Decentralized PMU-Assisted Power System State Estimation With Reduced Interarea Communication

Abstract

This paper presents a decentralized approach to multi-area power system state estimation using a combination of conventional measurement devices and newer phasor measurement units (PMU). We employ a reduced-order approach to state estimation, wherein the PMU observable and unobservable components of the state vector are estimated separately in each control area. The estimation problem is solved by exchanging information through an improved gossip-based protocol which takes into account the weak measurement coupling between control areas. A detailed analysis of the proposed protocol reveals that the amount of information exchange is always less than the naïve gossip based scheme. We show through simulations on the IEEE 118-bus test system that, in practice, the gossip iterations converge in one iteration regardless of the number of control areas. Our simulations also show that the marginal information exchange is also considerably lower when using the proposed method.

A Privacy-Preserving State Estimation Scheme for Smart Grids

“…Considering a different privacy scenario in a transmission system, articles [10], [19], [20], [21] dealt with the threats of privacy leakage when state estimation is collaboratively processed between k sub-transmission systems. Existing approaches to decentralized state estimation partition the measurement vector such that each local area-based player attempts to perform local state estimation with measurements taken within its area.…”

“…For a specific problem of distributed linear state estimation, [10] presented a trade-off between estimation fidelity and leakage of private state data as a result of sharing data in a two-agent network model. In [19], [20] a privacy-preserving distributed state estimation with phasor measurement units was investigated but the scheme still violates the privacy of sub-systems due to the exchange of information related to measurements on tielines linking neighbouring area. To securely contribute private information for a privacy-preserving hierarchical state estimation, [21] proposed a privacy-preserving distributed state estimation framework in which a cloud-based highlevel control centre coordinates low-level control centres to compute the estimated states.…”

Research Needs for Realization of Zero-Carbon Power Grids with Selected Case Studies

“…Most recent studies (e.g., [70][71][72]) have focused on the sequential approach; PMU estimators first obtain and deliver SE results to SCADA estimators, or vice versa. For example, in [70,71], the PMU estimators first obtained the SE models and then provided them to the SCADA estimators, along with information on the boundary states and measurement couplings. The SCADA estimators then used linear SE models to reduce the sizes and complexities of non-linear SE problems.…”