A taxonomy of multi-area state estimation methods

Abstract

This paper presents a critical review of the state of the art in multi-area state estimation (MASE) methods, which are currently gaining renewed interest due to their capability of properly tracking multi-TSO transactions and accommodating highly redundant information systems. Based on several classification criteria, a taxonomy of MASE methods is first proposed. Two main categories, namely two-step or hierarchical versus decentralized, are identified. Then, for each class of methods, the resulting model structure and area interactions are discussed and a brief presentation is made of a selected subset of references.