This paper studies the energy efficiency optimization of blockchain consensus algorithms in regional economic scenarios, proposes an optimization algorithm OptiCon based on dynamic resource allocation, and verifies its effectiveness through theoretical modeling and experiments. The study constructs a theoretical framework and evaluation model for energy efficiency optimization, and analyzes the shortcomings of traditional consensus algorithms PoW and PoS in energy consumption and performance. Experimental results show that OptiCon reduces unit transaction energy consumption by 53% and 26% compared with PoW and PoS, respectively, increases transaction throughput by 79% and 20%, reduces confirmation delay from 11.2 s and 7.8 s to 5.9 s, and shows strong adaptability and stability in supply chain finance and cross-border trade scenarios. The study confirms the important role of dynamic resource allocation strategies in improving the energy efficiency of blockchain systems, and provides theoretical and practical support for their sustainable application in regional economy.