Energy production and audit at renewable energy power plants

At all electricity producing renewable power plants, the main problems that occurs from the planning stage to the production stage, is the reliability of the meteorological data for the location of the power plant, the change according to the time (change trend) and to use the date at a real model to determine the production level. If the energy production capacity of a renewable power plant can not be determined correctly, reliable capacity could be determined wrongly, and as a result investment and production expenses could be calculated wrongly. Electricity network think that, the discontinuous connections at electricity energy cause waves, and create technical problems at regional network, which leads to fall at the efficiency and affectivity. This is the major reason for not benefiting efficiently from the wind energy plants in Turkey until today. By making a plan at a regional dimension, will be benefited from the diversity of the plants and therefore could give more stable and quality electrical energy to the network.New approaches were brought to these problems by wind trend forecasts made with statistical studies using the wind measurement data of the meteorological stations representing coastal town at Marmara and North Aegean coast, and by Artificial Neural Networks (ANN) method. In order to be used at wind fields planning, by the help of wind and other meteorological measurement data at the examined region, detailed statistical forms to trace the affinity of the wind were formed.By investigating the wind power production for the peak, low and reference months in terms of wind speed, of the areas that the stations at the region examined by the statistical studies represent, the decreasing factor of the difference at the wind trend on the fluctuations at the electricity energy produced from the wind power was demonstrated. By the help of formed two new generation ANN models, wind speed and directions will be predicted accurately and it would be possible to complete the missing and less dependable wind data. Thanks to this, energy production plan and control will be able to be done sensitively enough in the mid and long term.The 2nd generation model, that was developed during the ANN study and was found more successful than the first generation models, was tested by the measurement data obtained from the stations at Marmara and North Aegean Cost, and the adequate consistency was observed.Keywords: Renewable energy power plants, wind energy, artificial neural networks, energy planning, Marmara and North Aegean cost.