ENERGY DEMAND FUNCTION SIMULATION IN IRAN, BY USING PARTICLE SWARM OPTIMIZATION (PSO) ALGORITHM

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EMAMI MEYBODI ALI; KHEZRI MOHSEN; AZAMI ARASH

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Journal: ENERGY ECONOMICS REVIEW Year:2009 | Volume:6 | Issue:20 Page(s): 141-159

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Information Journal Paper

Title

ENERGY DEMAND FUNCTION SIMULATION IN IRAN, BY USING PARTICLE SWARM OPTIMIZATION (PSO) ALGORITHM

Author(s)

EMAMI MEYBODI ALI | KHEZRI MOHSEN | AZAMI ARASH | Issue Writer Certificate

Keywords

ENERGY DEMANDQ2

SIMULATIONQ2

PARTICLE SWARM OPTIMIZATION ALGORITHMQ2

Abstract

In this study, two forms of non-linear ENERGY DEMAND functions are simulated to forecast the future situation of ENERGY DEMAND in Iran (total final energy consumption) by using trend lines of macroeconomic indices. In other words, we study how efficiency of the ENERGY DEMAND estimation in Iran can be improved through use of Particle Swarm Optimization (PSO) algorithm. The PSO-based ENERGY DEMAND SIMULATION (PSOEDS) model is developed using population gross domestic product and export of goods and services as variables. In this essay, one of the suggested equations is exponential and the other one is quadratic. In ENERGY DEMAND projection, the quadratic form provides better results and can be used for evaluation of energy sector projects in Iran with greater effectiveness.

Cites

ANALYSIS AND PROJECTION OF INCOME DISTRIBUTION IN URBAN AND RURAL AREAS OF IRAN FOR 2025 VISION

References

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APA: Copy

EMAMI MEYBODI, ALI, KHEZRI, MOHSEN, & AZAMI, ARASH. (2009). ENERGY DEMAND FUNCTION SIMULATION IN IRAN, BY USING PARTICLE SWARM OPTIMIZATION (PSO) ALGORITHM. ENERGY ECONOMICS REVIEW, 6(20), 141-159. SID. https://sid.ir/paper/99471/en

Vancouver: Copy

EMAMI MEYBODI ALI, KHEZRI MOHSEN, AZAMI ARASH. ENERGY DEMAND FUNCTION SIMULATION IN IRAN, BY USING PARTICLE SWARM OPTIMIZATION (PSO) ALGORITHM. ENERGY ECONOMICS REVIEW[Internet]. 2009;6(20):141-159. Available from: https://sid.ir/paper/99471/en

IEEE: Copy

ALI EMAMI MEYBODI, MOHSEN KHEZRI, and ARASH AZAMI, “ENERGY DEMAND FUNCTION SIMULATION IN IRAN, BY USING PARTICLE SWARM OPTIMIZATION (PSO) ALGORITHM,” ENERGY ECONOMICS REVIEW, vol. 6, no. 20, pp. 141–159, 2009, [Online]. Available: https://sid.ir/paper/99471/en

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