Multi-Objective Optimal Power Sharing Model for Futuristic SAARC Super Smart Grids

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Abstract

One-fourth population of the world lives in South Asia. The electricity generation for this population consumes the substantial fossil fuels, resulting in the significant emissions of harmful gases in the global environment. To protect the natural environment, South Asian Association for Regional Cooperation (SAARC) has planned a super smart grid for the power sharing between South Asian countries through the integration of the renewable energy resources (RERs). However, the capability of these countries to construct such a mega power grid is unclear due to the unavailability of proper strategic analysis, lack of information about RERs potential, and the lack of decision making models. This paper analyzes the existing power grids in SAARC countries, identifies their electricity generation potential, and develops an integer linear programming model based on the power generation cost, CO2 emissions, and disruption risk. This study solves the proposed model using goal programming methods. The results exhibited that the SAARC countries have the capability to share the sustainable super smart grids through the substantial integration of RERs. For instance, the model solution based on 100% renewable power (i.e. Case 5) exhibited 36% cost savings, 86% CO2 emission reduction, and 39% risk reduction compared with corresponding non-renewable power based model solution (i.e. Case 1). In addition, this study performs the cost-benefit analysis for the existing and proposed power systems of SAARC countries. The results provide the various insights to policy makers and practitioners for the strategic decision making related to the SAARC super smart grid. In addition, the methodology of this paper can be adopted for other super smart grids around the world.

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CITATION STYLE

APA

Liaqat, M., Ghadi, Y., & Adnan, M. (2022). Multi-Objective Optimal Power Sharing Model for Futuristic SAARC Super Smart Grids. IEEE Access, 10, 328–351. https://doi.org/10.1109/ACCESS.2021.3137592

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