  With the emerging of smart grid techniques, cyber attackers may be able to
gain access to critical energy infrastructure data and strategic market
participants may be able to identify offer prices of their rivals. This paper
discusses a privacy-preserving economic dispatch approach in competitive
electricity market, in which individual generation companies (GENCOs) and load
serving entities (LSEs) can mask their actual bidding information and physical
data by multiplying with random numbers before submitting to Independent System
Operators (ISOs) and Regional Transmission Owners (RTOs). This would avoid
potential information leakage of critical energy infrastructure and financial
data of market participants. The optimal solution to the original ED problem,
including optimal dispatches of generators and loads and locational marginal
prices (LMPs), can be retrieved from the optimal solution of the proposed
privacy-preserving ED approach. Numerical case studies show the effectiveness
of the proposed approach for protecting private information of individual
market participants while guaranteeing the same optimal ED solution.
Computation and communication costs of the proposed privacy-preserving ED
approach and the original ED are also compared in case studies.
