The distributed energy management (DEM) problem of smart grids is devoted to achieving optimal energy dispatch and allocation to ensure social welfare maximization. It can be modelled as a distributed optimization problem with physical constraints, whose solution depends on data sharing between smart devices. The exchange of information creates a potential risk for eavesdroppers to intercept and access private data. To avoid privacy leakages, a privacy-preserving optimization strategy via output masks in a consensus framework is proposed to realize social welfare maximization of energy management, where power demand relies on the parameters of the demand sides. Theoretical analysis discloses that eavesdroppers are unable to accurately infer private information of the generators/demand loads. Furthermore, both the convergence and optimality of the proposed strategy are discussed by means of the matrix perturbation theory and the famous KKT optimality condition. Finally, the effectiveness of the proposed strategy for solving the DEM problem is confirmed by the simulation experiments.

Economic dispatch problems (EDPs), as a basic issue of smart grids, have appealed to a wide range of research interests owing to the expansion of network scales and the increase of system complexity. The flexibility of economic dispatch algorithms puts forward urgent requirements of distributed optimization methods dependent on information exchanges, which may lead to the leakage of private information. To solve this problem, a privacy-preserving strategy in a distributed paradigm is proposed by adding artificial sequences to the transmitted multi-step gradient information. In light of such a strategy, a new distributed privacy-preserving optimization approach in light of multi-step gradient information is developed to handle the addressed EDPs. When introduced parameter sequences satisfy suitable conditions, both the convergence to the optimal solution and the privacy of sensitive parameters in the generator cost are effectively guaranteed. Finally, an illustrative simulation is specially offered to verify the validity of the developed strategy.