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Djurdjevic D.Z.,University of Pristina in Kosovska Mitrovica
Proceedings of the 24th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2011 | Year: 2011

This paper is aimed at analysing the status and perspectives of the solar photovoltaic (PV) power engineering in the Republic of Serbia under present circumstances. The main objective of this paper is to assess the potential for solar PV power system utilization in Serbia. At the moment solar PV technology is not implemented in the Serbian renewable energy sources (RES) sector, however, some firm positive steps in this direction are recently taken. The effects of recently introduced feed-in tariffs (FITs) in Serbia are discussed, from the point of view of solar PVs utilization. The Serbian authorities are addressed to make an efficient policy which can enable competitive investment and utilization of emerging solar PV power systems. Assessments, calculated data and suggestions presented in this paper can be helpful to everyone who wants to participate in developing and investing in solar PV technology in Serbia. The aim of this paper is to support development of the solar PV and generally RES energy sector in Serbia as a country with great potential for utilizing PVs. The results of present study show that there is a lot of administrative work to be done (policy-making, educational support and RES and PVs promotion) in order to achieve expected results from solar PV power engineering in the future.

Petkovic D.,University of Nis | Shamshirband S.,University of Malaya | Kamsin A.,University of Malaya | Lee M.,Chonbuk National University | And 2 more authors.
Renewable and Sustainable Energy Reviews | Year: 2016

The main objective of wind farm modeling is to maximize wind farm efficiency. The optimal wind turbine placement on a wind farm could be modified by taking economic aspects into account. The net present value (NPV) is the most important criteria for project investment estimating. The general approach in deciding the distinctive choice for a task through NPV is to treat the money streams as known with conviction. Even little deviations from the decided beforehand values might effectively negate the choice. To assess the investment risk of wind power project, this paper constructed a process that selected the most influential wind farm parameters on the NPV with adaptive neuro-fuzzy (ANFIS) method. This procedure is typically called variable selection, which corresponds to finding a subset of the full set of recorded variables that exhibits good predictive abilities. Variable seeking utilizing the ANFIS system was performed to figure out how the seven wind farm parameters affect the NPV of the wind farm. © 2015 Elsevier Ltd. All rights reserved.

Radosavljevic J.,University of Pristina in Kosovska Mitrovica
Applied Artificial Intelligence | Year: 2016

This article presents a new hybrid algorithm based on particle swarm optimization (PSO) and the gravitational search algorithm (GSA) for solving the combined economic and emission dispatch (CEED) problem in power systems. Performance of this approach for the CEED problem is studied and evaluated on three test systems with 3, 6, and 40 generating units, with various cost curve nature and different constraints. The results obtained are compared to those reported in the recent literature. Those results show that the proposed algorithm provides an effective and robust high-quality solution of the CEED problem. © 2016 Taylor & Francis.

Anicic O.,University of Pristina in Kosovska Mitrovica | Petkovic D.,University of Nis | Cvetkovic S.,University of Pristina in Kosovska Mitrovica
Renewable and Sustainable Energy Reviews | Year: 2016

Noise annoyance caused by wind turbines has become a great problem in recent years, due to the rapid increase in number of wind turbines, triggered by sustainable energy goals set forward at the national and international level. Up to now, not all aspects of the generation, propagation and perception of wind turbine noise are well understood. For a modern large wind turbine, aerodynamic noise from the blades is generally considered to be the dominant noise source, provided that mechanical noise is adequately eliminated. The sources of aerodynamic noise can be divided into tonal noise, inflow turbulence noise, and airfoil self-noise. Many analytical and experimental acoustical studies performed the wind turbines. Since the wind turbine noise level analyzing by numerical methods could be very challenging and time consuming, soft computing techniques are preferred. The objective of this article was to estimate noise level of wind turbine by support vector regression (SVR) procedure. To build an effective wind turbine noise level prediction model, the polynomial and radial basis function (RBF) are applied as the kernel function of SVR in this research study. According to the results, a greater improvement in estimation accuracy can be achieved through the SVR with radial basis function compared to SVR with polynomial basis function. © 2015 Elsevier Ltd. All rights reserved.

Klimenta D.,University of Pristina in Kosovska Mitrovica | Radosavljevic J.,University of Pristina in Kosovska Mitrovica | Jevtic M.,University of Pristina in Kosovska Mitrovica | Raicevic V.,University of Pristina in Kosovska Mitrovica | And 2 more authors.
International Journal of Heat and Mass Transfer | Year: 2011

It is shown in this paper that the non-adiabatic nature of phase-to-earth fault thermodynamics in buried power cables can be modelled in an even more precise manner by using the FEM. The nonlinear FEM model has been created on the basis of an authentic case of fault caused by a previous mechanical damage of the cable sheath and insulation, as well as heat sources, thermo-physical and electrical material properties as functions of temperature and time. The proposed model is applicable to power cables of all voltage levels with different polymer insulations laid in soils with changeable moisture content, as well as to the dry arc tracking or wet arc tracking phenomena in PVC-insulated cables. © 2010 Elsevier Ltd. All rights reserved.

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