A NEW FIVE-PARAMETER MODEL FOR PV PANELS-EXPERIMENTAL VALIDATION ON A POLYCRYSTALLINE MODULE

A new five-parameters model to describe the relation between the electric current and the voltage for a photovoltaic module is experimentally validated on the field, with variable conditions of operative temperature and solar irradiance. The electrical parameters of the one diode equivalent circuit are found by solving an equations system based on the data commonly issued by manufacturers in standard test conditions. To verify the capability of the new model to fit PV panel characteristics, the model was tested on two different panels comparing the results both with the data issued by manufacturers and with the results obtained using the five- parameters model already proposed by other Authors. The comparison shows that the new model is able to reproduce with very good precision the I-V curve issued by manufactures. Furthermore, the reliability of the proposed model was assessed performing an experimental validation connecting a PV panel to several different electrical resistances. The simultaneous measurement of the silicon temperature, air temperature, wind speed and direction, solar irradiance and voltage drop across the load, has permitted to verify a very good correspondence between the measured and the calculated data

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

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

Improving the thermal performance of the transparent building envelope: finite element analysis of possible techniques to reduce the U-value of the glassblocks

U-value of glazed elements is often a critical issue because these components, due to their small thickness and to the poor resistance of the glass and frame materials, cause very relevant heat fluxes. This paper presents an investigation on the thermal properties of a particular glazed component: the glassblock. Generally standard glassblocks have high U- values in comparison to the maximum values allowed by energy efficiency standards for glazed surfaces. This paper reports a summary of possible solutions that could improve the performances of the glassblock. A set of new configurations of the glassblock has been defined by schematic models and their overall thermal resistance has been assessed by the means of Finite Element software. The resulting performances are presented in terms of the global thermal transmittance of the modified glassblocks, also considering the effects of sealing and mortar. The paper also shows some significant potential improvements to address new production lines

On the Efficacy of PCM to Shave Peak Temperature of Crystalline Photovoltaic Panels: An FDM Model and Field Validation

The exploitation of renewable energy sources and specifically photovoltaic (PV) devices have been showing significant growth; however, for a more effective development of this technology it is essential to have higher energy conversion performances. PV producers often declare a higher efficiency respect to real conditions and this deviation is mainly due to the difference between nominal and real temperature conditions of the PV. In order to improve the solar cell energy conversion efficiency many authors have proposed a methodology to keep the temperature of a PV system lower: a modified crystalline PV system built with a normal PV panel coupled with a Phase Change Material (PCM) heat storage device. In this paper a thermal model analysis of the crystalline PV-PCM system based on a theoretical study using finite difference approach is described. The authors developed an algorithm based on an explicit finite difference formulation of energy balance of the crystalline PV-PCM system. Two sets of recursive equations were developed for two types of spatial domains: a boundary domain and an internal domain. The reliability of the developed model is tested by a comparison with data coming from a test facility. The results of numerical simulations are in good agreement with experimental data

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

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

A numerical solution that determines the temperature field inside phase change materials: application in buildings

The use of novel building materials that contain active thermal components would be a major advancement in achieving significant heating and cooling energy savings. In the last 40 years, Phase Change Materials or PCMs have been tested as thermal mass components in buildings, and most studies have found that PCMs enhance the building energy performance. The use of PCMs as an energy storage device is due to their relatively high fusion latent heat; during the melting and/or solidification phase, a PCM is capable of storing or releasing a large amount of energy. PCMs in a wall layer store solar energy during the warmer hours of the day and release it during the night, thereby decreasing and shifting forward in time the peak wall temperature. In this paper, an algorithm is presented based on the general Fourier differential equations that solve the heat transfer problem in multi-layer wall structures, such as sandwich panels, that includes a layer that can change phase. In detail, the equations are proposed and transformed into formulas useful in the FDM approach (finite difference method), which solves the system simultaneously for the temperature at each node. The equation set proposed is accurate, fast and easy to integrate into most building simulation tools in any programming language. The numerical solution was validated using a comparison with the Voller and Cross analytical test problem

Development of Neural Network Prediction Models for the Energy Producibility of a Parabolic Dish: A Comparison with the Analytical Approach

Solar energy is one of the most widely exploited renewable/sustainable resources for electricity generation, with photovoltaic and concentrating solar power technologies at the forefront of research. This study focuses on the development of a neural network prediction model aimed at assessing the energy producibility of dish–Stirling systems, testing the methodology and offering a useful tool to support the design and sizing phases of the system at different installation sites. Employing the open-source platform TensorFlow, two different classes of feedforward neural networks were developed and validated (multilayer perceptron and radial basis function). The absolute novelty of this approach is the use of real data for the training phase and not predictions coming from another analytical/numerical model. Several neural networks were investigated by varying the level of depth, the number of neurons, and the computing resources involved for two different sets of input variables. The best of all the tested neural networks resulted in a coefficient of determination of 0.98 by comparing the predicted electrical output power values with those measured experimentally. The results confirmed the high reliability of the neural models, and the use of only open-source IT tools guarantees maximum transparency and replicability of the models

Monitoring Results and Energy Performances Evaluation of Freescoo Solar DEC Systems

This work addresses the energy saving performances of some solar Desiccant and Evaporative Cooling (DEC) systems working with the freescoo technology. The innovative freescoo concept is based on the use two fixed and cooled adsorption beds and advanced indirect evaporative cooling processes. The main feature of this new adsorption bed concept is to allow the simultaneous dehumidification and cooling of air. The systems analyzed have been installed in Italy last here and results based on field monitoring data are here presented. A description of the monitored systems and comparisons between the energy performances based on the main performance indicators such as EER, thermal COP, cooling power, off grid operation data are shown

The new building regulation plan schema in the town of Castelbuono (Sicily): the experience of FACTOR20- LIFE+ project

The LIFE+ Programme is the European Union’s funding instrument for the environment. The general objective of LIFE+ is to contribute to the implementation, updating and development of EU environmental policy and legislation by co-financing pilot or demonstration projects with European added value. In the framework of LIFE+, the project “Forwarding demonstrative ACTions On a Regional and local scale (FACTOR20) to reach EU targets of the European Plan 20/20/20” was founded by European Commission. FACTOR20 is aimed to define a set of tools to support the planning of regional and national policies for the reduction of greenhouse gas emissions and for the reduction of energy consumption. The knowledge of the existing building allow to quantify energy consumption of an urban area and to highlight what are the main energy problems on which to intervene. One of these tools is the definition of a new building regulation schema that identifies the best practices to improve the energy efficiency, to reduce the GHG emissions and to promote the use of RES. The authors, in order to assess the applicability and the effectiveness of some key actions proposed in the new building regulation plan schema, have performed a detailed dynamic analysis of energy consumptions related to typical building structures strongly representative of Sicilian context. The simulations, carried out by using TRNSYS17, have permitted to assess the actual energy consumptions and then to compare the new energy performances induced by the application of some key retrofit actions. In this way it was possible to identify which retrofit action is more convenient from the point of view of energy and environmental; also the designer have an indication to the designer on the priorities of retrofit actions