The idea of a smart grid is based on the increased integration of information technologies throughout the power grid. Technologies such as phasor measurement units (PMUs) are being deployed to increase the number of wide-area measurements across the bulk power system providing increased awareness of the system operational state. However, from a critical infrastructure perspective, the advanced metering infrastructure introduces a concern: the loss of communication among devices and the power grid. This communication loss may interfere with the wide-area control system performance and adversely affect the power system dynamics. This paper proposes a method based on genetic algorithms for wide-area robust damping controller design considering multiple operation points and loss of communication links related to the input and to the output of the central controller. The method is applied to enhance the damping of the electromechanical oscillations in an IEEE benchmark system: the Simplified 14-Generator Model of the Southeastern Australian Power System. The performance of the designed controller is evaluated using modal analysis and non-linear simulations in the time-domain. The obtained results demonstrate the effectiveness of the method to design a single centralized controller that provides satisfactory damping to the electromechanical oscillations over several operating points, even when there is a loss of a communication link, thus being robust w.r.t. is an important aspect of a critical power grid infrastructure.

Mapping the spatial distribution of nodal inertia is crucial for helping system operators identify locational frequency stability issues in the power system operation planning process. Currently, index-based methods cannot retrieve the nodal inertia values for all load buses. To do so, this paper proposes an accurate analytical formulation relying only on steady-state system parameters to determine the nodal inertia values and, thus, map the spatial distribution of system inertia. The performance and reproducibility of the proposed formulation are evaluated using three test systems: a 5-bus radial system with two synchronous generators, a multimachine IEEE 68-bus benchmark system, and a larger 140-bus test system. Our spatial distribution of inertia is validated using time-domain simulations and numerical estimations. We compare the proposed method against the inertia distribution indexes presented in the literature. The results indicate that our formulation adequately quantifies the nodal inertia value in system buses, with low computational cost, and providing a suitable tool for operation planning analysis.

This paper presents a new data-driven methodology for power system coherency identification of generator and non-generator buses. This methodology is exclusively based on intrinsic statistical properties extracted directly from observations, without any prior assumption of the probability distribution function (PDF) for the data. The main advances of this proposal are: ( i ) gathering of statistical information from the data itself despite scenarios where the PDF may change (different inverter-based load and generation scenarios, load levels of the system, and changes in topology); and ( ii ) assignment of buses into coherent areas without any tuning of parameters, nor manually labeling of huge amounts of training data. This new method, called typicality-based data analysis (TDA), is applied to the correlation metric of the distance between dynamic responses of buses, either voltage angles or frequencies. Simulated signals from a benchmark power system with cases considering the presence of non-synchronous generation and islanding conditions, and real data associated with generation trips in the U.S. Eastern Interconnection are used to corroborate the methodology effectiveness.

In this paper, an environmental economic dispatch problem with storage, network, and inter-temporal constraints is considered. An approach based on the simultaneous perturbation technique is proposed to deal with the equality and inequality constraints in the economic dispatch problem. The algorithm has been implemented using Matlab and tested on a 6-bus, 5-generator system and a 140-bus, 48-generator system. The effects of cap-and-trade policies, energy storage, and transmission line flow limits in economic dispatch are discussed. The simulations reveal that the method can handle a variety of constraints with good convergence performance.