Saudi Arabia's Electricity: Energy Supply and Demand Future Challenges

Harbi, Fahad Al; Csala, Dénes

doi:10.1109/gpecom.2019.8778554

Cited by 7 publications

(2 citation statements)

References 6 publications

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“…The performance of the proposed method of genetic algorithms is important due to the inherent parallelism of genetic algorithms and the need to reduce computation time [34]. Alharbi and Csala [35] conducted a study to forecast the long-term power performance for Saudi Arabia using a Group Method of Data Handling (GMDH)-based neural network. Although these methods are widely used, these models lack high accuracy and evaluation methods.…”

Section: Overview Of Related Studiesmentioning

confidence: 99%

A Seasonal Autoregressive Integrated Moving Average with Exogenous Factors (SARIMAX) Forecasting Model-Based Time Series Approach

Alharbi

Csala

2022

Inventions

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Time series modeling is an effective approach for studying and analyzing the future performance of the power sector based on historical data. This study proposes a forecasting framework that applies a seasonal autoregressive integrated moving average with exogenous factors (SARIMAX) model to forecast the long-term performance of the electricity sector (electricity consumption, generation, peak load, and installed capacity). In this study, the model was used to forecast the aforementioned factors in Saudi Arabia for 30 years from 2021 to 2050. The historical data that were inputted into the model were collected from Saudi Arabia at quarterly intervals across a 40-year period (1980−2020). The SARIMAX technique applies a time series approach with seasonal and exogenous influencing factors, which helps reduce the error values and improve the overall model accuracy, even in the case of close input and output dataset lengths. The experimental findings indicated that the SARIMAX model has promising performance in terms of categorization and consideration, as it has significantly improved forecasting accuracy compared with the simpler autoregressive integrated moving average-based techniques. Furthermore, the model is capable of coping with different-sized sequential datasets. Finally, the model aims to help address the issue of a lack of future planning and analyses of power performance and intermittency, and it provides a reliable forecasting technique, which is a prerequisite for modern energy systems.

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Section: Overview Of Related Studiesmentioning

confidence: 99%

A Seasonal Autoregressive Integrated Moving Average with Exogenous Factors (SARIMAX) Forecasting Model-Based Time Series Approach

Alharbi

Csala

2022

Inventions

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“…For the period from 2010 to 2017, for example, the consumption of electricity per capita in the Kingdom rose by 20 percent, compared to the United States, in which the consumption of electricity per capita declined by more than 5.9 percent (IEA, 2022a), (IEA, 2022b). Based on the current energy policy and rapid growth in population and economy, the peak demand in Saudi Arabia is expected to keep increasing and reach approximately 84 GW by 2030 and 103 GW by 2040 (Al Harbi and Csala, 2019). Accordingly, at the current pace of using current sources for power generation, an additional 12 percent of oil barrels should be burned to meet the rapid growth of peak demand in 2030, which will be doubled every ten years.…”

Section: Saudi Arabia's Energy Strategy and Associated Challengesmentioning

confidence: 99%

Electrical energy future of Saudi Arabia: Challenges and opportunities

Aldhubaib

2022

Front. Energy Res.

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The economy of Saudi Arabia is primarily oil-based, and the energy system is heavily dependent on fossil fuel sources. Electrical demand in Saudi Arabia has been overgrowing due to the high rates of both population and economy. The real problem is that most of this demand has been met by polluting sources, which in turn causes severe economic and environmental challenges. Despite the abundant amount of clean and freely available renewable sources, the practice of benefiting from these sources is minimal and modest. Therefore, the country has launched a promising vision, one pillar of which is diversifying energy sources and reducing dependence on oil. Since Saudi Arabia is located within the equatorial Sun Belt area, the country is a candidate for leading the World’s renewable energy industry, particularly solar energy. This paper discusses the current energy policy in Saudi Arabia, the associated main energy-related challenges and promising opportunities, and the efforts and actions taken by the country’s policymakers to address these challenges and to take advantage of available opportunities–especially those related to electrical energy–to assure continued future prosperity for subsequent generations.

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Future of Residential Electricity Demand in Saudi Arabia and the Role of Energy Efficiency in 2060's Net Zero Pledge

Aldubyan

2024

Preprint

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Saudi Arabia's Electricity: Energy Supply and Demand Future Challenges

Cited by 7 publications

References 6 publications

A Seasonal Autoregressive Integrated Moving Average with Exogenous Factors (SARIMAX) Forecasting Model-Based Time Series Approach

A Seasonal Autoregressive Integrated Moving Average with Exogenous Factors (SARIMAX) Forecasting Model-Based Time Series Approach

Electrical energy future of Saudi Arabia: Challenges and opportunities

Future of Residential Electricity Demand in Saudi Arabia and the Role of Energy Efficiency in 2060's Net Zero Pledge

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