This study presents a novel three-tiered energy bidding framework aimed at enhancing the resilience and economic competitiveness of electrical grids before, during, and after natural disasters. Traditional methods often focus on mitigating load curtailments during extreme events, but our proactive approach utilizes Binary Integer Linear Programming optimization to maximize customer satisfaction by securing desired bid values at lower rates based on CIBIL Score amidst natural calamities. The framework integrates three layers: a physical layer equipped with smart meter data collection, a middle layer facilitating power allocation using MATLAB optimization techniques, and a security layer employing distributed ledger technology like blockchain to ensure data integrity and system security. By integrating these layers, our approach offers a comprehensive solution to optimize system performance and customer satisfaction during adverse conditions, thereby strengthening grid resilience and enhancing economic competitiveness. This proactive strategy not only mitigates the impact of natural disasters on the grid but also fosters a more resilient and economically viable energy ecosystem, contributing to sustainable development and long-term resilience in the face of climatic upheavals.