Static Compensators (STATCOMs) in Power Systems

Abstract

Short-term voltage stability is an increasing concern in today’s power systems given growing penetration of induction motors. The instability can lead to catastrophic consequences such as cascading failures and/or wide-spread blackouts. STATCOMs are able to provide rapid and dynamic reactive power (VAr) support into the system and therefore improve system’s short-term voltage performance following a large disturbance. Importantly, the sizing and locating of the STATCOM integration determine how much the short-term voltage performance can be improved. This chapter presents a novel systematic method for optimal placement of STATCOMs against short-term voltage instability. The problem is formulated as a multi-objective optimization model minimizing two conflicting objectives: (1) total investment cost and (2) expected unacceptable short-term voltage performance subject to a set of probable contingencies. Indices for quantifying short-term voltage stability and the related risk level are proposed for problem modeling. Candidate buses for STATCOM installations are analytically selected based on trajectory sensitivity technique. Load dynamics are fully considered using a composite load model comprising induction motor and other typical components. For the proposed model, rather than a single solution, a set of trade-off solutions called Pareto optimal solutions can be obtained, and the decision-maker may select one from them depending on practical needs. A relatively new and superior multiobjective evolutionary algorithm called multi-objective evolutionary algorithm based on decomposition (MOEA/D) is introduced and employed to find the Pareto optimal solutions to the model. The proposed method is verified on the New England 10-machine 39-bus system using industry-grade simulation tool and system models. Simulation results have validated the effectiveness of the proposed method. The method can be practically applied to provide decision-support for STATCOM installations.