Assessing Renewable Energy Adoption to Achieve Sustainable Development Goals in Ha’il Region

Abstract

Today’s environmental issues are among the primary themes that researchers explore in their search for practical solutions to achieve the Sustainable Development Goals (SDGs), such as reducing carbon emissions and promoting sustainable practices. Renewable energy is crucial to overcoming future challenges, causing many countries to accelerate their adoption at various levels. In this context, the impact of renewable energy adoption on achieving the Sustainable Development Goals in the Ha’il region has been evaluated. Specifically, two techniques are employed. The first technique is an empirical model based on the Vector Error Correction Model (VECM), which identifies the SDGs related to renewable energy in achieving SDGH. Only three SDGs (SDG7, SDG12, and SDG13) were found to influence SDGH significantly. The second technique uses deep learning, specifically LSTM networks, to forecast SDGH behavior over a ten-year period about the three selected SDGs. The results indicate that these three SDGs play a crucial role in sustainable development in the Ha’il region. Therefore, this research produces strategic recommendations to optimize the adoption of renewable energy in the Ha’il region. These findings provide policymakers with a data-driven framework to enhance strategies, utilize resources more efficiently, and promote broader sustainability initiatives.