DIFFERENTIAL PRIVACY DYNAMIC ECONOMIC DISPATCH WITH DISTRIBUTED CONSENSUS BASED ON ADMM

. This paper addresses the economic dispatch problem with privacy protection in a smart grid. The smart grid consists of traditional generators (GTs), wind turbines (WTs), and photovoltaic stations (PVs). The objective is to meet energy demand and minimize the total cost while ensuring the security of users' data. To achieve this, an optimization method based on the alternating direction method of multipliers (ADMM) is proposed. Firstly, the cost functions for GTs, PVs, and WTs are established, taking account of both static and dynamic constraints of distributed energies. Next, the algorithm is utilized to solve the optimization problems, and the Newton method is applied to finding the zero points of functions that cannot be easily separated into variables. Additionally, differential privacy is employed to protect the cost functions from potential attackers attempting to steal them. Finally, the effectiveness of the optimization method and the confidentiality of the system are verified through simulations.