Energy consumption Forecast modeling using artificial intelligence method (A case study in Hamadan province)

Document Type : Case Study

Authors

1 Professor, Department of Sustainable Energy Systems Engineering, Faculty of Energy Engineering and Sustainable Resources, University of Tehran, Tehran, Iran

2 Phd. Student, School of Energy Engineering and Sustainable Resources, College of Interdisciplinary Science and Technologies, University of Tehran, Tehran, Iran

3 Associate Professor, Department of Sustainable Energy Systems Engineering, University of Tehran, Tehran, Iran

10.22059/ses.2024.383569.1104

Abstract

In this research, artificial intelligence has been used to predict energy consumption in cold regions (case study of Hamadan province). In this regard, artificial neural network models and fuzzy logic are used to predict the current trend of energy consumption. To achieve this goal, the multilayer perceptron model has been used by testing several possible architectures as well as fuzzy logic in order to select the best generalization capability. Real recorded input and output data affecting long-term energy consumption have been used in the training, validation and testing process. In this article, the developed model of neural networks is used to predict the energy consumption of Hamedan province during the years 1400 to 1409. The data is extracted annually from the energy balance sheet of the Ministry of Energy from 1380 to 1399. The output results are also compared with the fuzzy logic method. Also, the simulation results show us that the electricity demand will reach about 3318 gigawatt hours by 1409. The proposed approach can be useful in the effective implementation of energy policies, as accurate energy consumption forecasting affects investment, revenue analysis, and market research management while maintaining security of supply.

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References

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Journal of sustainable Energy Systems
Volume 3, Issue 4
October 2024
Pages 341-360

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