Projecting Saudi Sectoral Electricity Demand in 2030 Using a Computable General Equilibrium Model

Soummane, Salaheddine; Ghersi, Frédéric

doi:10.30573/ks--2021-dp12

Cited by 3 publications

(2 citation statements)

References 29 publications

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“…The per capita electricity consumption in Saudi Arabia is estimated to be three times compared of the world average [2]. According to a recent study in [3], the peak demand in Saudi Arabia is predicted to reach 365.4 TW by 2030. Hence, the Saudi Electricity Company (SEC) aims to meet this future load by adding new generation capacities [4].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Weibull Distribution Parameters for Wind Speed Characteristics Using Neural Network Algorithm

AlRashidi¹

2023

Computers, Materials &Amp; Continua

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Harvesting the power coming from the wind provides a green and environmentally friendly approach to producing electricity. To facilitate the ongoing advancement in wind energy applications, deep knowledge about wind regime behavior is essential. Wind speed is typically characterized by a statistical distribution, and the two-parameters Weibull distribution has shown its ability to represent wind speeds worldwide. Estimation of Weibull parameters, namely scale (c) and shape (k) parameters, is vital to describe the observed wind speeds data accurately. Yet, it is still a challenging task. Several numerical estimation approaches have been used by researchers to obtain c and k. However, utilizing such methods to characterize wind speeds may lead to unsatisfactory accuracy. Therefore, this study aims to investigate the performance of the metaheuristic optimization algorithm, Neural Network Algorithm (NNA), in obtaining Weibull parameters and comparing its performance with five numerical estimation approaches. In carrying out the study, the wind characteristics of three sites in Saudi Arabia, namely Hafer Al Batin, Riyadh, and Sharurah, are analyzed. Results exhibit that NNA has high accuracy fitting results compared to the numerical estimation methods. The NNA demonstrates its efficiency in optimizing Weibull parameters at all the considered sites with correlations exceeding 98.54.

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Section: Introductionmentioning

confidence: 99%

Estimation of Weibull Distribution Parameters for Wind Speed Characteristics Using Neural Network Algorithm

AlRashidi¹

2023

Computers, Materials &Amp; Continua

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“…Soummane and Ghersi used a prediction and analysis model for power average calculation. By analyzing the demand of di erent power parts, the model results of the whole region are obtained [3]. Hirose used a base-extended variable coefficient model to forecast short-and medium-term electricity demand problems [4].…”

Section: Introductionmentioning

confidence: 99%

Evaluation and Analysis of Electric Power in China Based on the ARMA Model

2022

Mathematical Problems in Engineering

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With the rapid development of China’s economy, power demand has been closely linked with economic development in order to analyze and predict the future power situation in China. Based on the historical data of China’s electricity consumption, this paper analyzes the data characteristics of China’s electricity consumption by using Eviews software. The long-term trend of power consumption sequence is eliminated by fitting the regression curve, and then the residual sequence is analyzed and identified according to the relevant theory of time series. Using the data of China’s power demand from 2004 to 2019, the ARMA time series model is used to analyze China’s future power situation finally according to the test statistics of the model. Finally, the exponential regression ARMA model is selected to predict China’s electricity consumption. The index regression analysis method extracts the long-term characteristic information of the sequence, which is conducive to the stability processing and empirical analysis of long-term prediction. The result predicts China’s power demand in 2020 more accurately, which can provide a reference for the future productivity layout of China’s power.

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Energy Efficiency: The Overlooked Energy Resource

Alqahtani¹,

Farooq²,

Almutairi³

2022

Alternative Energies and Efficiency Evaluation

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The objective of this chapter is to draw the attention of government policy makers internationally to a strategy for alleviating global warming through proven cost-effective energy efficiency measures. The Saudi Arabian government has embraced the approach with demonstrable success over the past 20 years, with rates of return on investments averaging more than 25%. Even though Saudi Aramco is the National Oil and Gas company, the company takes the threat of climate change to the world’s economies very seriously and initiated programs for, systematically and responsibly, transition to less-polluting energy sources. Primarily, the chapter will define the supply chain components of Saudi Arabia’s energy sector and explain the existing conditions and efficiencies of each of its components. It analyzes the existing energy management framework and its achievements, as well as its current and forthcoming commitments, status, and updates. It will also explain the vital equipment, systems, and processes in the supply chain, with possible energy efficiency improvement gaps based on existing literature/Energy Assessment Reports conducted by Saudi Aramco professionals in numerous industrial facilities. The chapter will pinpoint the highest achievable efficiencies areas in major systems, processes, or equipment and discusses its impact on the primary energy fuels and green house gas (GHG) emission reduction.

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Projecting Saudi Sectoral Electricity Demand in 2030 Using a Computable General Equilibrium Model

Cited by 3 publications

References 29 publications

Estimation of Weibull Distribution Parameters for Wind Speed Characteristics Using Neural Network Algorithm

Estimation of Weibull Distribution Parameters for Wind Speed Characteristics Using Neural Network Algorithm

Evaluation and Analysis of Electric Power in China Based on the ARMA Model

Energy Efficiency: The Overlooked Energy Resource

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