A framework for enhancement of power system dynamic behavior

Grid operation under market competition forces systems closer to their instability boundaries, and operating decisions must be based on accurate online system identifications. This paper presents a new framework for online power system dynamic stability enhancement with a new rescheduling market construction. The approach is to solve the online transient and oscillatory stability constrained economic power system operation by a mixture of a modified particle swarm optimization (PSO) and artificial neural network (ANN). The problem is formulated as nonlinear constrained optimization problem and PSO has been used as optimization tool to guarantee searching the optimal economic solution within the available hyperspace reducing the time consumed in the computations by using ANN to assess power system dynamic stability. The rescheduling process based on the generation companies (GENCOs)/consumer´s bids is used as a remedial action to maintain system operation away from the limits of system stability. The goal of the approach is to minimize the opportunity cost payments for GENCOs/consumers backed down in generation/load and the additional cost for GENCOs/consumers increased their generation/load in order to enhance system dynamic stability. The critical clearing time (CCT) at the critical contingency is considered as an index for transient stability. System minimum damping of oscillation (MDO) is considered as indicator for oscillatory stability. The proposed framework is examined on a 66-bus test system.