Global Electricity Consumption Estimation Using Particle Swarm Optimization (PSO)

نویسندگان

  • E. Assareh
  • M. A. Behrang
  • R. Assareh
  • N. Hedayat
چکیده

An integrated Artificial Neural NetworkParticle Swarm Optimization (PSO) is presented for analyzing global electricity consumption. To aim this purpose, following steps are done: STEP 1: in the first step, PSO is applied in order to determine world’s oil, natural gas, coal and primary energy demand equations based on socio-economic indicators. World’s population, Gross domestic product (GDP), oil trade movement and natural gas trade movement are used as socio-economic indicators in this study. For each socio-economic indicator, a feed-forward back propagation artificial neural network is trained and projected for future time domain. STEP 2: in the second step, global electricity consumption is projected based on the oil, natural gas, coal and primary energy consumption using PSO. global electricity consumption is forecasted up to year 2040. Keywords—Particle Swarm Optimization; Artificial Neural Networks; Fossil Fuels; Electricity; Forecasting

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تاریخ انتشار 2012