3,217 research outputs found

    Application of adaptive models for the determination of the thermal behaviour of a photovoltaic panel

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    The use of reliable forecasting models for the PV temperature is necessary for a more correct evaluation of energy and economic performances. Climatic conditions certainly have a remarkable influence on thermo-electric behaviour of the PV panel but the physical system is too complex for an analytical representation. A neural-network-based approach for solar panel temperature modelling is here presented. The models were trained using a set of data collected from a test facility. Simulation results of the trained neural networks are presented and compared with those obtained with an empirical correlation

    Volume II: Thermal Behaviour, Energy Efficiency in Buildings and Sustainable Construction

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    This second volume of the Special Issue includes 13 contributions, from across the world, with very interesting research topics such as: Energy Intensity Reduction; Large-Scale Non-Residential Buildings; Dynamic Control of HVAC with Heat Pumps; Reed Potential as a Regenerative Building Material and Their Performance Characterisation; Experimental Evaluation of Energy-Efficiency in a Holistically Designed Building; A Case Study of Design and Energy Performance Analysis of a Hotel Building in a Hot and Dry Climate; Internal Convective and Radiative Heat Transfer Coefficients for a Vertical Wall in a Residential Building; Passive Façade Performance Evaluation with Shape Memory Alloy (SMA) during the Architectural Design Process; Thermal Performance Improvement of Double-Pane Lightweight Steel Framed (LSF) Walls Using Thermal Break Strips (TBS) and Reflective Foils; Energy Performance of Buildings with Thermochromic Windows in Mediterranean Climates; Energy Performance and Benchmarking for University Classrooms in Hot and Humid Climates; Effect of HVAC’s Management on Indoor Thermo-Hygrometric Comfort and Energy Balance: In Situ Assessments on a Real nearly Zero Energy Building (nZEB); Stochastic-Based Optimisation Approach towards the Integration of Photovoltaic Panels in Multi-Residential Social Housing; Effect of Climate Change and Occupant Behaviour on the Environmental Impact of the Heating/Cooling Systems of a Real Apartment: A Parametric Study through Life Cycle Assessment; Road Thermal Collector for Building Heating in South Europe (Italy): Numerical Modeling and Design of an Experimental Set-Up

    EQUIVALENT MODELS FOR PHOTOVOLTAIC CELL – A REVIEW

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    Over the years, the contribution of photovoltaic energy to an eco-friendly world is continually increasing. Photovoltaic (PV) cells are commonly modelled as circuits, so finding the appropriate circuit model parameters of PV cells is crucial for performance evaluation, control, efficiency computations and maximum power point tracking of solar PV systems. The problem of finding circuit model of solar PV cells is referred to as “PV cell equivalent model problem”. In this paper, the existing research works on PV cell model parameter estimation problem are classified according to error quali-quantitative analysis, number of parameters, translation equations and PV technology. The existent models were discussed pointing out its different levels of approximation. A qualitative comparative ranking was made and four models were found to be the best ones for simulating PV cells. Besides, based on the conducted review, some recommendations for future research are provided

    Assessment of the Operating Temperature of Crystalline PV Modules Based on Real Use Conditions

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    Determining the operating temperature of photovoltaic panels is important in evaluating the actual performance of these systems. In the literature, different correlations exist, in either explicit or implicit forms, which often do not account for the electrical behaviour of panels; in this way, estimating is based only on the passive behaviour of the . In this paper, the authors propose a new implicit correlation that takes into account the standard weather variables and the electricity production regimes of a panel in terms of the proximity to the maximum power points. To validate its reliability, the new correlation was tested on two different PV panels (Sanyo and Kyocera panels) and the results were compared with values obtained from other common correlations already available in the literature. The data show that the quality of the new correlation drastically improves the estimation of the photovoltaic operating temperature

    Metaheuristic Algorithm for Photovoltaic Parameters: Comparative Study and Prediction with a Firefly Algorithm

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    In this paper, a Firefly algorithm is proposed for identification and comparative study of five, seven and eight parameters of a single and double diode solar cell and photovoltaic module under different solar irradiation and temperature. Further, a metaheuristic algorithm is proposed in order to predict the electrical parameters of three different solar cell technologies. The first is a commercial RTC mono-crystalline silicon solar cell with single and double diodes at 33 °C and 1000 W/m2. The second, is a flexible hydrogenated amorphous silicon a-Si:H solar cell single diode. The third is a commercial photovoltaic module (Photowatt-PWP 201) in which 36 polycrystalline silicon cells are connected in series, single diode, at 25 °C and 1000 W/m2 from experimental current-voltage. The proposed constrained objective function is adapted to minimize the absolute errors between experimental and predicted values of voltage and current in two zones. Finally, for performance validation, the parameters obtained through the Firefly algorithm are compared with recent research papers reporting metaheuristic optimization algorithms and analytical methods. The presented results confirm the validity and reliability of the Firefly algorithm in extracting the optimal parameters of the photovoltaic solar cell

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

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    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
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