A comparative study of MPPT strategies and a novel singlephase integrated buck-boost inverter for small wind energy conversion systems

This paper presents the analysis of some usual MPPT (Maximum Power Point Tracking) strategies intended for small wind energy conversion (up to 1kW) based on permanent magnet synchronous generators (PMSG), considering the stand-alone application for a novel buck-boost integrated inverter. Each MPPT method is analytically introduced and then it is simulated using MatLab/Simulink considering standard conditions of wind and also commercially available turbines and generators. The extracted power in each case is compared with the maximum available power, so the tracking factor is calculated for each method. Thus, the focus is on the application to improve the efficiency of stand-alone wind energy conversion systems (WECS) with battery chargers and AC load supplied by inverter. Therefore, for this purpose a novel single phase buck-boost integrated inverter is introduced. Finally, the main experimental results for the introduced inverter are presented. © 2011 IEEE.

Mini-inversores para aproveitamento de energia fotovoltaica, com técnicas de MPPT, sincronismo e conexão com a rede de CA em BT, proteção de ilhamento, gerenciamento da energia e da operação

Pós-graduação em Engenharia Elétrica - FEIS

Inversores integrados monofásicos e trifásicos para aplicações fotovoltaicas: técnicas para obtenção de mppt, detecção e proteção de ilhamento, sincronização e paralelismo com a rede de distribuição de energia elétrica

Pós-graduação em Engenharia Elétrica - FEIS

Analytical study and evaluation results of power optimizers for distributed power conditioning in PV arrays

The use of modular or ‘micro’ maximum power point tracking (MPPT) converters at module level in series association, commercially known as “power optimizers”, allows the individual adaptation of each panel to the load, solving part of the problems related to partial shadows and different tilt and/or orientation angles of the photovoltaic (PV) modules. This is particularly relevant in building integrated PV systems. This paper presents useful behavioural analytical studies of cascade MPPT converters and evaluation test results of a prototype developed under a Spanish national research project. On the one hand, this work focuses on the development of new useful expressions which can be used to identify the behaviour of individual MPPT converters applied to each module and connected in series, in a typical grid-connected PV system. On the other hand, a novel characterization method of MPPT converters is developed, and experimental results of the prototype are obtained: when individual partial shading is applied, and they are connected in a typical grid connected PV array

A coordinated control scheme for power demand changes in a PMSG based multi-terminal DC wind farm

Although maximum power point tracking (MPPT) is crucial in the design of a wind power generation system, the necessary control strategies should also be considered for conditions that require a power reduction, called de-loading in this paper. A coordinated control scheme for a proposed current source converter (CSC) based DC wind energy conversion system is presented in this paper. This scheme combines coordinated control of the pitch angle, a DC load dumping chopper and the DC/DC converter, to quickly achieve wind farm de-loading. MATLAB/Simulink simulations and experiments are used to validate the purpose and effectiveness of the control scheme, both at the same power level. © 2013 IEEE.

Thermography-based virtual MPPT scheme for improving PV energy efficiency under partial shading conditions

This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array.

Hybrid Power System Intelligent Operation and Protection Involving Plug-in Electric Vehicles

Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.

Modelling of an efficient dynamic smart solar photovoltaic power grid system

A smart solar photovoltaic grid system is an advent of innovation coherence of information and communications technology (ICT) with power systems control engineering via the internet [1]. This thesis designs and demonstrates a smart solar photovoltaic grid system that is selfhealing, environmental and consumer friendly, but also with the ability to accommodate other renewable sources of energy generation seamlessly, creating a healthy competitive energy industry and optimising energy assets efficiency. This thesis also presents the modelling of an efficient dynamic smart solar photovoltaic power grid system by exploring the maximum power point tracking efficiency, optimisation of the smart solar photovoltaic array through modelling and simulation to improve the quality of design for the solar photovoltaic module. In contrast, over the past decade quite promising results have been published in literature, most of which have not addressed the basis of the research questions in this thesis. The Levenberg-Marquardt and sparse based algorithms have proven to be very effective tools in helping to improve the quality of design for solar photovoltaic modules, minimising the possible relative errors in this thesis. Guided by theoretical and analytical reviews in literature, this research has carefully chosen the MatLab/Simulink software toolbox for modelling and simulation experiments performed on the static smart solar grid system. The auto-correlation coefficient results obtained from the modelling experiments give an accuracy of 99% with negligible mean square error (MSE), root mean square error (RMSE) and standard deviation. This thesis further explores the design and implementation of a robust real-time online solar photovoltaic monitoring system, establishing a comparative study of two solar photovoltaic tracking systems which provide remote access to the harvested energy data. This research made a landmark innovation in designing and implementing a unique approach for online remote access solar photovoltaic monitoring systems providing updated information of the energy produced by the solar photovoltaic module at the site location. In addressing the challenge of online solar photovoltaic monitoring systems, Darfon online data logger device has been systematically integrated into the design for a comparative study of the two solar photovoltaic tracking systems examined in this thesis. The site location for the comparative study of the solar photovoltaic tracking systems is at the National Kaohsiung University of Applied Sciences, Taiwan, R.O.C. The overall comparative energy output efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic monitoring system as observed at the research location site is about 72% based on the total energy produced, estimated money saved and the amount of CO2 reduction achieved. Similarly, in comparing the total amount of energy produced by the two solar photovoltaic tracking systems, the overall daily generated energy for the month of July shows the effectiveness of the azimuthal-altitude tracking systems over the 450 stationary solar photovoltaic system. It was found that the azimuthal-altitude dual-axis tracking systems were about 68.43% efficient compared to the 450 stationary solar photovoltaic systems. Lastly, the overall comparative hourly energy efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic energy system was found to be 74.2% efficient. Results from this research are quite promising and significant in satisfying the purpose of the research objectives and questions posed in the thesis. The new algorithms introduced in this research and the statistical measures applied to the modelling and simulation of a smart static solar photovoltaic grid system performance outperformed other previous works in reviewed literature. Based on this new implementation design of the online data logging systems for solar photovoltaic monitoring, it is possible for the first time to have online on-site information of the energy produced remotely, fault identification and rectification, maintenance and recovery time deployed as fast as possible. The results presented in this research as Internet of things (IoT) on smart solar grid systems are likely to offer real-life experiences especially both to the existing body of knowledge and the future solar photovoltaic energy industry irrespective of the study site location for the comparative solar photovoltaic tracking systems. While the thesis has contributed to the smart solar photovoltaic grid system, it has also highlighted areas of further research and the need to investigate more on improving the choice and quality design for solar photovoltaic modules. Finally, it has also made recommendations for further research in the minimization of the absolute or relative errors in the quality and design of the smart static solar photovoltaic module.

Hybrid power system intelligent operation and protection involving plug-in electric vehicles

Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. ^ The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. ^ The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.^

A Voltage Limiter Circuit for Indoor Light Energy Harvesting Applications

A voltage limiter circuit for indoor light energy harvesting applications is presented. This circuit is a part of a bigger system, whose function is to harvest indoor light energy, process it and store it, so that it can be used at a later time. This processing consists on maximum power point tracking (MPPT) and stepping-up, of the voltage from the photovoltaic (PV) harvester cell. The circuit here described, ensures that even under strong illumination, the generated voltage will not exceed the limit allowed by the technology, avoiding the degradation, or destruction, of the integrated die. A prototype of the limiter circuit was designed in a 130 nm CMOS technology. The layout of the circuit has a total area of 23414 mu m(2). Simulation results, using Spectre, are presented.

Implementação de um Sistema MPPT em Circuito Integrado CMOS

Ao longo dos últimos anos a indústria microelectrónica tem evoluído no sentido de reduzir o consumo energético dos seus dispositivos no sentido de estes serem alimentados por fontes energéticas diversas, nomeadamente fontes renováveis. A crescente demanda por componentes energeticamente eficientes e pela miniaturização dos componentes eletrónicos exigem a conceção de fontes de alimentação com potência reduzida na ordem das dezenas de μW ás centenas de mW. Atualmente, com os crescentes avanços tecnológicos é possível obter componentes energéticamente eficientes e com tamanhos reduzidos capazes de colmatar as restrições energéticas das mais variadas aplicações. A utilização de fontes energia elétrica que tirão proveito da energia existente no meio onde se inserem os diversos dispositivos eletrónicos ou simplesmente para recarregar as baterias, apresenta-se como um dos principais objetivos a alcançar. Entre todas as energias renováveis, a energia fotovoltaica surge como umas das que proporciona um maior potencial. A sua disponibilidade global e os constantes desenvolvimentos tecnológicos no âmbito do fotovoltaico permitem o desenvolvimento de sistemas de alimentação com rendimento energético cada vez mais elevado. A presente dissertação tem como objetivo o estudo, a simulação e implementação de um conversor CC-CC, step-up, com algoritmo de controlo MPPT integrado designado por método de correlação de ripple (Ripple Correlation Control – RCC), para aplicações de baixa potência na ordem das dezenas de μW às centenas de mW. Desenvolveu-se um conversor CC-CC, autónomo, para carregamento de baterias com recurso a painéis fotovoltaicos, como fonte de energia, de forma contínua mesmo em situações de baixa luminosidade. Um circuito de gestão de energia devidamente dimensionado foi implementado com recurso a um algoritmo de procura do ponto de máxima potência (Maximum Power Point Tracking – MPPT). O objetivo desta implementação é extrair a máxima potência disponível da fonte de energia elétrica, neste caso o painel fotovoltaico, independentemente das condições meteorológicas e da potência requerida pela carga, sendo o excesso de energia redirecionado para a bateria. Nesta dissertação apresentam-se os resultados das simulações, assim como os resultados experimentais de todos os circuitos desenvolvidos de forma a validar todo o sistema implementado.

DC Boost Stage in Photovoltaic Systems

The performance of Grid connected Photovoltaic System working with DCBoost stage is investigated. The DC-Boost Converter topology is deduced from three phase half controlled bridge and controlled by Sliding Mode Control. Due to the fact that Grid connected Photovoltaic System includes Solar cells as a DC source and inverter for grid connection, those are under the scope of this research as well. The advantages of using MPPT are analyzed. The system is simulated in Matlab-Simulink™ environment.

Avaliação das principais t́cnicas para obtenção de MPPT de paińis fotovoltaicos

Electrical energy from photovoltaic panels (PV) has became an increasing viable alternative because of the great concern for environmental preservation and the possibility of the reduction of the conventional fuels, and this natural energy source is free, abundant and clean. In addition, Brazil is a privileged country because of the high levels of irradiation throughout its territory all over the year. Thus the exploitation of the energy from PV is one of the best alternatives to overcome the supply electrical energy issues. However, nowadays the energy conversion efficiency is low and the initial costs are high for these energy systems. Therefore, in order to increase the efficiency of these systems the extraction of the maximum power point (MPP) from PV is extremely necessary, and it is done using the maximum power point tracking (MPPT) techniques. The MPP of the PV varies non linearly with the environmental conditions and several MPPT techniques are available in literature, and this paper presents a careful comparison among the most usual techniques, doing meaningful comparisons with respect to the amount of energy extracted, PV voltage ripple, dynamic response and use of sensors, considering that the models are implemented via MatLab/Simulink®. © 2010 IEEE.

Evaluation of MPPT techniques for photovoltaic applications

This paper presents a careful evaluation among the most usual MPPT (Maximum Power Point Tracking) techniques, doing meaningful comparisons with respect to the amount of energy extracted from the photovoltaic (PV) panel, PV voltage ripple, dynamic response and use of sensors. Firstly, the MPPT and boost converter models were implemented via MatLab/Simulink®, and after a DC to DC boost converter, digitally controlled, was implemented and connected to an Agilent Solar Array simulator, in order to validate the simulation results. The algorithms are digitally developed and the main experimental results are also presented from the implemented prototype. Furthermore, the experimental dynamic results and the computed tracking factors are presented. © 2011 IEEE.

Evaluation of the main MPPT techniques for photovoltaic applications

This paper presents evaluations among the most usual maximum power point tracking (MPPT) techniques, doing meaningful comparisons with respect to the amount of energy extracted from the photovoltaic (PV) panel [tracking factor (TF)] in relation to the available power, PV voltage ripple, dynamic response, and use of sensors. Using MatLab/Simulink and dSPACE platforms, a digitally controlled boost dc-dc converter was implemented and connected to an Agilent Solar Array E4350B simulator in order to verify the analytical procedures. The main experimental results are presented for conventional MPPT algorithms and improved MPPT algorithms named IC based on proportional-integral (PI) and perturb and observe based on PI. Moreover, the dynamic response and the TF are also evaluated using a user-friendly interface, which is capable of online program power profiles and computes the TF. Finally, a typical daily insulation is used in order to verify the experimental results for the main PV MPPT methods. © 2012 IEEE.