Weighted Bandwidth Method for Stability Assessment of Complex DC Power Systems on Ships

In shipboard DC grids, tightly controlled load converters can impair the system stability, thus provoking the ship blackout. Conversely, load converters regulated by low control bandwidths are capable of inducing a stabilizing action. This compensation is verifiable if the loads are few. On the contrary, the balancing of control dynamics is hardly evaluated if the bus feeds multiple (i.e., hundreds or more) DC controlled loads. In this paper, the weighted bandwidth method (WBM) is presented to assess the small-signal stability of a complex shipboard power system by aggregating the multiple converters into two sets of controlled loads. Once the validity of the aggregation is proven, a stability study is performed on the two-loads system. As the last system is more inclined to instability than the initial multiple-loads system, the verification of the two-loads stability criterion guarantees that the shipboard DC grid also remains stable. Finally, emulations on HIL verify the proposed stability assessment thus providing the first unique verification of WBM.

Small signal stability enhancement of a large scale power system using a bio-inspired whale optimization algorithm

A whale optimization algorithm (WOA)-based power system stabilizer (PSS) design methodology on modified single machine infinite bus (MSMIB) and multi-machine systems to enhance the small-signal stability (SSS) of the power system is presented. The PSS design methodology is implemented using an eigenvalue (EV)-based objective function. The performance of the WOA is tested with several CEC14 and CEC17 test functions to investigate its potential in optimizing the complex mathematical equations. The New England 10-generator 39-bus system and the MSMIB system operating at various loading conditions are considered as the test systems to examine the proposed method. Extensive simulation results are obtained which validate the effectiveness of the proposed WOA method when compared with other algorithms.