Change of real and simulated energy production of certain photovoltaic technologies in relation to orientation, tilt angle and dual-axis sun-tracking. A case study in Hungary

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An Efficient Microcontroller Based Sun Tracker Control for Solar Cell Systems

The solar energy is fast becoming a different means of electricity resource. Now in world Fossil fuels are seriously depleting thus the need for another energy source is a necessity. To create effective utilization of its solar, energy efficiency must be maximized. An attainable way to deal with amplifying the power output of sun-powered exhibit is by sun tracking. This paper presents the control system for a solar cell orientation device which follows the sun in real time during daytime

Solar array fed synchronous reluctance motor driven water pump : an improved performance under partial shading conditions

An improved performance of a photovoltaic (PV) pumping system employing a synchronous reluctance motor (SynRM) under partial shading conditions is proposed. The system does not include the dc-dc converter that is predominantly being utilized for maximizing the output power of the PV array. In addition, storage batteries are also not contained. A conventional inverter connected directly to the PV array is used to drive the SynRM. Further, a control strategy is proposed to drive the inverter so that the maximum output power of the PV array is achieved while the SynRM is working at the maximum torque per Ampere condition. Consequently, this results in an improved system efficiency and cost. Moreover, two maximum power point tracking (MPPT) techniques are compared under uniform and partial shadow irradiation conditions. The first MPPT algorithm is based on the conventional perturbation and observation (P&O) method and the second one uses a differential evolution (DE) optimization technique. It is found that the DE optimization method leads to a higher PV output power than using the P&O method under the partial shadow condition. Hence, the pump flow rate is much higher. However, under a uniform irradiation level, the PV system provides the available maximum power using both MPPT techniques. The experimental measurements are obtained to validate the theoretical work

Management of solar energy in microgrids using IoT-based dependable control

© 2017 IEEE. Solar energy generation requires efficient monitoring and management in moving towards technologies for net-zero energy buildings. This paper presents a dependable control system based on the Internet of Things (IoT) to control and manage the energy flow of renewable energy collected by solar panels within a microgrid. Data for optimal control include not only measurements from local sensors but also meteorological information retrieved in real-time from online sources. For system fault tolerance across the whole distributed control system featuring multiple controllers, dependable controllers are developed to control and optimise the tracking performance of photovoltaic arrays to maximally capture solar radiation and maintain system resilience and reliability in real time despite failures of one or more redundant controllers due to a problem with communication, hardware or cybersecurity. Experimental results have been obtained to evaluate the validity of the proposed approach

A real time simulation of a photovoltaic system with maximum power point tracking

International audienceThis work presents an experimental stand for the study of a power electronics control system to locate and track the maximum power point of a photovoltaic (PV) array to ensure efficient power transfer from the solar cells to the load under varying environmental conditions. A real-time photovoltaic solar cell measurements and a control system was developed to guarantee that the maximum power output is attained. This stand is built at the Electrical Machinery Laboratory of “Vasile Alecsandri” University of Bacau, Romania

Design of Control Algorithm for Renewable Energy Resources

The need for renewable energy sources is on the rise because of the subtle energy crisis in the world today. By the year 2020, India plans to produce atleast a minimum of 20 Gigawatts of Solar power, whereas we have only tapped less than half a Gigawatt of our potential as of March 2010. Solar energy is an important untapped resource in a tropical country like ours. The main obstruction for the penetration and reach of solar PV systems is their high capital cost and low efficiency. In this thesis, we examine a schematic to extract maximum obtainable solar power from a PV module and use the energy for DC and AC application also tackling with the problem of partial shading in PV. This project also uses the concept of Maximum PowerPoint Tracking (MPPT) which significantly increases the efficiency of the solar photovoltaic system. But in this project our main intention is to interface the PV array with the MPP tracker and process power for dc and ac loads. All simulations are carried under MATLAB/Simulink environment

The design and optimization of a system using an induction motor driven pump, powered by solar panels

This thesis describes the design and evaluation of an induction motor driven water pumping system which is powered by solar panels. The system consists of a positive displacement pump, solar panels and an induction motor with a microprocessor controlled inverter. The reason that an induction motor has been chosen for the project is that these motors are cheaper and more robust than the more conventional DC motors. It is expected that by using an induction motor, the system performance will improve significantly for the same investment. The motor has a power rating of 0.75kW and it has been specially designed for a solar application. The system has been designed to operate from between five and seven solar panels, which yields a system capacity of 350W. The capacity could be extended to operate up to the full rating of the motor. A variable frequency drive has been designed to control the motor speed. The drive consists of a power MOSFET inverter bridge which is controlled by an 8031 microcontroller. Software has been written for the controller to generate the required pulse-width modulated signals to the inverter. Also included in the system design is an array tracker which optimizes the power output of the solar panels. The efficiency of the motor has been optimized for the torque requirements of the pump. This has been achieved by implementing an optimized voltage frequency curve and by providing for operation above the rated frequency of the motor. The motor has been operated in the frequency range of 5 - 80Hz. The inverter efficiency was high at 87% and this is expected to increase at higher power ratings. The combined motor and inverter efficiency was found to be 67% over a frequency range of 45 - 80Hz. This is only marginally less than the efficiency found in DC systems where a DC-DC converter is required to drive the motor. The control method for the system incorporated a method of maximizing the water delivery. This was achieved by optimizing the motor speed while monitoring the panel voltage. The voltage was monitored because of the high inertia of the pump, which made pure speed control difficult to implement. A field test was conducted to compare the developed AC system with a Mono DC system. The gearing of the DC system was not optimal and hence a higher flow rate was achieved with the AC system. However, the efficiency of the DC motor and converter combination proved to be slightly higher than that of the AC system. This comparison neglected the effect of poor maximum power point tracking of the DC system. In conclusion, the implementation of an AC induction motor system offers significant advantages over a DC system in terms of cost and reliability, while similar efficiencies are expected from the two systems. The cost reduction with a seven panel system will more than cover the cost of another panel, which represents a 15% increase in the system input power. The speed control of the system ensures that the water delivery is maximized at all operating irradiance levels and hence the panel output is fully utilized. The system performance is further enhanced with the use of an array tracker, which will improve the panel output by approximately 20%

Real-time Modelling, Diagnostics and Optimised MPPT for Residential PV Systems

The work documented in the thesis has been focused into two main sections. The first part is centred around Maximum Power Point Tracking (MPPT) techniques for photovoltaic arrays, optimised for fast-changing environmental conditions, and is described in Chapter 2. The second part is dedicated to diagnostic functions as an additional tool to maximise the energy yield of photovoltaic arrays (Chapter 4). Furthermore, mathematical models of PV panels and arrays have been developed and built (detailed in Chapter 3) for testing MPPT algorithms, and for diagnostic purposes.In Chapter 2 an overview of the today’s most popular MPPT algorithms is given, and, considering their difficulty in tracking under variable conditions, a simple technique is proposed to overcome this drawback. The method separates the MPPT perturbation effects from environmental changes and provides correct information to the tracker, which is therefore not affected by the environmental fluctuations. The method has been implemented based on the Perturb and Observe (P&O), and the experimental results demonstrate that it preserves the advantages of the existing tracker in being highly efficient during stable conditions, having a simple and generic nature, and has the benefit of also being efficient in fast-changing conditions. Furthermore, the algorithm has been successfully implemented on a commercial PV inverter, currently on the market. In Chapter 3, an overview of the existing mathematical models used to describe the electrical behaviour of PV panels is given, followed by the parameter determination for the five-parameter single-exponential model based on datasheet values, which has been used for the implementation of a PV simulator taking in account the shape, size ant intensity of partial shadow in respect to bypass diodes.In order to eliminate the iterative calculations for parameter determinations, a simplified three-parameter model is used throughout Chapter 4, dedicated to diagnostic functions of PV panels. Simple analytic expressions for the model important parameters, which could reflect deviations from the normal (e.g. from datasheet or reference measurement) I −V characteristic, is proposed.A considerable part of the thesis is dedicated to the diagnostic functions of crystalline photovoltaic panels, aimed to detect failures related to increased series resistance and partial shadowing, the two major factors responsible for yield-reduction of residential photovoltaic systems.Combining the model calculations with measurements, a method to detect changes in the panels’ series resistance based on the slope of the I − V curve in the vicinity of open-circuit conditions and scaled to Standard Test Conditions (STC) , is proposed. The results confirm the benefits of the proposed method in terms of robustness to irradiance changes and to partial shadows.In order to detect partial shadows on PV panels, a method based on equivalent thermal voltage (Vt) monitoring is proposed. Vt is calculated using the simplified three-parameter model, based on experimental curve. The main advantages of the method are the simple expression for Vt, high sensitivity to even a relatively small area of partial shadow and very good robustness against changes in series resistance.Finally, in order to quantify power losses due to different failures, e.g. partial shadows or increased series resistance, a model based approach has been proposed to estimate the panel rated power (in STC). Although it is known that the single-exponential model has low approximation precision at low irradiation conditions, using the previously determined parameters it was possible to achieve relatively good accuracy. The main advantage of the method is that it relies on already determined parameters (Rsm, Vt) based on measurements, therefore reducing the errors introduced by the limitation of the single-exponential model especially at low irradiation conditions

Adaptive photovoltaic solar module based on internet of things and web-based monitoring system

This paper presents an intelligent of single axis automatic adaptive photovoltaic solar module. A static solar panel has an issue of efficiency on shading effects, irradiance of sunlight absorbed, and less power generates. This aims to design an effective algorithm tracking system and a prototype automatic adaptive solar photovoltaic (PV) module connected through internet of things (IoT). The system has successfully designated on solving efficiency optimization. A tracking system by using active method orientation and allows more power and energy are captured. The solar rotation angle facing aligned to the light-dependent resistor (LDR) voltage captured and high solar panel voltage measured by using Arduino microcontroller. Real-time data is collected from the dynamic solar panel, published on Node-Red webpage, and running interactive via android device. The system has significantly reduced time. Data captured by the solar panel then analyzed based on irradiance, voltage, current, power generated and efficiency. Successful results present a live data analytic platform with active tracking system that achieved larger power generated and efficiency of solar panel compared to a fixed mounted array. This research is significant that can help the user to monitor parameters collected by the solar panel thus able to increase 51.82% efficiency of the PV module

Integration of a lithium-ion battery in a micro-photovoltaic system: Passive versus active coupling architectures

A balcony photovoltaic (PV) system, also known as a micro-PV system, is a small PV system consisting of one or two solar modules with an output of 100–600 Wp and a corresponding inverter that uses standard plugs to feed the renewable energy into the house grid. In the present study we demonstrate the integration of a commercial lithium-ion battery into a commercial micro-PV system. We firstly show simulations over one year with one second time resolution which we use to assess the influence of battery and PV size on self-consumption, self-sufficiency and the annual cost savings. We then develop and operate experimental setups using two different architectures for integrating the battery into the micro-PV system. In the passive hybrid architecture, the battery is in parallel electrical connection to the PV module. In the active hybrid architecture, an additional DC-DC converter is used. Both architectures include measures to avoid maximum power point tracking of the battery by the module inverter. Resulting PV/battery/inverter systems with 300 Wp PV and 555 Wh battery were tested in continuous operation over three days under real solar irradiance conditions. Both architectures were able to maintain stable operation and demonstrate the shift of PV energy from the day into the night. System efficiencies were observed comparable to a reference system without battery. This study therefore demonstrates the feasibility of both active and passive coupling architectures