STATE ESTIMATION IN POWER SYSTEMS BASED ON A MATHEMATICAL PROGRAMMING APPROACH

This chapter revisits the state estimation problem in power system and develops a direct approach of a mathematical programming solution for the most relevant estimators. Bearing in mind that recent progress in nonlinear and mixed integer nonlinear optimization techniques, the aims of the chapter are to formulate the most common state estimation algorithms as mathematical programming problems and to compare them from the numerical and computational perspectives. From the optimization perspective, the chapter provides formulations as mathematical programming problems for the most common state estimation procedures, comparing them from both the numerical and computational perspectives. State of the art of current available nonlinear optimization solvers, recent advances in computational speed, and emerging multi‐core Hyper‐Threading Technology processors allow the estimation problem to be solved directly. Two main advantages can be led by proceeding in this manner: alternative estimators can be easily used, and decomposition techniques can be applied, resulting in decentralized estimators.