Mode selective damping of power system electromechanical oscillations for large power systems using supplementary remote signals

This paper presents the design of local decentralized power system stabilizer (PSS) controllers, using selected suitable remote signals as supplementary inputs, for a separate better damping of specific inter-area modes, for large-scale power systems. System identification technique is used for deriving lower order state-space models suitable for control design. The lower-order model is identified by probing the network in open loop with low-energy pulses or random signals. The identification technique is then applied to signal responses, generated by time-domain simulations of the large-scale model, to obtain reduced-order model. Lower-order equivalent models, thus obtained, are used to design each local PSS controller separately for each of the inter-area modes of interest. The PSS controller uses only those local and remote input signals in which the assigned single inter-area mode is most observable and is located at a generator which is most effective in controlling that mode. The PSS controller, designed for a particular single inter-area mode, also works mainly in a frequency band given by the natural frequency of the assigned mode. The locations of the local PSS controllers are obtained based on the amplitude gains of the frequency responses of the best-suited measurement to the inputs of all generators in the interconnected system. For the selection of suitable local and supplementary remote input signals, the features or measurements from the whole system are pre-selected first by engineering judgment and then using a clustering feature selection technique. Final selection of local and remote input signals is based on the degree of observability of the considered single mode in them. To provide robust behavior, H-infinity control theory together with an algebraic Riccati equation approach has been applied to design the controllers. The effectiveness of the resulting PSS controllers is demonstrated through digital simulation studies conducted on a sixteen-machine, three-area test power system. (C) 2012 Elsevier Ltd. All rights reserved.