Dynamic modeling of a stand-alone pem fuel cell connected to adjustable speed drive

Fuel cell has a good potential as a stand-alone generation system and as energy supplied to Adjustable Speed Drive (ASD) model. This is because of its low operation temperature (70ºC until 90ºC) and also it has a good dynamic response. In this project, Proton Exchange Membrane (PEM) fuel cell is used as energy source. Dynamic modeling of a stand-alone PEM fuel cell which connected to several types of ASD system had been modeled by using Matlab/Simulink software. The PEM fuel system has several important sections, namely, fuel cell controller, fuel cell and power conditioning unit. Integrated and proportional controllers are used to control the fuel cell or the hydrogen flow rate that enters the PEM fuel cell. Simulation results show that fuel cell output power can fulfill the load demand in a short duration. Single-phase ASD and three-phase ASD are reviewed as loads in this project and their individual harmonics are investigated based on simulation results. Results also show that ASD generates harmonics to the line voltage and current. A method to reduce harmonics distortion in a network of ASD is proposed in this project. As a result, by combining different types of ASD as network, significant reduction on total harmonics distortion can be obtained

Automatic Generation Control System: The Impact of Battery Energy Storage in Multi Area Network

Renewable energy sources (RES) are currently experiencing significant expansion, and the integration of these sources into power systems necessitates more complex auxiliary facilities. Battery energy storage systems (BESS) have been widely recognized in recent literature as an effective means of enhancing control capabilities. This study focuses on the implementation of an Automatic Generation Control (AGC) system with the integration of BESS in a multi-area network. Maintaining system frequency, especially during peak loads, poses challenges for AGC systems. The objective of this study is to investigate the utilization of BESS to enhance AGC for frequency control in power system networks. Additionally, the effectiveness of BESS in improving frequency control in multi-area networks is demonstrated through several case studies. The AGC and BESS simulations were conducted using MATLAB Simulink to evaluate the proposed frequency control method's effectiveness. &nbsp

Automatic Generation Control System: The Impact of Battery Energy Storage in Multi Area Network

Renewable energy sources (RES) are currently experiencing significant expansion, and the integration of these sources into power systems necessitates more complex auxiliary facilities. Battery energy storage systems (BESS) have been widely recognized in recent literature as an effective means of enhancing control capabilities. This study focuses on the implementation of an Automatic Generation Control (AGC) system with the integration of BESS in a multi-area network. Maintaining system frequency, especially during peak loads, poses challenges for AGC systems. The objective of this study is to investigate the utilization of BESS to enhance AGC for frequency control in power system networks. Additionally, the effectiveness of BESS in improving frequency control in multi-area networks is demonstrated through several case studies. The AGC and BESS simulations were conducted using MATLAB Simulink to evaluate the proposed frequency control method's effectiveness. &nbsp

Development of an intelligent and remote IoT-based monitoring system for power quality application

Power quality is an extremely critical when it comes to electricity consumer in all aspect of practices. A small variation in the voltage results in the shutdown of sensitive equipment and a brief shut down leads to additional production or operational cost. In order to solve the power quality issue, it is important to understand the characteristic of the power quality disturbance signal. A decent and efficient monitoring devise is essential to capture and analyze the disturbance signal. This project proposed a development of a remote intelligent IoT-based power quality monitoring device that able to monitor, capture, characterize, and diagnose the power quality event occured in the smart grid system or any electric distribution system based on Space Vector Machine Platform. It is expected that the proposed project will assist engineers to understand the power quality root caused effectively and able to react fast to mitigate the issue

Power Forecasting from Solar Panels Using Artificial Neural Network in UTHM Parit Raja

This paper presents a step-by-step procedure for the simulation of photovoltaic modules with numerical values, using MALTAB/Simulink software. The proposed model is developed based on the mathematical model of PV module, which based on PV solar cell employing one-diode equivalent circuit. The output current and power characteristics curves highly depend on some climatic factors such as radiation and temperature, are obtained by simulation of the selected module. The collected data are used in developing Artificial Neural Network (ANN) model. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) are the techniques used to forecast the outputs of the PV. Various types of activation function will be applied such as Linear, Logistic Sigmoid, Hyperbolic Tangent Sigmoid and Gaussian. The simulation results show that the Logistic Sigmoid is the best technique which produce minimal root mean square error for the system

Performance comparison of PEMFC hydrogen reformer with different controllers

The renewable energy technology has become very popular due to major constraint in the existing electrical system such as high electricity demand, increased in fuel prices and concern of environmental pollution. The aims of this project are to develop a complete Proton Exchange Membrane Fuel Cell (PEMFC) model with hydrogen reformer by using MATLAB/ Simulink with three different controllers and comparison between the three controllers will be discussed. This project presents the development of methods to solve the problem of PEMFC output voltage by using different controllers which are Proportional Integral (PI), Proportional Integral Derivatives (PID) and Proportional Integral Fuzzy (PI-Fuzzy) controllers. The Ziegler Nicholas tuning method is used to tune PI and PID gains in a Simulink model. It helps the system to achieve a balance between performance and robustness for both controllers. The Mamdani type was used to develop the fuzzy controller in Simulink model. The transient performances that will be discussed are rise time, settling time, maximum overshoot, and percentage of overshoot. The results show that the proposed PI-Fuzzy is better than the conventionally used PI and PID controllers

Artificial intelligence based direct torque control of induction motor drive system

In this project, a three-phase Induction motor (IM) under the direct torque control (DTC) technique is studied. IM is known for its simple engines and its self-starter feature but it always suffered a setback in the area of torque and speed control as it is a highly coupled nonlinear plant and proves to be most complex and expensive speed drive. The application of direct torque control (DTC) is beneficial for fast torque reaction in IM but provide high torque and ripples due to harmonic effects. Thus, the speed control of induction motor is important to achieve maximum torque and efficiency. The aim of this study is to improve tracking performance of the induction motor drive using artificial intelligence control system. A method for controlling induction motor drive is presented with Proportional-Integral (PI) controller and Artificial Neural Networks (ANNs) for performance comparison. MATLAB/SIMULINK software is used to develop a three-phase 2 pole-cage type induction motor model. Also the performances of the two controllers have been verified in terms of its speed and torque responses. The ANN is trained so that the speed of the drive tracks the reference speed. This study proved that the performance and dynamics of the induction motor are enhanced using ANN controller as compared with PI controller

Stability Assessment On Inertial Response For Automatic Generation Control System

Integration of more renewable energy sources (RES) undoubtedly bring more impact into power system. The distributed generation of RES in grid-connected knowingly will interfere frequency system’s stability due to decoupling to at point of common coupling. Inertia plays main role for bringing up frequency regulation at very early stage of frequency responses. Thus, to include RES such as solar photovoltaic (PV) and wind turbine (WT) could be a good idea but ideally PV has no inertia while WT only partially inertia. Therefore, the objective of this paper is to do an assessment on frequency stability specifically on inertial response with regard to unit commitment e.g. synchronous generator and RES participation. However, to know certainly the inertia constant (H) for each generator with respect to its rating ultimately difficult as it can varies depending to several factors i.e. unit type and manufacturer. Hence, an equation is proposed and yielded to facilitate for H determination of synchronous generator. The proposed equation is tested with other IEEE systems for its accuracyness. The estimated values are then simulated in various scenarios and cases i.e. increment of inertia, splitting of unit commitment and RES participation toward inertial response. MATLAB Simulink software is used to simulate and analyze the end results. Finally, the famous Kundur’s 4 Machine Two-Area Test system is used to verify the effectiveness for entire findings

A hybrid solar-battery-supercapacitor based camping lamp

Lighting is an essential and insufficient lighting will make us difficult to see things clearly and performing almost all our daily activities. There will be a problem for activities like camping or hiking because there is no electricity and a camping lamp usually used to provide light. Previous product of camping lamp use only rechargeable battery as the supply and it is unconvincing to use the camping lamp for a long time as it only stays on for a few days. A camping lamp that can be charged by exposing to the sunlight can be the solution to overcome this problem. This study is enhancing the features of camping lamp using solar energy as the source to recharge the energy storage devices. There are two types of energy storage devices namely rechargeable battery and supercapacitor that function as the backup charging system. The supercapacitor harvest solar energy from the camping lamp itself so that the product can be recharge when there is no sustainable sunlight. The product will give a huge benefit to anyone who love to do outdoor activity

Modeling Of A Planar Sofc Performance Using Artificial Nueral Network

The Planar Solid Oxide Fuel Cell (PSOFC) is one of the renewable energy technologies that is important as the main source for distributed generation and can play a significant role in the conventional electrical power generation. PSOFC stack modeling is performed in order to provide a platform for the optimal design of fuel cell systems. It is explained by the structure and operating principle of the PSOFC for the modeling purposes. PSOFC model can be developed using Artificial Neural Network approach. The data required to train the neural net-work model is generated by simulating the existing PSOFC model in the MATLAB/ Simulink software. The Radial Basis Function (RBF) and Multilayer Perceptron (MLP) neural networks are the most useful techniques in many applications and will be applied in developing the PSOFC model. A detailed analysis is presented on the best ANN network that gives the greatest results on the performances of the PSOFC. The simulation results show that Multilayer Perceptron (MLP) gives the best outcomes of the PSOFC performance based on the smallest errors and good regression analysis