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The application of renewable energy sources in electrical energy generation is becoming widespread due to the decrease of installation costs and the increase of environmental concerns. Hybrid power generation systems are advantageous to meet the load demand, but optimal sizing is the main concern for having a cost-effective system based on given load demand and technoeconomic indicators. This paper proposes a deterministic algorithm and utilizes genetic and artificial bee colony (ABC) optimization algorithms for optimal sizing of PV/battery and PV/WT/battery hybrid systems with minimum levelized cost of electricity (LCOE) constraint for two locations, Nigde and Bozcaada, in Turkey. The loss of power supply probability (LPSP) is used to build a reliable system and to make sure that the system produces required energy. Experimental results showed that optimal sizing of each location is different due to different wind and solar characteristics of locations. PV/battery model is more suitable for Nigde location with 1.

Abstract- Noise emitted by road traffic is one of the main causes that degrade the standard of the population lives in urban areas. In this paper, is developed a model for the estimating of continuous noise level (Leq) on the two-lane main urban road with medians in the city of Prishtina. Comparison of the results was done through performance indicators. It is found that independent variables have direct impact to dependent variable (Leq) and determination coefficient achieve accuracy close to 94 %. This approach could be applied for predicting traffic noise to different locations with the same category of roads through residential areas. Key words- Road urban traffic noise, Model, Multiple regression analysis.

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