A Robust Frequency Control Approach in PV-Diesel Hybrid Power System

Hybrid power generation system such as photovoltaic (PV)-diesel is one of the solution to reduce operational cost of the conventional diesel generation system. However, fluctuation of PV power due to uncertainty in weather condition may generate an unstable frequency of system. Further, it may reduce the reliability of the power utility, especially when the penetration of PV power is large. Therefore, a frequency control approach that involving PV with battery supervised by neural network algorithm is proposed to generate a stable system frequency. This method can reduce the frequency deviation without smoothing PV output power. The PV panels can generate maximum power according to the weather condition and frequency deviation. The PV output power and battery output power is controlled by neural network algorithm control. The neural network algorithm control is considering frequency deviation, average insolation and change of insolation as input. The proposed method is compared with similar system but without the existence of battery as energy storage system. The simulation results show that the proposed method can generate small frequency deviation compared with system without battery

Control Strategies of DC–DC Converter in Fuel Cell Electric Vehicle

There is a significant need to research and develop a compatible controller for the DC–DC converter used in fuel cells electric vehicles (EVs). Research has shown that fuel cells (FC) EVs have the potential of providing a far more promising performance in comparison to conventional combustion engine vehicles. This study aims to present a universal sliding mode control (SMC) technique to control the DC bus voltage under varying load conditions. Additionally, this research will utilize improved DC–DC converter topologies to boost the output voltage of the FCs. A DC–DC converter with a properly incorporated control scheme can be utilized to regulate the DC bus voltage–. A conventional linear controller, like a PID controller, is not suitable to be used as a controller to regulate the output voltage in the proposed application. This is due to the nonlinearity of the converter. Furthermore, this thesis will explore the use of a secondary power source which will be utilized during the start–up and transient condition of the FCEV. However, in this instance, a simple boost converter can be used as a reference to step–up the fuel cell output voltage. In terms of application, an FCEV requires stepping –up of the voltage through the use of a high power DC–DC converter or chopper. A control scheme must be developed to adjust the DC bus or load voltage to meet the vehicle requirements as well as to improve the overall efficiency of the FCEV. A simple SMC structure can be utilized to handle these issues and stabilize the output voltage of the DC–DC converter to maintain and establish a constant DC–link voltage during the load variations. To address the aforementioned issues, this thesis presents a sliding mode control technique to control the DC bus voltage under varying load conditions using improved DC–DC converter topologies to boost and stabilize the output voltage of the FCs

Implement Using KY Converter for Hybrid Renewable Energy Applications: Design, Analysis, and Implementation

This chapter mainly focuses on meeting the energy demand and methodologies of renewable energy. Nowadays, researchers are mainly focusing on renewable energy from the sun, wind, biomass, etc. due to energy crises and the lack of non-renewable energy. The potential for solar energy is high and this demand can best be met with hybrid systems, which can provide an uninterruptible power supply. This chapter looks at the performance metrics of hybrid energy as well as the methodologies and various control techniques connected with power management. The chapter also defines the photovoltaic (PV)-based, novel, dual KY boost converter. Dual PV sources act as input for the dual KY boost converter to generate as much energy as possible from the dual PV system, using the inverter module to produce single-phase alternating current output. A dual KY boost converter can provide higher maximum power, a faster response, and smaller voltage ripple. KY boost converters are designed to generate stable output values according to various conditions because of various control techniques and the maximum power point tracking control algorithm

Advanced Statistical Modeling, Forecasting, and Fault Detection in Renewable Energy Systems

Fault detection, control, and forecasting have a vital role in renewable energy systems (Photovoltaics (PV) and wind turbines (WTs)) to improve their productivity, ef?ciency, and safety, and to avoid expensive maintenance. For instance, the main crucial and challenging issue in solar and wind energy production is the volatility of intermittent power generation due mainly to weather conditions. This fact usually limits the integration of PV systems and WTs into the power grid. Hence, accurately forecasting power generation in PV and WTs is of great importance for daily/hourly efficient management of power grid production, delivery, and storage, as well as for decision-making on the energy market. Also, accurate and prompt fault detection and diagnosis strategies are required to improve efficiencies of renewable energy systems, avoid the high cost of maintenance, and reduce risks of fire hazards, which could affect both personnel and installed equipment. This book intends to provide the reader with advanced statistical modeling, forecasting, and fault detection techniques in renewable energy systems

H-GA-PSO Method for Tuning of a PID Controller for a Buck-Boost Converter Modeled with a New Method of Signal Flow Graph Technique

In this paper, a new method of signal flow graph technique and Mason's gain formula are applied for extracting the model and transfer functions from control to output and from input to output of a buck-boost converter. In order to investigate necessity of a controller for the converter with assumed parameters, the frequency and time domain analysis is done and the open loop system characteristics are verified. In addition, the needed closed loop controlled system specifications are determined. Moreover, designing a controller for the mentioned converter system based on the extracted model is discussed. For this purpose, a proportional-integral-derivative (PID) controller is designed and the hybrid of genetic algorithm (GA) and particle swarm optimization (PSO), called H-GA-PSO method is used for tuning of the PID controller. Finally, the simulation results are used to show the performance of the proposed modeling and regulation methods

Design and Performance Analysis of Effective Controllers for Multi-level DC to DC Cascaded Boost Converter

In this article, an investigation of effective controllers for Multi-level DC to DC Positive Output Cascaded Boost Converter operating in continuous conduction mode is carried out. The positive output cascaded boost converter is recently designed converter which increases the output voltage in geometric progression with simple structure and has better voltage transfer gain in comparison with conventional converter. In this study, two level cascaded positive output boost converter (TLCPOBC) using super lift technique was considered and the results were compared with single level cascaded positive output boost converter (SLCPOBC) to show the importance and need of Multi-level converters in DC to DC applications. Due to switching mode operation, the characteristics of TLCPOBC were non-linear in nature. In addition, during line and load variations, the system was not stable and converters behaved drastically. Therefore, an effective controller is essential to enhance the dynamic characteristics of converter. Linear controllers like Proportional Integral Controller (PI) and Proportional plus Proportional Integral Controller (P plus PI) were considered in this study. Here, PI controller acts as Single Loop Controller (SLC) whereas, P plus PI acts as Multi Loop Controller (MLC). The main advantage of MLC over SLC is that it may regulate both output voltage and inductor current of TLCPOBC which improves the performance of the system over a wide range of operating conditions. Using Ziegler –Nicholas tuning method, the parameters of controllers were obtained by the state-space equations of TLCPOBC. The performance of controllers is verified in MATLAB/Simulink models and results are validated to show the importance of an effective controller for TLCPOBC

Modeling and identification of power electronic converters

Nowadays, many industries are moving towards more electrical systems and components. This is done with the purpose of enhancing the efficiency of their systems while being environmentally friendlier and sustainable. Therefore, the development of power electronic systems is one of the most important points of this transition. Many manufacturers have improved their equipment and processes in order to satisfy the new necessities of the industries (aircraft, automotive, aerospace, telecommunication, etc.). For the particular case of the More Electric Aircraft (MEA), there are several power converters, inverters and filters that are usually acquired from different manufacturers. These are switched mode power converters that feed multiple loads, being a critical element in the transmission systems. In some cases, these manufacturers do not provide the sufficient information regarding the functionality of the devices such as DC/DC power converters, rectifiers, inverters or filters. Consequently, there is the need to model and identify the performance of these components to allow the aforementioned industries to develop models for the design stage, for predictive maintenance, for detecting possible failures modes, and to have a better control over the electrical system. Thus, the main objective of this thesis is to develop models that are able to describe the behavior of power electronic converters, whose parameters and/or topology are unknown. The algorithms must be replicable and they should work in other types of converters that are used in the power electronics field. The thesis is divided in two main cores, which are the parameter identification for white-box models and the black-box modeling of power electronics devices. The proposed approaches are based on optimization algorithms and deep learning techniques that use non-intrusive measurements to obtain a set of parameters or generate a model, respectively. In both cases, the algorithms are trained and tested using real data gathered from converters used in aircrafts and electric vehicles. This thesis also presents how the proposed methodologies can be applied to more complex power systems and for prognostics tasks. Concluding, this thesis aims to provide algorithms that allow industries to obtain realistic and accurate models of the components that they are using in their electrical systems.En la actualidad, el uso de sistemas y componentes eléctricos complejos se extiende a múltiples sectores industriales. Esto se hace con el propósito de mejorar su eficiencia y, en consecuencia, ser más sostenibles y amigables con el medio ambiente. Por tanto, el desarrollo de sistemas electrónicos de potencia es uno de los puntos más importantes de esta transición. Muchos fabricantes han mejorado sus equipos y procesos para satisfacer las nuevas necesidades de las industrias (aeronáutica, automotriz, aeroespacial, telecomunicaciones, etc.). Para el caso particular de los aviones más eléctricos (MEA, por sus siglas en inglés), existen varios convertidores de potencia, inversores y filtros que suelen adquirirse a diferentes fabricantes. Se trata de convertidores de potencia de modo conmutado que alimentan múltiples cargas, siendo un elemento crítico en los sistemas de transmisión. En algunos casos, estos fabricantes no proporcionan la información suficiente sobre la funcionalidad de los dispositivos como convertidores de potencia DC-DC, rectificadores, inversores o filtros. En consecuencia, existe la necesidad de modelar e identificar el desempeño de estos componentes para permitir que las industrias mencionadas desarrollan modelos para la etapa de diseño, para el mantenimiento predictivo, para la detección de posibles modos de fallas y para tener un mejor control del sistema eléctrico. Así, el principal objetivo de esta tesis es desarrollar modelos que sean capaces de describir el comportamiento de un convertidor de potencia, cuyos parámetros y/o topología se desconocen. Los algoritmos deben ser replicables y deben funcionar en otro tipo de convertidores que se utilizan en el campo de la electrónica de potencia. La tesis se divide en dos núcleos principales, que son la identificación de parámetros de los convertidores y el modelado de caja negra (black-box) de dispositivos electrónicos de potencia. Los enfoques propuestos se basan en algoritmos de optimización y técnicas de aprendizaje profundo que utilizan mediciones no intrusivas de las tensiones y corrientes de los convertidores para obtener un conjunto de parámetros o generar un modelo, respectivamente. En ambos casos, los algoritmos se entrenan y prueban utilizando datos reales recopilados de convertidores utilizados en aviones y vehículos eléctricos. Esta tesis también presenta cómo las metodologías propuestas se pueden aplicar a sistemas eléctricos más complejos y para tareas de diagnóstico. En conclusión, esta tesis tiene como objetivo proporcionar algoritmos que permitan a las industrias obtener modelos realistas y precisos de los componentes que están utilizando en sus sistemas eléctricos.Postprint (published version

Design and analysis of three phase inverter based Solar PV powered single switch Buck-Boost converter with reduced THD for industrial applications

The development of economical and sustainable eco-friendly renewable source powered power electronic converters have become more attractive in various areas such as automotive, household and industrial applications etc., Bucking and boosting of voltage according to the requirement is also much needed. So, this work proposes a solar PV powered single switch buck-boost converter which reduces implementation cost, minimal voltage and current stress across the capacitors and diodes and less switching power losses. The work structure comprises of solar PV source with modified P and O algorithm based MPPT, single switch buck-boost dc-dc converter, battery backup to store excess energy, three phase inverter with sinusoidal PWM to find optimal switching angles for harmonic control and 3Φ induction motor load. Here reduction of THD is applied to the line to line voltage of the inverter. Performance analysis of the proposed circuit is done using MATLAB/SIMULINK platform. A detailed steady state analysis of the dc-dc converter topology is also analyzed to system stability. The proposed single switch buck-boost converter is designed to provide an output voltage and current of 363V, 45.5A DC from 520V, 35A PV array. The designed converter is then employed to run a three phase full bridge inverter with 440V, 15A AC. From the simulation results, it is found that the solar powered single switch buck-boost with MPPT is stable, efficient with minimal losses and less THD with better quality output