Particle Swarm Optimization Approach for Estimation of Energy Demand of TurkeyTuran Paksoy1*, Eren Özceylan1, NimetYapıcı Pehlivan2 and Gerhard-Wilhelm Weber3
- *Corresponding Author:
- Turan Paksoy
Selçuk University, Department of Industrial Engineering, Campus, 42031, Konya, Turkey
E-mail: t[email protected]
This paper presents an application of Particle Swarm Optimization (PSO) technique to estimate energy demandof Turkey, based on economic indicators.The ec onomic indicators that are used during the model development are: gross national product (GNP), population, import and export figures of Turkey. Energy demand and other economic indicators in Turkey from 1979 to 2005 are considered as the case of this study. The energy estimation model based on PSO (EEPSO) is developed in two forms (linear (EEPSOL) and quadratic (EEPS OQ))and applied to forecast energy demand in Turkey. PSOQ form provided better-fit solution due to fluctuations of the economic indicators. In order to show the accuracy of the algorithm, some comparisons are made with previous studies which are using Ant Colony Optimization (ACO) and PSO. The future energy demand is calculated under different scenarios. The relative estimation errors of the proposed models are the lowe st when they are compared with the Ministry of Energy and Natural Resources (MENR) projection.