Confidential distributed optimal scheduling method and system, computer equipment and medium

Abstract

The invention provides a confidential distributed optimal scheduling method and system, computer equipment and a medium. The method comprises the following steps: constructing a single-target optimal scheduling model according to actual topology of a smart power grid; converting the single-target optimal scheduling model into a corresponding Lagrange dual model; and according to a subgradient iteration rule, solving the Lagrange duality model to obtain an optimal scheduling solution of the smart power grid. According to the method, noise meeting certain conditions is added to main body node privacy information of communication transmission in combination with the subgradient iteration rule, so that the defects that in the prior art, optimality is easily influenced by privacy levels, all security attacks cannot be handled, the communication efficiency is low, and the cost is high are solved, the optimal scheduling problem and the information security problem of generator sets in a modern smart power grid are efficiently solved, and an effective calculation and analysis means is provided for safe and reliable operation of the smart power grid.

Description

technical field [0001] The invention relates to the technical field of power grid economic scheduling optimization methods, in particular to a noise-based confidential distributed optimal scheduling method, system, computer equipment and storage media. Background technique [0002] Affected by economic and environmental factors such as energy crisis, distributed energy resources, and communication networks, modern energy networks are mostly dynamic and distributed, and this trend inevitably leads to technological and technological differences in energy management and smart grid operation. theoretical challenge. In recent years, with the continuous development of large-scale new energy sources and demand-side response, economic dispatch optimization methods have received widespread attention as an important basic issue of smart grids. In new power systems, a large number of new energy sources and demand-side response resources, It will seriously increase the diversity of pow...

AI Technical Summary

Problems solved by technology

Although some scholars have proposed privacy protection methods applied in distributed optimization, such as the method of introducing classic differential privacy algorithm, the method of observability design and the method of combining partial homomorphic encryption, etc., although it can achieve privacy protection to a certain extent. protection, but each has its own defects. For example, the optimality of the solution using the method of introducing the classic differential privacy algorithm is inevitably affected by the trade-off between optimality and privacy level; the method of observability design cannot deal with information eavesdropping in the communication network Or; each iteration of the method combined with partial homomorphic encryption requires the transmission of information based on partial homomorphic encryption, which takes more time than direct information transmission and is only applicable to undirected communication networks

Images