Comprehensive forecasting of California’s energy consumption: A multi-source and sectoral analysis using ARIMA and ARIMAX models
1 Departments of Statistics and Mathematics, University of California, Irvine, Irvine, CA, USA.
2 Departments of Computer Science and Mathematics, California State University, Fullerton, Fullerton, CA, USA.
3 Department of Mechanical Engineering, Cypress College, Cypress, CA, USA.
4 Applied Intelligence, Accenture California, CA, USA
Research Article
World Journal of Advanced Research and Reviews, 2024, 22(02), 484–497
Publication history:
Received on 30 March 2024; revised on 05 May 2024; accepted on 07 May 2024
Abstract:
California’s significant role as the second-largest consumer of energy in the United States underscores the importance of accurate energy consumption predictions. With a thriving industrial sector, a burgeoning population, and ambitious environmental goals, the state’s energy landscape is dynamic and complex. This paper presents a comprehensive analysis of California’s energy consumption trends and provides detailed forecasting models for different energy sources and sectors. The study leverages ARIMA and ARIMAX models, considering both historical consumption data and exogenous variables. We address the unique challenges posed by the COVID-19 pandemic and the limited data for 2022, highlighting the resilience of these models in the face of uncertainty. Our analysis reveals that while fossil fuels continue to dominate California’s energy landscape, renewable energy sources, particularly solar and biomass, are experiencing substantial growth. Hydroelectric power, while sensitive to precipitation, remains a significant contributor to renewable energy consumption. Furthermore, we anticipate ongoing efforts to reduce fossil fuel consumption. The forecasts for energy consumption by sector suggest some decline in the commercial and residential sectors, reflecting California’s recently declining population and the shift away from brick-and-mortar shops and offices to online websites and remote work. In contrast, the industrial and transportation sectors are expected to experience some growth until they return to more constant pre-COVID levels.
Keywords:
Energy Forecasting; California Energy; ARIMA; Sectoral Analysis; Predictive Models
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0