of the grid after the mitigation of a failure. The overall control of the system is adaptable under various practically occurring situations such as disconnection of the PV array, the battery, and the grid from the system. The detailed design and control of the proposed system are presented. The validity of the proposed system is performed through a laboratory prototype developed for a power rating of 2.2 kW connected to the utility grid. The performance of the system is found satisfactory under various disturbance, and the recorded results have been demonstrated.

Abstract: This paper deals with the design and performance analysis of a three-phase single stage solar photovoltaic integrated unified power quality conditioner (PV-UPQC). The PV-UPQC consists of a shunt and series-connected voltage compensators connected back-to-back with common dc-link. The shunt compensator performs the dual function of extracting power from PV array apart from compensating for load current harmonics. An improved synchronous reference frame control based on moving average filter is used for extraction of load active current component for improved performance of the PV-UPQC. The series compensator compensates for the grid side power quality problems such as grid voltage sags/swells. The compensator injects voltage in-phase/out of phase with point of common coupling (PCC) voltage during sag and swell conditions, respectively. The proposed system combines both the benefits of clean energy generation along with improving power quality. The steady state and dynamic performance of the system are evaluated by simulating in MATLAB-Simulink under a nonlinear load. The system performance is then verified using a scaled down laboratory prototype under a number of disturbances such as load unbalancing, PCC voltage sags/swells, and irradiation variation.

Abstract: This paper deals with a new version of perturb and observe tracking algorithm for maximum power extraction from the solar photovoltaic panel, which has self-predictive and decision taking ability. The working principle of self-predictive perturb and observe (SPP&O) algorithm is based on three consecutive operating points on the power-voltage characteristic. Out of three points, first two points very smartly detects the dynamic condition, as well as in normal condition, quickly searches the maximum power point (MPP) region. Moreover, by using a circular analogy, all points decide the optimal operating position for next iteration, which is responsible for quick MPP tracking as well as improved dynamic performance. Here, in every new iteration, the step-size is reduced by 90% from the previous step-size, which provides an oscillation-free steady-state performance. The effectiveness of the proposed technique is validated by MATLAB simulation as well as tested on hardware prototype. Moreover, comparison between SPP&O algorithm and state of art methods is made. Its satisfactory dynamic and steady-state behaviors with low algorithm complexity as well as the low computational burden of the SPP&O algorithm show the superiority over state of the art methods.

Abstract: Renewable energy (RE) sources when integrated to utility network to form hybrid power system pose challenges in terms of stability and power quality. A method based on Stockwell's transform (S-transform) is presented in this paper for power quality (PQ) assessment and detection of islanding, outage and grid synchronization of renewable energy sources. Voltage signals are decomposed using multi-resolution analysis (MRA) of S-transform and features extracted are realized to assess the power quality disturbances associated with various events. Operational events are detected with the help of features extracted from the S-transform based decomposition of negative sequence component of voltage. A power quality index is proposed to rank the various operational events based on power quality. Proposed algorithm has been tested successfully on IEEE-13 bus test system with necessary modifications to integrate wind and solar PV generators to form the hybrid power system. Simulation results are validated in real time environment with the help of real time digital simulation (RTDS) system.