Optimal Sizing Grid-Connected Hybrid PV/Generator/Battery Systems Following the Prediction of CO2 Emission and Electricity Consumption by Machine Learning Methods (MLP and SVR): Aseer, Tabuk, and Eastern Region, Saudi Arabia

Abstract

Researchers’ concentration has been on hybrid systems that can fulfill economic and environmental goals in recent years. In this study, first, the prediction of CO2 emission and electricity consumption of Saudi Arabia by 2040 is made by employing multi-layer perceptron (MLP) and support vector regression (SVR) methods to see the rate of CO2 emission and electricity consumption. In this regard, the most important parameters such as gross domestic product (GDP), population, oil consumption, natural gas consumption, and renewable consumption are considered. Estimating CO2 emission by MLP and electricity consumption by SVR showed 815 Mt/year and 475 TWh/year, respectively, where R2 for MLP and SVR was 0.99. Prediction results showed a 31% and 39% increase in CO2 emission and electricity consumption by 2040 compared to 2020. Second, the optimum combination of components for supplying demand load and desalination load in residential usages are found where 0% capacity shortage, 20–60$/t penalty for CO2 emission, sell back to the grid, and both fixed and random grid outages are considered. Load demands were considered under two winter and non-winter times so that 4,266, 2,346, and 3,300 kWh/day for Aseer, Tabuk, and the Eastern Region were shown, respectively. Results show that 0.12, 0.11, and 0.12 (kW (PV))/(kWh/day(load)) and 0.1, 0.08, and 0.08 (kW(Bat))/(kWh/day(load)) are required under the assumption of this study for Aseer, Tabuk, and the Eastern Region, respectively. Also, COEs for the proposed systems are 0.0934, 0.0915, and 0.0910 $/kWh for Aseer, Tabuk, and the Eastern Region, respectively. Also, it was found that renewable fractions (RFs) between 46% and 48% for all of the case studies could have rational COE and NPCs and fulfill the increasing rate of CO2 emission and electricity consumption. Finally, sensitivity analysis on grid CO2 emission and its penalty, load and solar Global Horizontal Irradiance (GHI), PV, and battery prices showed 45%–55%, 42%–52%, and 43%–49% RFs for Aseer, Tabuk, and the Eastern Region, respectively.

Smart Grid: Leading International Experience of Marketing and its Contribution to Sustainable and Environmental Development of Energy Economy

“…In contrast to Albogamy et al (2022), Almutairi et al (2022), Liu et al (2022), Saxena et al (2022), Zaidan et al (2022), it was found that Smart Grid mainly depends on government governance, which includes both infrastructure support, and regulation of the energy economy. The role of corporate governance is secondary.…”

“…The publications of Albogamy et al (2022), Almutairi et al (2022), Liu et al (2022), Saxena et al (2022), Zaidan et al (2022) suggest the functioning and development of Smart Grid based on corporate governance with a secondary role of the state. Smart Grid is interpreted as a high-tech innovation of energy companies.…”

Performance Analysis Using Multi-Year Parameters for a Grid-Connected Wind Power System

“…The second category is when consumption is less 1-6000 kWh, with the rate charge of at 0.048 USD/kWh. Based on these categories, these new rates were used to schedule the fixed prices at various times during the day as explained in [35]. Figure 6 shows the considered grid-connected system in the research.…”