Dynamic Simulation and Sensitivity Analysis of Steam Generation Solar Power Plant
Unified Power Quality Conditioner (UPQC) Research Study on Steady - State Power Flow
Photovoltaic Module Failure Detection using Machine Vision and Lazy Learning Technique
Design and Implementation of Wallace Tree Multiplier and Its Applications in FIR Filter
Review on Obstacle Detection in Solar Panel Cleaning Applications
Loss Distribution Methodology with a Sense Of Emission Dispatch
Low Power Optimization Technique Based Linear Feedback Shift Register
Leakage Power Reduction Using Multi Modal Driven Hierarchical Power Mode Switches
Validation of IOV chain using OVM Technique
Performance of Continuous and Discontinuous Space Vector Pwm Technique for Open End Winding Induction Motor Drive
Electronic Circuit Design for Electromagnetic Compliance through Problem-Based Learning
Trioinformatics: The Innovative and Novel Logic Notation That Defines, Explains, and Expresses the Rational Application of The Law of Trichotomy for Digital Instrumentation and Circuit Design
Design Of a Novel Gated 5T SRAM Cell with Low Power Dissipation in Active and Sleep Mode
A Two Stage Power Optimized Implantable Neural Amplifier Based on Cascoded Structures
An Efficient Hybrid PFSCL based Implementation of Asynchronous Pipeline
The Analog-to-Digital Converter (ADC), with its wide variety of applications in the electronics and communication domains, is the most crucial unit in every digital gadget. This paper discusses a smart way of converting an input analog signal to its digital counterpart using an innovative Adaptive-Delta modulator, followed by a signal reconstruction process to retrieve the original message. It has done the design in Matrix Laboratory (MATLAB) Simulink, and the hardware implementation is tested on the Xilinx Spartan-6 LX45 FPGA core. This design aims for high-accuracy conversion and optimization of hardware resources. The 1-bit adaptive model is superior in comparison to the traditional delta modulation (DM) scheme while tracking stiff analog input signals, producing a much lower mean square error. The implementation is quite simple as it uses the transmission of 1-bit digital data at a time. On the receiver side, digital-toanalog conversion (DAC) makes use of the same adaptive logic in reconstructing the original input signal. The designed prototype demonstrates its resistance to a wide range of input amplitude and frequency variations. The ADC-DAC design method in this paper is accurate, makes the best use of resources, and is easy to use.
Power electronic devices are essential to industrial processes, research, and development, it provides high efficiency, low cost, fast operation, and ideal dimensions. Power systems are significantly affected by harmonics, which are mainly generated by non-linear loads and power conversion technologies, including static converters, breakers, cycloconverters, battery charging systems, and heating components. Various filtering methods are available for harmonic suppression, among which the active power shunt filter is one of the most significant and effective. Harmonics are suppressed and system efficiency is improved using the Grey Wolf Optimization (GWO) approach. The design criteria are integrated into the cost function itself. Using various design criteria, the performance of a shunt active power filter is investigated. The design criteria used are Integral square error (ISE), Integral absolute error (IAE), Integral time absolute error (ITAE), and Integral time square error (ITSE) with ITAE having the best performance.
In this paper, the basic D flip-flop has been considered with TSPC (True Single-Phase Clock) logic. Here, the leakage power of 1031 pW fell to the power for the operation of the memory elements, which is a lot compared to other triggers. The challenge is to reduce the optimal power off to conserve idle power. To solve this problem, three different powersaving techniques were considered, such as Technique 1: sleeping transistors, Technique 2: sleepy stack, and Technique 3: sleepy keeper. In a comparative study, it was observed that Technique 1 is the most optimal method for delays (falling and rising) and off-state leakage power compared to the other methods considered. The off-state leakage power was 1.753 pW, which is 93.07% and 76.90% less than by Techniques 2 and 3, respectively.
Every digital signal processing application performs multiplication operations. The addition and shift operations are part of multiplication operation. Many ideas have been created for computing systems with different design goals in terms of power, area, and speed. Typical architecture of these applications include digital signal processor (DSP), fast Fourier transform (FFT), and Multiply and Accumulate (MAC) unit. This paper offers a new way to increase the speed of DSP systems. This method uses four 2x2 LUT (look-up table) multipliers to demonstrate it at a 4x4 multiplier. The proposed multiplier was created using the Xilinx Vivado software and programmed in the Verilog HDL language. In addition, the delay, area, and power consumption of the proposed multiplier design differ from those of conventional multipliers. The simulation results show that, compared to typical methods, the operation consumes less power, reaching only 3.751 W compared to the conventional multiplier of 4.804 W, and shows lower latency.
Growing demand for energy and concerns about environmental pollution has increased the use of renewable energy sources for electricity generation. Among all the renewable energy sources, solar energy is considered the most popular because of its huge benefits. This paper addresses two different problems with using photovoltaic (PV) systems in different applications. One of which is poor tracking performance, especially under partially shaded conditions (PSC). Therefore for global maximum power point (GMPP) tracking, a swarm intelligence-based maximum power point tracking (MPPT) method is used, which includes a particle swarm optimization (PSO) algorithm under the PSC, thereby improving the tracking efficiency of the PV system.