Search

Regarding solar energy resource potential, Hungary has a daily total of around 3.2 to 3.6 kWh/m2 and an annual total of approximately 1168 to 1314 kWh/m2. It makes it a good position for solar thermal collectors in combination with an ORC system. In this study, the authors investigated solar thermal as a heat source to generate electricity, with ORC utilizing R245fa as a working fluid. Due to the limited time for utilizing solar thermal by ORC, while the highest electricity usage is at night, heat storage is carried out by integrating a TES-evaporator using organic PCM.

Since the agreement was signed officially in 2013, Institut Teknologi Nasional Bandung (ITENAS Bandung) – Indonesia and Hungarian University of Agriculture and Life Sciences (MATE Godollo) – Hungary have implemented a lot of scholarly activities, and one of them is research collaboration in the field of solar energy, especially in the thematic field of photovoltaic (PV). A set of experimental facilities has been developed and constructed to support related research. Basic facilities to understand the principle of electricity generated by PV, i.e., having the solar power plant (SPP) laboratory scale have been fulfilled by both universities. MATE Godollo has a 10 kWp SPP installation and uses polycrystalline and amorphous silicon PV modules, meanwhile, ITENAS Bandung has 1 kWp SPP and uses monocrystalline silicon PV modules. In this paper, a set of activities related to PV research collaboration between ITENAS Bandung and MATE Godollo will be elaborated, including the output and the outcome of the activities, and plan activities involving other university partners, Slovak University of Agriculture in Nitra – Slovakia and Czech University of Life Science Prague, Czech Republic.

In the course of drying process one of the main problems is to exactly determine the moisture content in the material bed. The measurement is an option, but its accuracy is not satisfactory. Another way to determine the moisture distribution is to use physically based or blackbox models. Physically based models give a moderately good result, but it normally takes a great effort to identify their parameters, and to solve the model itself. Derivation of the classical black-box models seems to be an uncomplicated approach. However, the application of such models is mainly limited mainly for process control. Therefore, this paper overviews the application opportunities of the use of artificial intelligence methods. Among those methods (neural network, Fuzzy modelling, genetic algorithm, etc) the main emphasize is given to the use of artificial neural network (ANN) modelling especially for grain drying as a widely applied dehydration technology. A methodology is given to the selection aspects of neural network structure and specifically to the main influencing model parameters as sampling time, randomised training, different training algorithms, number of hidden neurones, number of linked data series and type of validation data. Based on the recent study, it is concluded that the ANN can be used during effectively in case of post-harvest processes especially for estimation the temperature and moisture content distribution.

In this work, the examination of an experimental air-cooled photovoltaic-thermal (PV/T) module is introduced. Two different shapes of fin fixed to the copper absorber plate are examined for the classical unit of an air-cooled PV/T collector. Vertical and louver-shaped fins (with the same surface area) are investigated and thermally evaluated in this study. The experiments aimed to increase the temperature difference between inlet and outlet air to reach high thermal performance. The enhancement result showed that the thermal efficiency of the louver fin unit increased by 48% and 54% compared to the vertical fin and unfinned units, respectively. Thus, louver fins are better than vertical fins with the same surface area [ABSTRACT FROM AUTHOR]