Marko Mancic

A model of a Serbian energy efficient house for decentralized electricity production

This paper presents architectural project and simulation of energy consumption and production of a model of Energy Efficient House for Decentralized Energy (DE). The house model is designed for the area of Serbia, based on the needs of an average Serbian family. The model is designed to investigate opportunities for DE of typical house geometry with advantages of passive solar architecture combined with active solar systems and heat pump. Simulation of the model was performed for the climate conditions for the city of Nis. Thermal load for designed net-zero energy efficient home for a period of one year was simulated by means of trnsys software. With respect to renewable energy sources in Serbia, production of electrical, heating, and cooling energy by solar photovoltaic/thermal collectors, heat pump, and heat storage is considered. The balance of simulated annual electricity production and consumption show that the house model can produce 51% of its energy demands. Simulation results are used to determin...

EXPERIMENTAL INVESTIGATION OF THE CONVECTIVE HEAT TRANSFER IN A SPIRALLY COILED CORRUGATED TUBE WITH RADIANT HEATING

The Archimedean spiral coil made of a transversely corrugated tube was exposed to radiant heating in order to represent a heat absorber of the parabolic dish solar concentrator. The main advantage of the considered innovative design solution is a coupling effect of the two passive methods for heat transfer enhancement - coiling of the flow channel and changes in surface roughness. The curvature ratio of the spiral coil varies from 0.029 to 0.234, while water and a mixture of propylene glycol and water are used as heat transfer fluids. The unique focus of this study is on specific boundary conditions since the heat flux upon the tube external surfaces varies not only in the circumferential direction, but in the axial direction as well. Instrumentation of the laboratory model of the heat absorber mounted in the radiation field includes measurement of inlet fluid flow rate, pressure drop, inlet and outlet fluid temperature and 35 type K thermocouples welded to the coil surface. A thermal analysis of the experimentally obtained data implies taking into consideration the externally applied radiation field, convective and radiative heat losses, conduction through the tube wall and convection to the internal fluid. The experimental results have shown significant enhancement of the heat transfer rate compared to spirally coiled smooth tubes, up to 240% in the turbulent flow regime.

NUMERICAL COMPUTATION AND PREDICTION OF ELECTRICITY CONSUMPTION IN TOBACCO INDUSTRY

Electricity is a key energy source in each country and an important condition for economic development. It is necessary to use modern methods and tools to predict energy consumption for different types of systems and weather conditions. In every industrial plant, electricity consumption presents one of the greatest operating costs. Monitoring and forecasting of this parameter provide the opportunity to rationalize the use of electricity and thus significantly reduce the costs. The paper proposes the prediction of energy consumption by a new time-series model. This involves time series models using a set of previously collected data to predict the future load. The most commonly used linear time series models are the AR (Autoregressive Model), MA (Moving Average) and ARMA (Autoregressive Moving Average Model). The AR model is used in this paper. Using the AR (Autoregressive Model) model, the Monte Carlo simulation method is utilized for predicting and analyzing the energy consumption change in the considered tobacco industrial plant. One of the main parts of the AR model is a seasonal pattern that takes into account the climatic conditions for a given geographical area. This part of the model was delineated by the Fourier transform and was used with the aim of avoiding the model complexity. As an example, the numerical results were performed for tobacco production in one industrial plant. A probabilistic range of input values is used to determine the future probabilistic level of energy consumption.