Cakar ayam shaping machine

Cakar ayam (Figure 7.1) is one of the Malay traditional cookies that are made from sliced sweet potatoes deep-fried in the coconut candy. In current practice of moulding the cookies, the fried sweet potatoes are molded using traditional manual tools, which are inefficient and less productive for the mass production purposes. “Kuih cakar ayam” associated with the meaning of the idiom means less messy handwriting has a somewhat negative connotation .This cookies may just seem less attractive in shape but still likeable . In fact, this cookie is considered a popular snack even outside the holiday season. The choice of the name of this cookie is more to shape actually resembles former chicken scratches made by the paw the ground while foraging. The value of wisdom, beauty and creativity of the Malays is clearly evident through the Malay cookie. Although it is attacked by the invention of modern cakes that look far more interesting, these cakes will be able to survive a long time until now

Power Quality Enhancement in Hybrid Photovoltaic-Battery System based on three–Level Inverter associated with DC bus Voltage Control

This modest paper presents a study on the energy quality produced by a hybrid system consisting of a Photovoltaic (PV) power source connected to a battery. A three-level inverter was used in the system studied for the purpose of improving the quality of energy injected into the grid and decreasing the Total Harmonic Distortion (THD). A Maximum Power Point Tracking (MPPT) algorithm based on a Fuzzy Logic Controller (FLC) is used for the purpose of ensuring optimal production of photovoltaic energy. In addition, another FLC controller is used to ensure DC bus stabilization. The considered system was implemented in the Matlab /SimPowerSystems environment. The results show the effectiveness of the proposed inverter at three levels in improving the quality of energy injected from the system into the grid.Peer reviewedFinal Published versio

Performance Analysis Of Hybrid Ai-Based Technique For Maximum Power Point Tracking In Solar Energy System Applications

Demand is increasing for a system based on renewable energy sources that can be employed to both fulfill rising electricity needs and mitigate climate change. Solar energy is the most prominent renewable energy option. However, only 30%-40% of the solar irradiance or sunlight intensity is converted into electrical energy by the solar panel system, which is low compared to other sources. This is because the solar power system\u27s output curve for power versus voltage has just one Global Maximum Power Point (GMPP) and several local Maximum Power Points (MPPs). For a long time, substantial research in Artificial Intelligence (AI) has been undertaken to build algorithms that can track the MPP more efficiently to acquire the most output from a Photovoltaic (PV) panel system because traditional Maximum Power Point Tracking (MPPT) techniques such as Incremental Conductance (INC) and Perturb and Observe (P&Q) are unable to track the GMPP under varying weather conditions. Literature (K. Y. Yap et al., 2020) has shown that most AIbased MPPT algorithms have a faster convergence time, reduced steady-state oscillation, and higher efficiency but need a lot of processing and are expensive to implement. However, hybrid MPPT has been shown to have a good performance-to-complexity ratio. It incorporates the benefits of traditional and AI-based MPPT methodologies but choosing the appropriate hybrid MPPT techniques is still a challenge since each has advantages and disadvantages. In this research work, we proposed a suitable hybrid AI-based MPPT technique that exhibited the right balance between performance and complexity when utilizing AI in MPPT for solar power system optimization. To achieve this, we looked at the basic concept of maximum power point tracking and compared some AI-based MPPT algorithms for GMPP estimation. After evaluating and comparing these approaches, the most practical and effective ones were chosen, modeled, and simulated in MATLAB Simulink to demonstrate the method\u27s correctness and dependability in estimating GMPP under various solar irradiation and PV cell temperature values. The AI-based MPPT techniques evaluated include Particle Swarm Optimization (PSO) trained Adaptive Neural Fuzzy Inference System (ANFIS) and PSO trained Neural Network (NN) MPPT. We compared these methods with Genetic Algorithm (GA)-trained ANFIS method. Simulation results demonstrated that the investigated technique could track the GMPP of the PV system and has a faster convergence time and more excellent stability. Lastly, we investigated the suitability of Buck, Boost, and Buck-Boost converter topologies for hybrid AI-based MPPT in solar energy systems under varying solar irradiance and temperature conditions. The simulation results provided valuable insights into the efficiency and performance of the different converter topologies in solar energy systems employing hybrid AI-based MPPT techniques. The Boost converter was identified as the optimal topology based on the results, surpassing the Buck and Buck-Boost converters in terms of efficiency and performance. Keywords—Maximum Power Point Tracking (MPPT), Genetic Algorithm, Adaptive Neural-Fuzzy Interference System (ANFIS), Particle Swarm Optimization (PSO

Survey on Photo-Voltaic Powered Interleaved Converter System

Renewable energy is the best solution to meet the growing demand for energy in the country. The solar energy is considered as the most promising energy by the researchers due to its abundant availability, eco-friendly nature, long lasting nature, wide range of application and above all it is a maintenance free system. The energy absorbed by the earth can satisfy 15000 times of today’s total energy demand and its hundred times more than that our conventional energy like coal and other fossil fuels. Though, there are overwhelming advantages in solar energy, It has few drawbacks as well such as its low conversion ratio, inconsistent supply of energy due to variation in the sun light, less efficiency due to ripples in the converter, time dependent and, above all, high capitation cost. These aforementioned flaws have been addressed by the researchers in order to extract maximum energy and attain hundred percentage benefits of this heavenly resource. So, this chapter presents a comprehensive investigation based on photo voltaic (PV) system requirements with the following constraints such as system efficiency, system gain, dynamic response, switching losses are investigated. The overview exhibits and identifies the requirements of a best PV power generation system

High efficient interleaved boost converter with novel switch adaptive control in photovoltaic application

PhD ThesisEnergy conversion efficiency is an important factor for the long-term feasibility of photovoltaic systems. Significant work has been carried out into improving the effectiveness of solar arrays in recent years. In addition, there has been substantial research into novel power converter topologies for maximum energy efficiency. However, in photovoltaic applications, even the most promising power converter topologies do not necessarily guarantee optimum performance under all operating conditions. For instance, the efficiency of the power conversion stage may be excellent during periods of high irradiance, but significantly lower in poorer light conditions. This work attempts to address this problem, by seeking to achieve higher energy conversion efficiency under sub-optimal conditions. In this thesis, stand-alone photovoltaic systems using DC-DC boost converters are considered. An interleaved boost converter with novel switch adaptive control scheme is designed to maximise system efficiency over a wider range of real-time operating atmospheric conditions and with different load conditions without incurring significant additional cost

Design and implementation of a dual-input single-output photovoltaic converter

In many solar inverters, a dc/dc converter is mainly located between the solar arrays and the inverter. This study presents an enhanced maximum power point tracking (MPPT) algorithm for photovoltaic (PV) systems that drives solar array voltages to track a reference value and decreases fluctuations and oscillations in PV voltage. Different from the previously presented methods, a novel MPPT method is proposed that ensures tracking accuracy by considering output voltage in addition to input voltage and currents. The proposed method detects dI/dV variations, compares the output voltage with the desired reference to shift operation mode and refreshes step size. The digital filtering, enhanced PI, and perturb-and-observe (P&O) tracking features of the proposed MPPT method make it robust to mitigate source fluctuations and sensitivity to partial shading based oscillations. In order to validate the success of the proposed method, a test rig has been installed with dual boost converters. The performance improvements have been verified by both simulation and experimental results that are compared to InCon and P&O MPPT methods. It is also confirmed by experimental results that the proposed MPPT method provides robust control capability in terms of tracking the reference voltage and rejecting the effects of various shading situations on solar arrays

Boost converter fed high performance BLDC drive for solar PV array powered air cooling system

This paper proposes the utilization of a DC-DC boost converter as a mediator between a Solar Photovoltaic (SPV) array and the Voltage Source Inverters (VSI) in an SPV array powered air cooling system to attain maximum efficiency. The boost converter, over the various common DC-DC converters, offers many advantages in SPV based applications. Further, two Brushless DC (BLDC) motors are employed in the proposed air cooling system: one to run the centrifugal water pump and the other to run a fan-blower. Employing a BLDC motor is found to be the best option because of its top efficiency, supreme reliability and better performance over a wide range of speeds. The air cooling system is developed and simulated using the MATLAB/Simulink environment considering the steady state variation in the solar irradiance. Further, the efficiency of BLDC drive system is compared with a conventional Permanent Magnet DC (PMDC) motor drive system and from the simulated results it is found that the proposed system performs better

Evolution engine technology in exhaust gas recirculation for heavy-duty diesel engine

In this present year, engineers have been researching and inventing to get the optimum of less emission in every vehicle for a better environmental friendly. Diesel engines are known reusing of the exhaust gas in order to reduce the exhaust emissions such as NOx that contribute high factors in the pollution. In this paper, we have conducted a study that EGR instalment in the vehicle can be good as it helps to prevent highly amount of toxic gas formation, which NOx level can be lowered. But applying the EGR it can lead to more cooling and more space which will affect in terms of the costing. Throughout the research, fuelling in the engine affects the EGR producing less emission. Other than that, it contributes to the less of performance efficiency when vehicle load is less

Roach Infestation Optimization MPPT Algorithm of PV Systems for Adaptive to Fast-Changing Irradiation and Partial Shading Conditions

Of all the renewable energy sources, solar photovoltaic (PV) power is considered to be a popular source owing to several advantages such as its free availability, absence of rotating parts, integration to building such as roof tops and less maintenance cost. The nonlinear current–voltage (I–V) characteristics and power generated from a PV array primarily depends on solar insolation/irradiation and panel temperature. The power output depends on the accuracy with which the nonlinear power–voltage (P–V) characteristics curve is traced by the maximum power point tracking (MPPT) controller. A DC-DC converter is commonly used in PV systems as an interface between the PV panel and the load, allowing the follow-up of the maximum power point (MPP). The objective of an efficient MPPT controller is to meet the following characteristics such as accuracy, robustness and faster tracking speed under partial shading conditions (PSCs) and climatic variations. To realize these objectives, numerous traditional techniques to artificial intelligence and bio-inspired techniques/algorithms have been recommended. Each technique has its own advantage and disadvantage. In view of that, in this thesis, a bio-inspired roach infestation optimization (RIO) algorithm is proposed to extract the maximum power from the PV system (PVS). In addition, the mathematical formulations and operation of the boost converter is investigated. To validate the effectiveness of the proposed RIO MPPT algorithm, MATLAB/Simulink simulations are carried out under varying environmental conditions, for example step changes in solar irradiance, and partial shading of the PV array. The obtained results are examined and compared with the particle swam optimization (PSO). The results demonstrated that the RIO MPPT performs remarkably in tracking with high accuracy as PSO based MPPT. Last but not the least, I am very grateful to the Arctic Centre for Sustainable Energy (ARC), UiT The Arctic University of Norway, Norway for providing an environment to d

Design and Implementation of Control Techniques of Power Electronic Interfaces for Photovoltaic Power Systems

The aim of this thesis is to scrutinize and develop four state-of-the-art power electronics converter control techniques utilized in various photovoltaic (PV) power conversion schemes accounting for maximum power extraction and efficiency. First, Cascade Proportional and Integral (PI) Controller-Based Robust Model Reference Adaptive Control (MRAC) of a DC-DC boost converter has been designed and investigated. Non-minimum phase behaviour of the boost converter due to right half plane zero constitutes a challenge and its non-linear dynamics complicate the control process while operating in continuous conduction mode (CCM). The proposed control scheme efficiently resolved complications and challenges by using features of cascade PI control loop in combination with properties of MRAC. The accuracy of the proposed control system’s ability to track the desired signals and regulate the plant process variables in the most beneficial and optimised way without delay and overshoot is verified. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed two times with considerably improved disturbance rejection. Second, (P)roportional Gain (R)esonant and Gain Scheduled (P)roportional (PR-P) Controller has been designed and investigated. The aim of this controller is to create a variable perturbation size real-time adaptive perturb and observe (P&O) maximum power point tracking (MPPT) algorithm. The proposed control scheme resolved the drawbacks of conventional P&O MPPT method associated with the use of constant perturbation size that leads to a poor transient response and high continuous steady-state oscillations. The prime objective of using the PR-P controller is to utilize inherited properties of the signal produced by the controller’s resonant path and integrate it to update best estimated perturbation that represents the working principle of extremum seeking control (ESC) to use in a P&O algorithm that characterizes the overall system learning-based real time adaptive (RTA). Additionally, utilization of internal dynamics of the PR-P controller overcome the challenges namely, complexity, computational burden, implantation cost and slow tracking performance in association with commonly used soft computing intelligent systems and adaptive control strategies. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed five times with reduced steady-state oscillations around maximum power point (MPP) and more than 99% energy extracting efficiency.Third, the interleaved buck converter based photovoltaic (PV) emulator current control has been investigated. A proportional-resonant-proportional (PR-P) controller is designed to resolve the drawbacks of conventional PI controllers in terms of phase management which means balancing currents evenly between active phases to avoid thermally stressing and provide optimal ripple cancellation in the presence of parameter uncertainties. The proposed controller shows superior performance in terms of 10 times faster-converging transient response, zero steady-state error with significant reduction in current ripple. Equal load sharing that constitutes the primary concern in multi-phase converters has been achieved with the proposed controller. Implementing of robust control theory involving comprehensive time and frequency domain analysis reveals 13% improvement in the robust stability margin and 12-degree bigger phase toleration with the PR-P controller. Fourth, a symmetrical pole placement Method-based Unity Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller has been designed and investigated. The proposed PR-P controller resolved the issues associated with the use of the PI controller which are tracking repeating control input signal with zero steady-state and mitigating the 3rd order harmonic component injected into the grid for single-phase PV systems. Additionally, the PR-P controller has overcome the drawbacks of frequency detuning in the grid and increase in the magnitude of odd number harmonics in the system that constitute the common concerns in the implementation of conventional PR controller. Moreover, the unprecedented design process based on changing notch filter dynamics with symmetrical pole placement around resonant frequency overcomes the limitations that are essentially complexity and dependency on the precisely modelled system. The verification and validation process of the proposed control schemes has been conducted using MATLAB/Simulink and implementing MATLAB/Simulink/State flow on dSPACE Real-time-interface (RTI) 1007 processor, DS2004 High-Speed A/D and CP4002 Timing and Digital I/O boards