New triple-action controller for inverter power quality improvement

An increased electricity demand and dynamic load changes are creating a huge burden on the modern utility grid, thereby affecting supply reliability and quality. It is thus crucial for modern power system researchers to focus on these aspects to reduce grid outages. High-quality power is always desired to run various businesses smoothly, but power-electronic-converter-based renewable energy integrated into the utility grid is the major source of power quality issues. Many solutions are constantly being invented, yet a continuous effort and new optimized solutions are encouraged to address these issues by adhering to various global standards (IEC, IEEE, EN, etc.). This paper therefore proposes a concept of establishing a renewable-energy-based microgrid cluster by integrating various buildings located in an urban community. This enhances power supply reliability by managing the available energy in the cluster without depending on the utility grid. Further, a “fuzzy space vector pulse width modulation” (FSV-PWM) technique is proposed to control the inverter, which improves the power supply quality. This work uniquely optimized the dq reference currents using fuzzy logic theory, which were used to plot the space vectors with effective sector selection to generate accurate PWM signals for inverter control. The modeling/simulation of the microgrid cluster involving the FSV-PWM-based inverter was carried out using MATLAB/Simulink®. The efficacy of the proposed FSV-PWM over the conventional ST-PWM was verified by plotting voltage, frequency, real/reactive power, and harmonic distortion characteristics. Various power quality indices were calculated under different disturbance conditions. The results showed that the use of the proposed FSV-PWM-based inverter adhered to all the key standard requirements, while the conventional system failed in most of the indices.

Section: Introductionmentioning

confidence: 99%

Power Quality Improvement in Renewable-Energy-Based Microgrid Clusters Using Fuzzy Space Vector PWM Controlled Inverter

Rao¹,

Kumar

Pradeep

et al. 2022

“…In addition, they proposed and developed an improved triple-action controller (TAC) design. To produce seamless sinusoidal voltage, the suggested TAC consists of a conventional PR, SHC, and a feed-forward current controller [17]. Moreover, in [18], the authors introduced a revolutionary "smart branch" that compensates for diverse power quality disruptions.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Hysteresis Current Controller for Power Quality Enhancement in Renewable Energy Integrated Clusters

Kumar

Rao²,

Padma

et al. 2022

Steady increase in electricity consumption, fossil fuel depletion, higher erection times of conventional plants, etc., are encouraging the use of more and more onsite renewable energy. However, due to the dynamic changes in environmental factors as well as the customer load, renewable energy generation is facing issues with reliability and quality of the supply. As a solution to all these factors, renewable energy integrated cluster microgrids are being formed globally in urban communities. However, their effectiveness in generating quality power depends on the power electronic converters that are used as an integral part of the microgrids. Thus, this paper proposes the “Fuzzy Hysteresis Current Controller (FHCC)-based Inverter” for improving the power quality in renewable energy integrated cluster microgrids that are operated either in grid-connected or autonomous mode. Here, the inverter is controlled through a fuzzy logic-based hysteresis current control loop, thereby achieving superior performance. System modelling and simulations are done using MATLAB/Simulink®. The performance analysis of the proposed and conventional inverter configurations is done by computing various power quality indices, namely voltage characteristics (swell, sag, and imbalance), frequency characteristics (deviations), and total harmonic distortion. The results reveal that the proposed FHCC-based inverter achieves a better quality of power than the traditional ST-PWM-based multilevel inverter in terms of IEEE/IEC/EN global standards for renewable energy integrated cluster microgrids application.

“…An upgraded custom power device, namely a distributed power condition controller, was adapted to a multi-microgrid system with greater penetration of various distributed generators on the island and interconnected modes to increase the power quality [15]. An optimal control mechanism for a multi-level converter [16,17] was developed, and this control scheme alleviated the glitches caused by the conventional approaches. Authors also reported a solution to resolve the fast dynamic concerns and fixed-frequency operation using a whole, robust voltage control scheme and angle droop approaches [18].…”

Section: Introductionmentioning

confidence: 99%

Harmonics Minimisation in Non-Linear Grid System Using an Intelligent Hysteresis Current Controller Operated from a Solar Powered ZETA Converter

Pattathurani

Dash²,

Dwibedi

et al. 2022

Due to the non-linear load characteristics in the domestic three-phase grid system, the quality of power transmission is a challenge for researchers. In this paper, the harmonics injected in a three-phase grid system due to the non-linear loads and a solution for harmonics minimisation using the hysteresis current controller (HCC) is presented. The proposed work consists of switched dc loads such as personal computers, SMPS, etc., connected to the three-phase grid system through the rectifier unit. These loads connected with other AC loads inject harmonics in the power lines. The total harmonic distortion (THD) at the power line is therefore increased. A ZETA embedded three-phase inverter using an artificial neural network-based HCC (ANN-HCC) is used to minimise the voltage and the current THDs. To ease the power consumption, a solar photovoltaic system (SPV) is used to power the ZETA embedded three-phase inverter. The output of the SPV is regulated using the ZETA dc/dc converter. However, the hysteresis bands (Uupper and Ulower) are selected using the ANN with respect to the actual value compared with the calculated current error. The vector shifts to the next based on the previous vector applied, and thereby the process repeats following the same pattern. The back propagation (BP)-based neural network is trained using the currents’ non-linear and differential functions to generate the current error. The neural structure ends when the value hits the hysteresis band. Simultaneously, the PWM control waveform is tracked by the neural network output. The proposed system is mathematically modelled using MATLAB/Simulink. An experimental setup of a similar prototype model is designed. The voltage and the current harmonics are measured using a Yokogawa CW240 power quality meter and the results are discussed.