Evaluation of the application of Phase Change Materials (PCM) on the envelope of a typical dwelling in the Mediterranean region

In this work the application of macroencapsulated Phase Change Materials (PCM) on the envelope of a typical dwelling in the Mediterranean region is evaluated. This is the first time PCMs are evaluated for application under the specific climatic conditions of Cyprus. The simulation process is carried out using Transient Systems Simulation software (TRNSYS). Two types of simulations have been carried out: the energy rate control test and the temperature level control test. The energy savings achieved by the addition of the PCM layer on the envelope of the test cubicle compared to the base case (no insulation) ranged between 21.7 and 28.6%. The optimum PCM case was also combined with a common thermal insulation topology in Cyprus. The results showed that the maximum energy savings per year was achieved by the combined case (66.2%). In the temperature level control test the constructions containing PCM performed better during summer. The results of the optimum PCM case and the combined case were economically evaluated using Life Cycle Cost (LCC). The results of this analysis showed that the PCM case has a very long payback period (14 ½ years) while this is changing when it is combined with insulation where the payback period is reduced to 7 ½ years

Systematic solar pvt testing in steady-state and dynamic outdoor conditions

In order to predict accurately the performance of solar-thermal or hybrid PVT systems, it is necessary that the steady-state and dynamic performance of the collectors is understood. This work focuses on the testing and detailed characterization of nonconcentrating PVT collectors based on the testing procedure specified in the European standard EN 12975-2. Three different types of PVT collectors were tested in Cyprus under outdoor conditions similar to those specified in the standard. Amongst other results, we show that that poor thermal contact between the laminate and the copper absorber can lead to a significant deterioration in thermal performance and that a glass cover improves the thermal performance by reducing losses as expected, but causes electrical losses that vary with the glass transmittance and the incident angle. It is found that the reduction in electrical efficiency at large solar incidence angles is more significant than that due to elevated temperatures representative of water heating applications. Dynamic tests are performed by imposing a step change in incident irradiance in order to quantify the collector time constant and effective heat capacity. A time constant of 8 min is found for a commercial PVT module, which compares to <2 min for a flat plate solar collector. The PVT collector time constant is found to be very sensitive to the thermal contact between the PV layer and the absorber, which may vary according to the quality of construction, and also to the operating flow rate.Papers presented at the 13th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Portoroz, Slovenia on 17-19 July 2017 .International centre for heat and mass transfer.American society of thermal and fluids engineers

Machine learning for estimation of building energy consumption and performance:a review

Ever growing population and progressive municipal business demands for constructing new buildings are known as the foremost contributor to greenhouse gasses. Therefore, improvement of energy eciency of the building sector has become an essential target to reduce the amount of gas emission as well as fossil fuel consumption. One most eective approach to reducing CO2 emission and energy consumption with regards to new buildings is to consider energy eciency at a very early design stage. On the other hand, ecient energy management and smart refurbishments can enhance energy performance of the existing stock. All these solutions entail accurate energy prediction for optimal decision making. In recent years, articial intelligence (AI) in general and machine learning (ML) techniques in specic terms have been proposed for forecasting of building energy consumption and performance. This paperprovides a substantial review on the four main ML approaches including articial neural network, support vector machine, Gaussian-based regressions and clustering, which have commonly been applied in forecasting and improving building energy performance

An adaptive wavelet-network model for forecasting daily total solar-radiation

The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet-networks are feed-forward networks using wavelets as activation functions. Wavelet-networks have been used successfully in various engineering applications such as classification, identification and control problems. In this paper, the use of adaptive wavelet-network architecture in finding a suitable forecasting model for predicting the daily total solar-radiation is investigated. Total solar-radiation is considered as the most important parameter in the performance prediction of renewable energy systems, particularly in sizing photovoltaic (PV) power systems. For this purpose, daily total solar-radiation data have been recorded during the period extending from 1981 to 2001, by a meteorological station in Algeria. The wavelet-network model has been trained by using either the 19 years of data or one year of the data. In both cases the total solar radiation data corresponding to year 2001 was used for testing the model. The network was trained to accept and handle a number of unusual cases. Results indicate that the model predicts daily total solar-radiation values with a good accuracy of approximately 97% and the mean absolute percentage error is not more than 6%. In addition, the performance of the model was compared with different neural network structures and classical models. Training algorithms for wavelet-networks require smaller numbers of iterations when compared with other neural networks. The model can be used to fill missing data in weather databases. Additionally, the proposed model can be generalized and used in different locations and for other weather data, such as sunshine duration and ambient temperature. Finally, an application using the model for sizing a PV-power system is presented in order to confirm the validity of this model.Total solar-radiation data Wavelet-network Forecasting Modelling Sizing PV systems

The application of solar desalination for water purification in Cyprus

For floppy disk accompanying this thesis, please apply to the issuing universityAvailable from British Library Document Supply Centre- DSC:DX188021 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo