Abstract:
Hybrid renewable energy systems are often used for rural electrification as an economic-eco-friendly choice. This study explores techno-economic, environmental, energy, sensitivity, social, as well as breakeven analysis and investigates how these systems can be used to achieve sustainable development goals. On the basis of load profile, geographical locations and climatic conditions, the system is modelled, simulated, and optimized. The optimal configuration and costs for the system components are obtained. The geospatial analysis approach is used for the identification of un-electrified remote areas. Pakistan has a large renewable potential across all its regions; Northern areas have great potential for Hydro, Punjab has potential for PV, and for Sindh and Balochistan, combined PV with wind is the most optimal solution for electrification. PV, hydro with battery is suitable for Gilgit Baltistan, with the least NPC and LCOE among all the regions.
In order to improve the overall efficiency of energy projects, customized business models are being proposed. In the proposed system, it is estimated that the deployment of RE-based MGs may reduce GHG emissions by up to 99%. The social impact assessment investigates how the deployment of energy projects will help the local economy and strengthen GDP. The breakeven analysis of the proposed energy system is also investigated in comparison to the cost of the grid extension scenario. Robust analysis is performed to ensure the technical reliability of the proposed system. Sensitivity analysis investigates uncertain parameter effects across NPC and LCOE. So, it is inferred from the study that the favourable way of rural electrification is the deployment of HRES-based MG’s. Before proposing massive transmission and distribution infrastructure investments for remote Pakistani areas, electricity planners must examine MGs. MG designs should be affordable in each geographical region to achieve a win-win situation for all stakeholders. Pakistan needs a robust policy and regulatory framework to scale up MG deployment. Finally, a statement is made about further research that will be done to develop this area of research.
