The Effectiveness of Hybrid Micro-Grid System in Selected Locations in Saudi Arabia

Abstract

The need for socio-economic development, industrialisation, and lifestyle advancement pro- pels rising energy demand globally. The majority of energy needs are met by fossil fuels (coal, oil, and gas), which emit significant greenhouse gas emissions, degrading the environment and accelerating the global climate impact. The greenhouse gas emission and its impact are more prominent in high energy-consuming nations like the Kingdom of Saudi Arabia, where most power is generated by fossil fuels. Although the country’s 35 million population is largely spread in major cities and towns (83%), a significant population (17%) still lives in rural and remote areas across the vast country (2.15 million square km). The power needs for most of these populations are met not by grid-connected power but by locally generated power (mainly diesel fuel). As a responsible nation, the Kingdom of Saudi Arabia has committed to the Paris Climate Agreement and adopted a plan to reduce fossil fuel use for power by gradually increasing renewable power generation, especially in remote and rural areas. The geographic location of Saudi Arabia offers the opportunity to enhance both solar and wind energy. However, the distribution of renewable energy (solar and wind) is not uniform throughout the country. Hence, the primary objective of this study is to explore the opportunity to harness renewable energy along with other types of energy, emphasising CO2 reduction and cost optimisation. The study is envisioned to develop a mathematical model of a hybrid power generation system incorporating solar, wind, and diesel energy for rural areas. This research aims to study and formulate accurate mathematical models to determine the hybrid microgrid system response for renewable energy location and allocation in rural and urban areas. A mathematical model is presented to design hybrid microgrid system based on the positioning of renewable energy resources besides the traditional resources to plan for the entire area. This new model takes into consideration demand needs and limited resources. The objective of the developed model is to minimise the emission and cost of the system while the demand is covered by using renewable energy. To quantify the power needs of the selected population, two areas along with the popu- lation—one in a rural area (Al-Gahah) and the other in an urban area (Jeddah)—have been selected. Data on household power usage have been obtained and analysed. Wind character- istics and solar irradiation data from the selected areas have also been collected. Based on collected data, the hybrid power generation mathematical model has been developed using five scenarios: a) diesel only, b) diesel and solar, c) diesel and wind, and d) diesel, solar, and wind. Initially, commercial software (HOMER) was used to predict optimal power generation for four scenarios. However, the optimised prediction did not fully address the need for local population requirements, especially the CO2 and cost together. To overcome these limita- tions, the mathematical power generation prediction model has been developed, validated by first an Excel-based model and later a Python-based model. The model validated by the case study data across four distinct scenarios, illustrate the robustness and efficacy of the model. It fulfils all constraints, determining the system configuration that achieves the de- sired function while complying with environmental and financial restrictions. The developed model is capable of predicting optimised power generation incorporating both cost and CO2 emissions. It can also be used to determine optimal power generation based only on cost or CO2 emissions. The model can be used to develop a hybrid power generation system using solar, wind, and other energy for areas in Saudi Arabia and elsewhere. The model can be used to enhance strategic, tactical, and operational planning for hybrid microgrid systems for achieving a more reliable power supply, a cleaner environment through diminished CO2 emis- sions, and reduced operational expenses for diverse microgrid and mini-grid power generation in Saudi Arabia and elsewhere.