Privacy-Preserving Distributed Optimization Scheme for Battery Swapping and Charging System With Homomorphic Encryption to Protect Wireless Communications

The proliferation of electric vehicles (EVs) has spurred a growing demand for efficient battery exchange and charging services, making the battery swapping-charging system (BSCS) an attractive solution.The various subsystems of the BSCS exchange data in real-time through wireless communication. However, due to the openness of wireless communication, data can be easily intercepted and tampered with during transmission, which may lead to the leakage of sensitive information. To address this, we introduce a privacy-preserving distributed optimization algorithm, leveraging homomorphic encryption and multi-party secure computing in the BSCS context. Initially, we formulate the operation management problem of BSCS problem as a constrained mixed integer programming (MIP) and employ the alternating direction method of multipliers (ADMM) for optimal resolution. Subsequently, we integrate ADMM with the Paillier cryptosystem for privacy protection. Empirical validation substantiates the algorithm security and convergence, ensuring that adversaries cannot deduce private information. Notably, the proposed algorithm yields a solution closely resembling the centralized solution, with a superior convergence rate compared to alternative methods.