Impedance estimation of single-phase diode bridge rectifier using kalman filter

Today, the majority of electronic loads are non-linear. Electronic ballasts for discharge lamps, audio equipment, and personal computers are examples of non-linear loads. DC voltage is used to power these electronic loads. It is important to convert AC voltage to DC voltage since the power distribution system operates on AC voltage. In low-power applications, single phase rectifiers convert AC electricity to DC voltage. The aspects that influence nonlinear loads and allow a power quality study include power factor, displacement factor, and harmonic distortion. The study of these phenomena has grown in popularity as this type of load has become more prevalent in residential and commercial environments. Nonlinear load modeling is a critical tool for resolving this issue. Then specialized research into the modeling of these loads is required. As a result, this study create a Kalman filter model by using MATLAB Simulink for estimating the RLC parameters of a single-phase diode bridge rectifier. The system design was carried out using the MATLAB Simulink platform, with the appropriate RLC parameters taken from relevant literature studies. This study discovered that the amount of process noise in a system indicates the system's performance. The simulation is finished when all of the required conditions are met, which means the accuracy attained is at least 90%. When compared to the Analytical technique, simulation results show that the proposed method is more accurate. It specifies that with a modest value of process noise, the precision of equivalent capacitance, resistance, and inductance becomes more precise. For Section 1, the percentage of accuracy improved by 0.26%, 0.6%, and 9.84%, respectively, for resistance, inductance, and capacitance. Besides, for Section 2, the percentage of accuracy increased by 0.16%, 0.1%, and 1.3% for resistance, inductance, and capacitance respectively. Finally, the Kalman Filter can be used to calculate the R, L, and C parameter values for a single-phase diode bridge rectifier

Power management and control stategies of renewable energy resources for micro-grid application

Microgrids (MGs) have become an increasingly familiar power sector feature in recent years and goes through the increase of renewable energies penetration. MG is defined as a group of interconnected loads and multiple distributed generators that is able to operate in grid-connected or islanding mode. Recent reports claim dramatic growth in projects planned for hundreds of GWs worldwide. Notably, following to many natural disasters, the concept of MG and its perceived benefits shifted beyond economic and environmental goals towards resilience. Consequently, MGs have begun to find a natural place in the regulatory and policy arena. Remote areas, facilities with low-quality local energy resources and critical infrastructure are all potential need the MGs solution. However, MGs have some disadvantages as the complexity of control and integration to keep the power quality to acceptable standards. The energy storage system requires more space and maintenance. Finally, protection is one of the important challenges facing the implementation of MGs. The present doctoral research is based on the philosophy of MGs for optimal integration and power management in an effective and efficient way to provide a sustainable and reliable power supply to consumers while reducing the overall cost. This work proposes a novel control strategies and design approaches of micro-grids for remote areas and grid connected system in which both the reliability of continuous power supply and power quality issues are treated. Moreover, this thesis also introduces the concept of Net Zero Energy House in which the system is designed in such a way that the house produces as much energy as it consumes over the year. Many controls algorithms have been investigated in order to find the best way to reduce the sensors’ number and the degree of control complexity while keeping better power quality as well as the system reliability. The developed concept is successfully validated through simulation as well as extensive experimental investigations. Particular attention is paid to the optimal integration of MGs based on the climate data of Central African States