Mid-term load forecasting - application in oil facilities
Oil production is a strategic business, important investments in infrastructure are performed in order to assure the reliability, quality and safety of the associated electric power system. This issue requires making an accurate forecast of power demand in the medium and long term, to avoid over- or under-investments that would produce economic effects. Conventional methods of forecasting demand for industrial sectors do not consider the variables involved in the process of oil extraction. For that reason, the present article, proposes a comprehensive method to forecast the electric power demand for an oil field in the medium-term. The key drivers of the demand, are parameters related to oil production process, which are directly obtained through field measurements, e.g. oil, gas, and water production volumes. A multiple linear regression method is applicated to forecast the future electricity demand, and it is validated by comparing the results of applying a conventional regression model. Satisfactory results are obtained.
A novel short-term load forecasting approach using Adaptive Neuro-Fuzzy Inference System
By developments on smart grid technologies, the management of the grid issue get more importance. Load forecasting is one of the most important topics for managing the grid. In this study, it is aimed to develop a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) based load forecasting approach for small regions having less consumption. For this aim Çay vocational high school campus area of Afyon Kocatepe University is considered. Measured and recorded hourly load demand of the campus is predicted using proposed ANFIS based model. In proposed forecasting model, only consumption parameter is required. The other parameters are calculated from this parameter. In this scope, first order derivative of the consumption, actual consumption, month and hour parameters are used as the inputs of ANFIS model to forecast next hour load demand. The experimental results show that the proposed approach is well in load forecasting for small regions.
Real-time expert seismology by non-linear oil reserves expert system
A non-linear 3-D elastic waves real - time expert system is proposed for the exploration of land and marine oil reserves, according to the new theory of "Real-Time Expert Seismology". This Generic Technology will work under Real Time Logic for searching the land and marine petroleum developed on the continental crust and on deeper water ranging from 300 to 2000 m, or 3000 m, or even more. Hence, the proposed real - time expert system will be the best device for the exploration of the continental margin areas (shelf, slope and rise) and the very deep waters, too. Furthermore, the above expert system will be suitable for the exploration of land oil reserves, as well. The objectives for exploration of marine and land oil resources are to locate, characterize and evaluate the size of such reserves. Hence, there is a research and development responsibility for the acquisition and analysis of geophysical, geological and reservoir engineering data for the land and the seas all over the world, in order to be explored their petroleum and gas reserves. Thus, through the new technology of "Real-time Expert Seismology", will be effected the exploration of a significant part of marine and land oil reserves very fast and by a low cost. 
 
   
 
 Key words: Real-time expert seismology, land oil reserves, marine oil reserves, non-linear real - time expert system, real- time logic, generic technology.