4.6 Article

DisEHPPC: Enabling Heterogeneous Privacy-Preserving Consensus-Based Scheme for Economic Dispatch in Smart Grids

Journal

IEEE TRANSACTIONS ON CYBERNETICS
Volume 52, Issue 6, Pages 5124-5135

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2020.3027572

Keywords

Demand response (DR)-based framework; distributed and effective heterogeneous privacy preserving consensus (DisEHPPC) scheme; economic dispatch (ED); Kullback-Leibler (KL) privacy; privacy-preserving incremental cost consensus (PPICC) algorithm

Funding

  1. Science and Technology Research Program of Chongqing Municipal Education Commission [KJQN202001120, KJQN201901101]
  2. Scientific Research Foundation of Chongqing University of Technology [2019ZD104]
  3. Qatar National Research Fund [NPRP12C-0814-190012]

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This article proposes a two-phase distributed and effective heterogeneous privacy-preserving consensus-based economic dispatch scheme for smart grids. The scheme protects the privacy of consumers and generators through the use of differential privacy and incremental cost consensus-based algorithm. Theoretical analysis and numerical experiments confirm the correctness and effectiveness of the proposed scheme.
These days, the increasing incremental cost consensus-based algorithms are designed to tackle the economic dispatch (ED) problem in smart grids (SGs). However, one principal obstruction lies in privacy disclosure for generators and consumers in electricity activities between supply and demand sides, which may bring great losses to them. Hence, it is extraordinarily essential to design effective privacy-preserving approaches for ED problems. In this article, we propose a two-phase distributed and effective heterogeneous privacy-preserving consensus-based (DisEHPPC) ED scheme, where a demand response (DR)-based framework is constructed, including a DR server, data manager, and a set of local controllers. The first phase is that Kullback-Leibler (KL) privacy is guaranteed for the privacy of consumers' demand by the differential privacy method. The second phase is that (epsilon, delta)-privacy is, respectively, achieved for the generation energy of generators and the sensitivity of electricity consumption to electricity price by designing the privacy-preserving incremental cost consensus-based (PPICC) algorithm. Meanwhile, the proposed PPICC algorithm tackles the formulated ED problem. Subsequently, we further carry out the detailed theoretical analysis on its convergence, optimality of final solution, and privacy degree. It is found that the optimal solution for the ED problem and the privacy preservation of both supply and demand sides can be guaranteed simultaneously. By evaluation of a numerical experiment, the correctness and effectiveness of the DisEHPPC scheme are confirmed.

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