Development of a dc-ac power conditioner for wind generator by using neural network

This project present of development single phase DC-AC converter for wind generator application. The mathematical model of the wind generator and Artificial Neural Network control for DC-AC converter is derived. The controller is designed to stabilize the output voltage of DC-AC converter. To verify the effectiveness of the proposal controller, both simulation and experimental are developed. The simulation and experimental result show that the amplitude of output voltage of the DC-AC converter can be controlled

A COMPARATIVE STUDY OF CONVENTIONAL PID AND FUZZY-PID FOR DC MOTOR SPEED CONTROL

The development of a Self Tuning Fuzzy proportional done to be compared with the conventional controller that (DC) motor. A simulation study is used to overcome the appearance of nonlinearities and uncertainties in the system with the proposed controller for the armature voltage controlled DC motors. Each parameter of the Fuzzy the fuzzy logic controller. The proportional, integral and derivative (KP,KI,KD) PID controller is being tuned by the controller. Different types of membership functions are evaluated in the fuzzy control and the best performance will be used in Fuzzy comparative analysis with the conventional PID. The FIS editor from MATLAB defines the membership function and the rules. Load disturbances from a variety of speed response and the step response are simulated from different scenarios

Design of Completion Detectors in Asynchronous Communication System

In digital design, there are two types of design, synchronous design and asynchronous design. In synchronous design, global clock is one of the main system that consume a lot of power. The power in synchronous design is consumed by clock even if there is no data processing take place. The asynchronous design that depends on data is clockless and as far as the power is concerned, asynchronous design does not consume much power compared with synchronous design and this really make asynchronus design the preffered choice for low power consumption. Besides having low power consumption, there are many advantages of aynchronous design compared with synchronous design. This paper proposed new dual rail completion detector (CD), 3-6 CD, 2-7 CD and 1-4 CD for on-chip communication that are used widely in an asynchronous communication system. The design of CD is based on the principle of sum adder. The circuit is designed by using Altera Quartus II CAD tools, synthesis and implementation process is executed to check the syntax error of the design. The design proved to be successful by using asynchronous on-chip communication in the simulatio

Designing a control system Based on SOC Estimation of BMS for PV-Solar System

One of the major challenges for battery energy stowage system is to design a supervisory controller which can yield high energy concentration, reduced self-discharge rate and prolong the battery lifetime. A regulatory PV-Battery Management System (BMS) based State of Charge (SOC) estimation is presented in this paper that optimally addresses the issues. The proposed control algorithm estimates SOC by Backpropagation Neural Network (BPNN) scheme and utilizes the Maximum Power Point Tracking (MPPT) scheme of the solar panels to take decision for charging, discharging or islanding mode of the Lead-Acid battery bank. A case study (SOC estimation) is demonstrated as well to depict the efficiency (Error 0.082%) of the proposed model using real time data. The numerical simulation structured through real-time information concedes that the projected control mechanism is robust and accomplishes several objectives of integrated PV-BMS for instance avoiding overcharging and deep discharging manner under different solar radiations

A battery integrated multiple input DC-DC boost converter

In this paper, the proposed single boost converter aims to harness more than one renewable energy (RE) input source and achieve a high voltage gain. The interleaved technique combined with voltage multiplier (VM) cells, reduced inductor current and attained high voltage transfer ratio. The boost converter possesses two unidirectional input ports and a bidirectional input port that is connected to a battery storage. The duty ratios of the power and interleaving switches are used to regulate the output voltage of the proposed converter. Three operation modes are identified, and steady state analyses of the converter are presented and discussed. The converter can store excess energy in the battery during periods of abundance and deliver power to the loads when the RE sources are low or unavailable. In addition, the output voltage is higher than that of the conventional boost converter. The converter delivered 278 V from 12 V and 24 V dual input sources. The converter operation is simulated and verified using MATLAB/Simulink

Design and Implementation of a Voltage Tracking with Artificial Neural Network Controller for a Double-input Buck-Boost Converter

This paper proposes an Artificial Neural Network (ANN) control voltage tracking scheme of a double-input buckboost DC-DC converter. In this topology, a back-propagation algorithm topology is implemented. The controller is developed to improve the performance of the double-input converter during transient and steady-state operations. The neural network controller design, which is developed against output voltage command tracking is proposed. The proposed concept has been investigated and validated experimentally on a laboratory prototype using DSP TMS320F28335real time digital controller to verify the dynamic response of the proposed controller. The experimental results confirm the validity of the proposed neural network control technique, which is a promising an efficient control topology that ensures doubleinput converter suitable for electric vehicle and renewable energy applications

An intelligent controlling method for battery lifetime increment using state of charge estimation in PV-battery hybrid system

In a photovoltaic (PV)-battery integrated system, the battery undergoes frequent charging and discharging cycles that reduces its operational life and affects its performance considerably. As such, an intelligent power control approach for a PV-battery standalone system is proposed in this paper to improve the reliability of the battery along its operational life. The proposed control strategy works in two regulatory modes: maximum power point tracking (MPPT) mode and battery management system (BMS) mode. The novel controller tracks and harvests the maximum available power from the solar cells under different atmospheric conditions via MPPT scheme. On the other hand, the state of charge (SOC) estimation technique is developed using backpropagation neural network (BPNN) algorithm under BMS mode to manage the operation of the battery storage during charging, discharging, and islanding approaches to prolong the battery lifetime. A case study is demonstrated to confirm the effectiveness of the proposed scheme which shows only 0.082% error for real-world applications. The study discloses that the projected BMS control strategy satisfies the battery-lifetime objective for off-grid PV-battery hybrid systems by avoiding the over-charging and deep-discharging disturbances significantly

An Intelligent Controlling Method for Battery Lifetime Increment Using State of Charge Estimation in PV-Battery Hybrid System

In a photovoltaic (PV)-battery integrated system, the battery undergoes frequent charging and discharging cycles that reduces its operational life and affects its performance considerably. As such, an intelligent power control approach for a PV-battery standalone system is proposed in this paper to improve the reliability of the battery along its operational life. The proposed control strategy works in two regulatory modes: maximum power point tracking (MPPT) mode and battery management system (BMS) mode. The novel controller tracks and harvests the maximum available power from the solar cells under different atmospheric conditions via MPPT scheme. On the other hand, the state of charge (SOC) estimation technique is developed using backpropagation neural network (BPNN) algorithm under BMS mode to manage the operation of the battery storage during charging, discharging, and islanding approaches to prolong the battery lifetime. A case study is demonstrated to confirm the effectiveness of the proposed scheme which shows only 0.082% error for real-world applications. The study discloses that the projected BMS control strategy satisfies the battery-lifetime objective for off-grid PV-battery hybrid systems by avoiding the over-charging and deep-discharging disturbances significantl

Effect of various configurations of swirl generator system on the hydrothermal performance of the flat-plate solar collector

This is a numerical study that analysis the heat extraction potential of solar collector tubes by assembling a couple of nozzles at the sealed end of the pipe to make swirl flow. Swirl flow intensifies the turbulence rate which augments heat transfer by ruffling the boundary layer. To this end, several decisive factors including nozzle angle (A: 30�, 45�, 60�, 90�), tube diameter (D: 20 mm, 50 mm), nozzle edge size (N: 6.25, 12.5, 25 mm (for D50) and N: 2.5, 5, 10 mm (for D20)), and mass flow rate (M: 0.1, 0.5, 1 kg/s (for D50) and M: 0.04, 0.2, 0.4 kg/s (for D20)) were considered. Results demonstrated that all of the models of class ’’A.../D20/N.../M...‘‘ had higher heat extraction potential but lower friction factor compared with ”A.../D50/N.../M...‘‘. Maximum and minimum values of heat flux extractions are 2113390 W/m2 and 59239 W/m2 that were obtained by ”A60/ D20/N2.5/M0.400 and ‘‘A30/D50/N25/M0.100. The created friction factor by class ”A.../D50/N .../M...‘‘ is higher than class ’’A.../D20/N.../M...”. The highest friction factor is 3.51 (’’A90/D 20/N2.5/M0.0400) and the lowest friction factor is 0.019 (‘‘A30/D20/N2.5/M0.200). Overall, for all cases, class ”A.../D50/N.../M...‘‘ bear the higher TPF compared with class ”A.../D50/N.../M ...‘‘ so that the greatest and lowest values of TPF are 5.09 and 0.49 achieved by ”A30/D50/N6.2 5/M100 and ‘‘A90/D20/N5/M0.400, respectively