With the power system evolving from passive to a more active system there is an incorporation of information and communication infrastructures in the system. The measurement data are more prone to tampering from attackers for mala fide intentions. Therefore, security and reliability of distribution have become major concerns. State estimation (SE), being the core function of the energy/distribution management system (EMS/DMS), has become necessary in order to operate the system efficiently and in a controlled manner.

Although SE is a well-known task in transmission systems, it is usually not a common task in unbalanced distribution systems due to the difference in design and operation philosophy. This thesis addresses these issues and investigates the distribution system state estimation with unbalanced full three-phase modelling. The formulation, based on weighted least squares estimation, is extended to include the open/closed switches as equality constraints.

This research then explores the vulnerabilities of the state estimation problem against attacks associated with leverage measurements. Detecting gross error particularly for leverage measurements have been found to be difficult due to low residuals. The thesis presents and discusses the suitability of externally studentized residuals compared to traditional residual techniques.

Additionally, the masking/swamping phenomenon associated with multiple leverages makes the identification of gross error even more difficult. This thesis proposes a robust method of identifying the high leverages and then detecting gross error when the leverage measurements are compromised. All algorithms are validated in different IEEE test systems.