In this paper we have proposed a non- linear mathematical model for a wind turbine. The objective function maximizes the power of the wind turbine and the constraints are related to the rotor and tower costs. Rotor diameter and hub height are the variables which affect on power of the wind turbine, so we have considered them as decision variable in our mathematical model. By increasing rotor diameter and hub height the power of the turbine will increase but the costs don’t let the infinitive increase in rotor diameter and height. The model applied for a typical case study and the results of solving the model for it have shown in the paper.
This paper studies the impact of climate change on the electricity consumption by means of a fuzzy regression approach. The climate factors which have been considered in this paper are humidity and temperature, whereas the simultaneous effect of these two climate factors is considered. The impacts of other climate variables, like the wind, with a minor effect on energy consumption are ignored. The innovation which applies in this paper is the division of the year into two parts by using the temperature-day graph in the year. To index the humidity, data of the minimum humidity per day are used. For temperature, the maximum temperature of the first part of the year (warm days) and the minimum of the second part (cold days) are used. The indicator for the consumption is the daily peak load. The model results show high sensitivity to the temperature but low sensitivity to the humidity. Moreover, it is concluded that the model structure cannot be the same and for the cold par additional variables such as gas consumption should be considered.