**Commenced**in January 2007

**Frequency:**Monthly

**Edition:**International

**Paper Count:**30761

##### Global Electricity Consumption Estimation Using Particle Swarm Optimization (PSO)

**Authors:**
N. Hedayat,
E.Assareh,
M.A. Behrang,
R. Assareh

**Abstract:**

An integrated Artificial Neural Network- Particle 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:**
Forecasting,
Electricity,
fossil fuels,
Particle Swarm Optimization,
Artificial NeuralNetworks

**Digital Object Identifier (DOI):**
doi.org/10.5281/zenodo.1055497

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