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This paper provides an enhanced modeling of the contingency response that collectively reflects high-fidelity physical and operational characteristics of power grids. Integrating active and reactive power contingency responses into the security-constrained optimal power flow (SCOPF) problem is challenging, due to the nonsmoothness and nonconvexity of feasible sets in consequence of piece-wise curves representing generator characteristics. We introduce a continuously-differentiable model using functions that closely resemble PV/PQ switching and the generator contingency response. These models enforce physical and operational limits by optimally allocating active power imbalances among available generators and deciding the bus type to switch from the PV type to the PQ type. The efficacy of this method is numerically validated on the IEEE 30-bus, 300-bus, and 118-bus systems with 12, 10, and 100 contingencies, respectively.

This paper presents an approach to obtain reduced-order models for power networks involving power electronic converters (PEC) via the frequency-domain balanced realizations (FDBR) technique. PECs play an essential role in power processing and energy conversion in modern electrical networks, such as the interconnection of renewable generators, HVDC links, and active filters. Integration of PECs into dynamic equivalents needs model-order reduction (MOR) in both low- and high-frequency ranges to account for both slow and fast dynamics due to the network and switching natures. The objective of the FDBR technique is to obtain an internally balanced system, i.e., an equally controllable/observable system, that can be reduced according to its dominant dynamics within the limited frequency bandwidths. This allows accounting for specific band-limited phenomena, such as those generated within a power network caused by PECs, which is the focus of this paper. The results show that faster yet accurate simulations are achieved by reduced-order models through FDBR compared to their full-order counterparts., Intelligent Electrical Power Grids

This paper presents an approach to obtain reduced-order models for power networks involving power electronic converters (PEC) via the frequency-domain balanced realizations (FDBR) technique. PECs play an essential role in power processing and energy conversion in modern electrical networks, such as the interconnection of renewable generators, HVDC links, and active filters. Integration of PECs into dynamic equivalents needs model-order reduction (MOR) in both low- and high-frequency ranges to account for both slow and fast dynamics due to the network and switching natures. The objective of the FDBR technique is to obtain an internally balanced system, i.e., an equally controllable/observable system, that can be reduced according to its dominant dynamics within the limited frequency bandwidths. This allows accounting for specific band-limited phenomena, such as those generated within a power network caused by PECs, which is the focus of this paper. The results show that faster yet accurate simulations are achieved by reduced-order models through FDBR compared to their full-order counterparts., Intelligent Electrical Power Grids

With the transition toward a smart grid, the power system has become strongly intertwined with the information and communication technology (ICT) infrastructure. The interdependency of both domains requires a combined analysis of physical and ICT processes, but simulating these together is a major challenge due to the fundamentally different modeling and simulation concepts. After outlining these challenges, such as time synchronization and event handling, this paper presents an overview of state-of-the-art solutions to interface power system and ICT simulators. Due to their prominence in recent research, a special focus is set on co-simulation approaches and their challenges and potentials. Further, two case studies analyzing the impact of ICT on applications in power system operation illustrate the necessity of a holistic approach and show the capabilities of state-of-the-art co-simulation platforms., QC 20180111

Optimal output synchronization of multi-agent leader-follower systems with unknown nonlinear dynamics is considered. The agents are assumed heterogeneous so that the dynamics may be nonidentical. A distributed observer is designed to estimate the leader state for each agent. A discounted performance function is defined for each agent, and an augmented Hamilton-Jacobi-Bellman (HJB) equation is derived to find its minimal value. The HJB solution depends on the trajectories of the local state and the distributed observer state. A control protocol based on the HJB solution assures that the synchronization error goes to zero locally asymptotically fast for all agents. The proposed approach has two main advantages compared to standard output synchronization methods. First, it is optimal in the sense that it not only makes the steady-state synchronization error zero, but also minimizes the transient error. Second, it does not require the explicit solution to the output regulator equations, though the HJB solutions implicitly provide optimal solutions to them. Finally, a reinforcement learning technique is used to learn the optimal control protocol for each agent without requiring any knowledge of the agents or the leader dynamics. Simulation studies on a notional multi-agent system validate the proposed approach.

The papers in this special issue on advanced distributed control of energy conversion devices and systems are loosely grouped into three categories: 1) ac energy conversion systems; 2) dc energy conversion systems; and 3) optimization and standards.

The papers in this special issue on advanced distributed control of energy conversion devices and systems are loosely grouped into three categories: 1) ac energy conversion systems; 2) dc energy conversion systems; and 3) optimization and standards.

The detailed switch-level models of front-end diode recti fi er loads can be readily implemented using a number of transient simulation programs, such as PSCAD/EMTDC, and the toolboxes in Matlab/Simulink. To improve the simulation ef fi ciency for the system-level studies, the so-called dynamic ave rage models have been widely used by researchers and en- gineers. Recently, several aver age-value modeling methodologies for the conventional three-phase (six-pulse) front-end recti fi er loads have been discussed, and the dynamic performance of sev- eral developed models has been demonstrated in discontinuous and continuous modes. In this paper, the effects of topological variations of the ac-side fi lters on the system performance are investigated. Also, the steady-st ate and dynamic impedances pre- dicted by the average models under balanced and unbalanced operation are compared. The studies and analyses presented here extend and complement those set forth in the preceding companion publication., Postprint (published version)

Interfacing issues in multiagent simulation for smart grid applications Wang, X.1; Zhang, P.2; Wang, Z.3; Dinavahi, V.4; Chang, G.5; Martinez, J.A.6; Davoudi, A.7; Mehrizi-Sani, A.8; Abhyankar, S.9 Source: IEEE Transactions on Power Delivery, v 28, n 3, 1918-27, July 2013; ISSN: 0885-8977; DOI: 10.1109/TPWRD.2013.2260566; Publisher: IEEE, USA Author affiliations: 1 Carleton Univ., Ottawa, ON, Canada 2 Electr. & Comput. Eng. Dept., Univ. of Connecticut, Storrs, CT, United States 3 Sch. of Electr. Eng., Shandong Univ., Jinan, China 4 Electr. & Comput. Eng. Dept., Univ. of Alberta, Edmonton, AB, Canada 5 Electr. Eng. Dept., Nat. Chung Cheng Univ., Chiayi, Taiwan 6 Dept. Eng. Electr.-ETSEIB, Univ. Politec. de Catalunya, Barcelona, Spain 7 Electr. & Comput. Eng. Dept., Univ. of Texas, Arlington, TX, United States 8 Sch. of Electr. Eng. & Comput. Sci., Washington State Univ., Pullman, WA, United States 9 Argonne Nat. Lab., Argonne, IL, United States Abstract: This paper discusses design and application of the multiagent simulation technology aiming to meet smart grid requirements. The difference between multiagent systems and multiagent simulation in smart grid applications is clarified. The state-of-the-art applications of multiagent simulation in power and energy systems are classified based on the simulation environment. The paper also addresses the interface issues including synchronization and data distribution for multiagent co-simulation. In addition, the emerging research paradigms in smart grid multiagent simulation are identified., Postprint (published version)