Power Demand Forecasting Using ANN and Prophet Models for the Load Despatch Center in Andhra Pradesh, India
Damini Swargam1, Mahitha Natte2, Durga Aparajitha Javvadi3, Vamsi Krishna Chaitanya Aray4, Venkata Rama Santosh Rachuri5, Sreedhar Reddy Veguru6
1Damini Swargam, Assistant Executive Engineer, Department of Andhra Pradesh State Load Despatch Center, Transmission Corporation of Andhra Pradesh Limited, Vijayawada (Andhra Pradesh), India.
2Mahitha Natte, Assistant Executive Engineer, Department of Andhra Pradesh State Load Despatch Center, Transmission Corporation of Andhra Pradesh Limited, Vijayawada (Andhra Pradesh), India.
3Durga Aparajitha Javvadi, Statistical Officer, Department of Andhra Pradesh State Load Despatch Center, Transmission Corporation of Andhra Pradesh Limited, Vijayawada (Andhra Pradesh), India.
4Vamsi Krishna Chaitanya Aray, Assistant Executive Engineer, Department of Andhra Pradesh State Load Despatch Center, Transmission Corporation of Andhra Pradesh Limited, Vijayawada (Andhra Pradesh), India.
5Venkata Rama Santosh Rachuri, Deputy Executive Engineer, Department of Andhra Pradesh State Load Despatch Center, Transmission Corporation of Andhra Pradesh Limited, Vijayawada (Andhra Pradesh), India.
6Sreedhar Reddy Veguru, Executive Engineer, Department of Andhra Pradesh State Load Despatch Center, Transmission Corporation of Andhra Pradesh Limited, Vijayawada (Andhra Pradesh), India.
Manuscript received on 27 February 2024 | Revised Manuscript received on 09 March 2024 | Manuscript Accepted on 15 March 2024 | Manuscript published on 30 March 2024 | PP: 1-8 | Volume-14 Issue-1, March 2024 | Retrieval Number: 100.1/ijsce.A362314010324 | DOI: 10.35940/ijsce.A3623.14010324
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper uses various data variables to develop and analyze ANN and Prophet models for power demand forecasting in Andhra Pradesh, India. The electricity power consumption in Andhra Pradesh was about 51,756.000 GWh in 2021. Currently, there is a great emphasis on saving power. Power Demand Forecasting is creating much interest, and many models, such as artificial neural networks combined with other techniques based on real-life phenomena, are used and tested. These models have become an essential part of the power and energy sector. This paper considered specific time-series analysis methods and deep-learning techniques for short-term power demand forecasting. This paper also analyzes and compares results between the prophet and ANN models to predict power demand in Andhra Pradesh, India. Our results comparatively revealed the model’s appropriateness for the problem. Both models performed well in three performance metrics: accuracy, generalization, and robustness. However, the AI model exhibits better accuracy than Prophet for the historical data set. The time taken for model fitting is also comparatively less for the AI models. The forecast accuracy of the electricity was in the range of 95 to 97.65.
Keywords: Demand Forecasting, Weather, Time Series Analysis, Prophet, Keras, TensorFlow
Scope of the Article: Neural Networks