Abstract
Bahrain was the first Gulf Cooperation Country (GCC) to discover oil. Since then, oil has become the keystone of the country's economic development, reflecting on all sectors, particularly power generation. This underlines the difficulty of shifting from well-established oil-based power production to renewable energy. Nevertheless, a significant milestone was achieved in January 2017, when the Sustainable Energy Unit (SEU) launched the National Renewable Energy Action Plan (NREAP). The plan sets the roadmap for identifying the most appropriate renewable resources for Bahrain and its best technologies. Special attention should be paid to Sustainable Generation Expansion Planning (GEP) for Bahrain's electrical system with renewables. This is because Bahrain's government is committed to the Sustainable Development Goals (SDG) and has incorporated them into its action plan since 2015.
The sustainability theme in the energy system interacts with different research areas, and it requires a multidimensional approach to cover its impact on the national grid, environment, economy and other sectors. This study aims to assist Bahrain's policymakers in evaluating the renewable energy technologies for sustainable growth of the generation sector by suggesting an Intelligent Decision Support System (IDSS) based on a combination of the Analytical Hierarchy Process (AHP) and Artificial Neural Networks (ANN). After evaluating the derived indicators from seventy-three studies by experts and applying the selection principles, fifteen indicators are selected for constructing the AHP model. The AHP model outcomes revealed that wind turbines are the most appropriate technology for Bahrain. Then, the ANN model is structured based on the generated cases from the AHP model. The Levenberg–Marquardt algorithm is used for processing the data with a hyper tangent sigmoid and a linear function for the hidden layer and output layer of the ANN model. The scenario analysis demonstrates that the IDSS can be used with confidence to explore the effect of each criterion and sub-criterion on the sustainable growth of the electrical grid in Bahrain.