Dynamic stability and network constrained optimal spinning reserve allocation

This paper presents an integrated work for regulation reserve allocation considering dynamic stability and load variations. In deregulated power system, participants compete to maximize their surplus without considering system stability margin, which forces the power system to operate closer to their instability boundaries. Suitable spinning reserve amount and allocation to meet additional load demand and the corresponding power flows through transmission lines at acceptable stability margin is an important aspect for a secure power system operation following a credible contingency. The geographical localization and coordination of the available amount of spinning reserve used for regulation must be based on accurate online system state to cover the uncertainty associated with electric demand. The target is to minimize the cost of spinning reserve considering system operational constraints independent on the energy market auctions. This target is achieved by using a mixture of a modified particle swarm optimization (PSO) and artificial neural network (ANN). ANN is used to assess power system stability to shortage the computation time. The rescheduling process based on the generation companies 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 has been applied on a 66-bus test system.