Electrical and electronic devices, when exposed to one or more power quality problems, are prone to failure. This study aims to enhance the quality of power in three-phase four-wire distribution grid using fuel cell integrated unified power quality conditioner (FCI-UPQC). The proposed FCI-UPQC has a four-leg converter on the shunt side and three-leg converter on the series side. A combination of a synchronous reference frame and instantaneous reactive power theories is utilised to generate reference signals of the FCI-UPQC. Also, this study proposes an adaptive neuro-fuzzy inference system (ANFIS) controller to maintain the DC-link voltage in the FCI-UPQC. The ANFIS controller is designed like a Sugeno fuzzy architecture and trained offline using data from the proportional-integral controller. The obtained results proved that the proposed FCI-UPQC compensated power quality problems such as voltage sag, swell, harmonics, neutral current, source current imbalance in the three-phase four-wire distribution grid. The presence of fuel cell in this work makes more effectiveness of the proposed system by providing real power support during supply interruption on the grid side. load current I a *, I b *, I c * converter current V L2a , V L2b , V L2c load voltage
In the current scenario, integration of renewables, growth of non-linear industrial and commercial loads results in various power quality issues. Among commercial utilities connected to the grid, hospital-operated loads include sensitive, linear, non-linear, and unbalanced loads. These loads are diverse as well as prioritized, which also causes major power quality issues in the local distribution system. Due to its widespread divergence, it leads to harmonic injection and reactive power imbalance. Distribution Static Compensator (DSTATCOM) is proposed as a solution for harmonic mitigation, load balancing, reactive power imbalances, and neutral current compensation. The present work utilizes Interval Type-2 Fuzzy Logic Controller (IT2FLC) with Recursive Least Square (RLS) filter for generating switching pulses for IGBT switches in the DSTATCOM to improve power quality in the Local Distribution Grid. The proposed approach also shows superior performance over Type 1 fuzzy logic controller and Conventional PI controller in mitigating harmonics. For effective realization, the proposed system is simulated using MATLAB software.INDEX TERMS Local distribution grid, DSTATCOM, Interval type 2 fuzzy logic controller, power quality, and Recursive least square filter.
Abstract:The power quality enhancement is very mandatory with the newer generation load equipments, whose performance is very sensitive to power quality disturbances especially with voltage sag, Harmonics and Interruption. The power electronic based power conditioning devices can be the effective solution to enhance the quality of the power supplied to the power distribution system. The series connected Dynamic Voltage Restorer (DVR) is one of the effective solution to mitigate power quality problems in the distribution system. In this paper, the Artificial Neural Network (ANN) controlled DVR is designed and the performance of the rectifier load connected system is investigated with conventional Proportional-Integral (PI) controller. The LevenbergMarquardt (LV) Back propagation algorithm is used to implement the control scheme of the Voltage Source Inverter (VSI). The ANN is trained offline using data from PI controller. In addition to the compensation of voltage sag and harmonics, the DVR is also used to protect a linear load from various disturbances in the source voltage. Three different types of faults with two level of voltage sag are analyzed and the performance of DVR with these disturbances is modeled using MATLAB/SIMULINK. The comprehensive result of the PI and ANN controllers are also presented.
In this literature, a new automated control strategy has been developed to manage the power supply from the wind power generation system to the load. The main objective of this research work is to develop a fuzzy logic-based pitch angle control and to develop a static transfer switch to make power balance between the wind power generation system and the loads. The power management control system is a progression of logic expressions, designed based on generating power and load power requirement. The outcome of this work targets at an improved power production, active and reactive power compensation and ensures system load constraints. To validate the proposed control strategy, a detailed simulation study is carried out on a 9-MW wind farm simulation simulated in MATLAB/Simulink environment.
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