Unmanned Aerial Vehicles (UAVs) are increasingly integrated into Internet of Things (IoT) ecosystems, serving critical roles across industries, particularly in smart grid inspection. However, UAVs inevitably collect and store sensitive data during critical operations, including inspection images with GPS information, route files, and point cloud data. Once leaked, these data pose serious threats to corporate economic security and national infrastructure. Traditional encryption methods often change data format and length, creating compatibility challenges with existing database systems and introducing substantial integration costs. To address this challenge, we propose an optimized Format Preserving Encryption (FPE) method for encrypting structured UAV sensitive data. We apply the FF3-1 algorithm with several optimization methods, including pre-generation of tweaks and all round keys, to enhance encryption performance. Given geographic coordinate data characteristics, we implement a geographic area limits strategy to preserve neighboring coordinate characteristics. Comprehensive experimental evaluations demonstrate our method’s encryption effectiveness, verify the geographic area limits strategy’s efficacy, and analyze performance characteristics. Results indicate that our proposed method effectively protects sensitive data from UAV without changing data format while achieving significant performance improvements, providing a practical solution for smart grid UAV data security.