Implementation of modular MPPT algorithm for energy harvesting embedded and IoT applications

The establishment of the latest IoT systems available today such as smart cities, smart buildings, and smart homes and wireless sensor networks (WSNs) are let the main design restriction on the inadequate supply of battery power. Hence proposing a solar-based photovoltaic (PV) system which is designed DC-DC buck-boost converter with an improved modular maximum power point tracking (MPPT) algorithm. The output voltage depends on the inductor, capacitor values, metal oxide semiconductor field effect transistor (MOSFET) switching frequency, and duty cycle. This paper focuses on the design and simulation of min ripple current/voltage and improved efficiency at PV array output, to store DC power. The stored DC power will be used for smart IoT systems. From the simulation results, the current ripples are observed to be minimized from 0.062 A to 0.02 A maintaining the duty cycle at 61.09 for switching frequencies ranges from 300 kHz to 10 MHz at the input voltage 48 V and the output voltage in buck mode 24 V, boost mode 100 V by maintaining constant 99.7 efficiencies. The improvised approach is compared to various existed techniques. It is noticed that the results are more useful for the self-powered Embedded & Internet of Things systems

Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels

A hybrid neural network approach based tool for identifying the photovoltaic one-diode model is presented. The generalization capabilities of neural networks are used together with the robustness of the reduced form of one-diode model. Indeed, from the studies performed by the authors and the works present in the literature, it was found that a direct computation of the five parameters via multiple inputs and multiple outputs neural network is a very difficult task. The reduced form consists in a series of explicit formulae for the support to the neural network that, in our case, is aimed at predicting just two parameters among the five ones identifying the model: the other three parameters are computed by reduced form. The present hybrid approach is efficient from the computational cost point of view and accurate in the estimation of the five parameters. It constitutes a complete and extremely easy tool suitable to be implemented in a microcontroller based architecture. Validations are made on about 10000 PV panels belonging to the California Energy Commission database

Optimized Multi-input Single-output Energy Harvesting System

The energy harvesting sources has been introduced as a promising alternative for battery power. However, harvested energy is inherently sporadic, unstable, and unreliable. For this reason, a non-volatile processor has been previously proposed to bridge the intermittent executions in frequent power losses. Nonetheless, recurrent power failures reduce overall system performance which has forced researchers to look into multi-input energy harvesting systems. The purpose of this study is to investigate the possible solutions to improve the reliability and functionality of battery-less devices. This study has two major objectives: (1) implementing periodic checkpointing on WISP5, and (2) proposing optimized multi-input single-output energy harvesting system. The WISP5 was acquired from the Sensor Systems Laboratory, University of Washington, as a viable RFID energy harvesting system to implement software checkpointing techniques. We performed the periodic checkpointing every 50ms based on the RFID power fluctuation style. Then, we explored a number of possible maximum power point tracking techniques to extract maximum power from harvesters. As a result, we verified that the open circuit voltage control is the most cost effective and efficient technique for both thermoelectric (TEG) and photovoltaic (PV) . Also, we revealed that in low-level input voltages, following the fact that the maximum power extraction can be achieved at half of open circuit voltage does not result in maximum possible efficiency. Therefore, by adjusting the converter input voltage at about 66% of open circuit voltage, we improved power efficiency by about 18%.Electrical Engineerin

Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels

A hybrid neural network approach based tool for identifying the photovoltaic one-diode model is presented. The generalization capabilities of neural networks are used together with the robustness of the reduced form of one-diode model. Indeed, from the studies performed by the authors and the works present in the literature, it was found that a direct computation of the five parameters via multiple inputs and multiple outputs neural network is a very difficult task. The reduced form consists in a series of explicit formulae for the support to the neural network that, in our case, is aimed at predicting just two parameters among the five ones identifying the model: the other three parameters are computed by reduced form. The present hybrid approach is efficient from the computational cost point of view and accurate in the estimation of the five parameters. It constitutes a complete and extremely easy tool suitable to be implemented in a microcontroller based architecture. Validations are made on about 10000 PV panels belonging to the California Energy Commission database

Design of single switch-boosted voltage current suppressor converter for uninterrupted power supply using green resources integration

Introduction. Uninterrupted power supply is the major requirement in the areas since it involves human lives. In the current scenario the demand and price of fossil fuels is increasing rapidly and availability also is not sufficient to the needs, an alternative identification to power generation is solar and wind energies. The purpose of designing an aimed, single switch boosted voltage and current suppressor (SS-BVCS) converter topology that interfaces both the wind and solar hybrid model. The method involves in the proposed chopper converter is derived by simply merging a switch and a pair of diodes and CLC filter which is used in realization of zero voltage switching for the main switch and a reversing diode to extract high voltage gain. The designed SS-BVCS converter topology can able to have a tight self-control on two power-processing paths. The novelty of the SS-BVCS converter module is designed to ensure maximum throughput, feeding to the load with high quality uninterrupted output, by boosting the DC voltage to a required amount and thereby supressing the current. Practical value obtained by the developed model utilizes both the sources for supply to the load individually or combined based on the extraction availability of the feeder. Also, the proposed SS-BVCS module delivers with efficient lesser component count and gaining maximum power from the harvest of green energy.Вступ. Джерело безперебійного живлення є основною вимогою в галузях, що пов'язані з людськими життями. У поточній ситуації, коли попит та ціна на викопне паливо швидко зростають, а їх доступність також недостатня для задоволення потреб, альтернативною технологією виробництва електроенергії є сонячна та вітрова енергія. Метою є розробка цільової топології перетворювача з підвищеною напругою та пригнічувачем струму з одним перемикачем (SS-BVCS), яка взаємодіє як з вітровою, так і з гібридною моделлю сонячної енергії. Метод включає запропонований перетворювач переривника, отриманий шляхом простого злиття перемикача, пари діодів і CLC-фільтра, який використовується для реалізації перемикання при нульовому напрузі для основного ключа і реверсивного діода для вилучення високого коефіцієнта посилення по напрузі. Розроблена топологія перетворювача SS-BVCS може забезпечити жорсткий самоконтроль на двох ланцюгах обробки енергії. Новизна модуля перетворювача SS-BVCS призначена для забезпечення максимальної пропускної здатності, живлення навантаження з якісним безперебійним виходом шляхом підвищення напруги постійного струму до необхідної величини і, таким чином, придушення струму. Практична цінність, отримана завдяки розробленій моделі, дозволяє використовувати як джерела живлення навантаження окремо, так і комбіновано залежно від можливості відбору фідера. Крім того, запропонований модуль SS-BVCS забезпечує ефективне використання меншої кількості компонентів та отримання максимальної потужності за рахунок збирання зеленої енергії

Design and Modeling for DC Nanogrids

Smart grids were constructed as a means of communication to the electric grid through computer and other information technologies. This line of communication acts as gauge for a more accurate reading of power consumed. A nano grid is a model version of a smart grid with the ability to function as separate power generator. Such feature allows for this grid to power single loads and apply for special applications. A DC-DC converter was designed to apply to a nano grid which is a form of a smart grid. The converter was a single-input-multi-output converter which is taking one dc voltage and applying it to two dc output voltages. This boost converter takes the inputs and increases its voltages, leading to the outputs respectively. The nano grid utilizes this proposed converter to carry out its special characteristics. Procedures carried out in this research showed the success of the converter. Further steps include the designing of a ring and radial architecture nanogrid to form a microgrid. A comparison of results are made showing the efficiency and reliability of ring architecture layout microgrids Doing this creates a more complex system, and provide relief to multiple sources to prevent outages

Power Source Buffering using a Triangular Modular Multilevel Converter with Energy Storage

As power systems throughout the world continue to utilize DC infrastructure within distributed generation solutions and microgrid designs, an effective DC-DC interfacing power electronic device must be developed for managing power flow and power quality levels between a system’s increasingly diversified array of sources and loads. DC-DC power electronic interfaces are continuing to gain increased attention throughout many distribution applications, including the information and communication technology (ICT), electric vehicle, and renewable generation industries. The research effort described herein explores the use of a multi-port DC-DC modular multilevel converter interfacing a dual-input connection of a 380 VDC system and a 42.9 VDC/ 40.7 A photovoltaic panel with a 96 VDC output resistive load. Ultracapacitors are used to power-buffer the input signal and in this application, the inherently intermittent solar panel output. This technology represents the merits of utilizing a singular interfacing device to consolidate the flows between joint generation and load, while maintaining stable output power through the use of a modular energy storage solution. This work will detail the operation and control of the DC-DC converter and its module-interfaced power buffering solution, as well as provide design methodologies for the system described

An adaptive and energy-maximizing control of wave energy converters using extremum-seeking approach

In this paper, we systematically investigate the feasibility of different extremum-seeking (ES) control schemes to improve the conversion efficiency of wave energy converters (WECs). Continuous-time and model-free ES schemes based on the sliding mode, relay, least-squares gradient, self-driving, and perturbation-based methods are used to improve the mean extracted power of a heaving point absorber subject to regular and irregular waves. This objective is achieved by optimizing the resistive and reactive coefficients of the power take-off (PTO) mechanism using the ES approach. The optimization results are verified against analytical solutions and the extremum of reference-to-output maps. The numerical results demonstrate that except for the self-driving ES algorithm, the other four ES schemes reliably converge for the two-parameter optimization problem, whereas the former is more suitable for optimizing a single-parameter. The results also show that for an irregular sea state, the sliding mode and perturbation-based ES schemes have better convergence to the optimum, in comparison to other ES schemes considered here. The convergence of PTO coefficients towards the performance-optimal values are tested for widely different initial values, in order to avoid bias towards the extremum. We also demonstrate the adaptive capability of ES control by considering a case in which the ES controller adapts to the new extremum automatically amidst changes in the simulated wave conditions

Power Electronics Platforms for Grid-Tied Smart Buildings

Renewable energy sources (such as sun, wind, water, or fuel cells) are attracting great interest for either grid-tied or off-grid arrangements in smart green buildings. It must be either used when generated, stored for future use on-site, delivered to the power grid, or shared among combination of these. Grid-tied buildings are connected to the utility grid service lines. Off-grid buildings have no connection to utility service lines. Both types employ inverters to convert power from direct current (DC) to alternating current (AC), and most off-grid systems have batteries to store energy for use when needed. Accordingly, power electronics systems are playing an important role as the enabling technology for smart grid. In addition, smart meter represents the interface part between the green building and the utility grid. In order to realize the interaction between both systems, a bidirectional power conditioning module is needed. This chapter introduces the different power electronics platforms suitable for grid-tied smart green buildings (such as residential homes, commercial, and industrial) as well as its integrative functionality with advanced metering infrastructure (AMI). In order to show the superiority of these platforms in conjunction with smart meters, a hardware case study with one of the most popular power electronics topologies is presented