A comparison of distributed optimal power flow algorithms

By B. H. Kim, Ross Baldick. 2000

397 citations recorded by the source corpus.

Subfields: Computational Mechanics, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/fbf4b80ffba0fb3b6ba1802a81c0db8cee2f6667

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In Computational Mechanics

In Electrical and Electronic Engineering

Citations in the corpus

Event-Triggered Feedback in Control, Estimation, and Optimization (2010, background): “This includes estimation [56, 69, 33], source localization [56], data gathering [15, 14], routing [46], control [77], resource allocation [55, 89] in sensor networks, resource allocation in wireless communication networks [86, 16], congestion control in wired communication networks [36, 44], and opt”
Some Efficient Optimization Methods for Solving the Security-Constrained Optimal Power Flow Problem (2014, methodology): “system analysis, to solve the classical OPF problem without the security constraints, in [17], Kim and Baldick split the power grid into a number of separate regions.”
A distribution company energy acquisition market model with integration of distributed generation and load curtailment options (2005, methodology): “In fact, after fulfilling the convergence criteria of the OPF [8-18], or if the maximum number of iterations of the routine (n=N) is achieved, the reactive power injected is computed as follows:”
A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems (2017, background): “See [51], [54], [55], [112] for additional discussion and quantitative comparisons among some of Fig.”
A decentralized solution to the DC-OPF of interconnected power systems (2003, background): “To achieve his or her 0885-8950/03$17.00 © 2003 IEEE goal, each TSO must solve a regional OPF, appropriately modified using information exchanged between neighboring regions, so that the overall interconnected system welfare is maximized.”