Double Consensus based Optimal Dispatch considering Communication Delay and Noise
17 Dec 2020-
TL;DR: In this article, the authors proposed a robust fully distributed consensus based algorithm (RFDCA) for optimal dispatch of generating units in power systems with a practical communication network, which considers noise, communication delay and a dynamically switching communication topology.
Abstract: This paper proposes a robust fully distributed consensus based algorithm (RFDCA) for optimal dispatch of generating units in power systems with a practical communication network, which considers noise, communication delay and a dynamically switching communication topology. The proposed approach is based on double consensus $- \lambda$ consensus achieved through first-order consensus protocol and $\Delta P$ consensus through average consensus protocol. The adverse effects of noise and communication delay can be lessened through a monotonically decreasing consensus gain function. The main advantage of this method is that the generating units need not share their cost characteristics to anyone, thereby preserving their private information. Another advantage of the proposed approach is that it can deal with networks of different sizes and topology, and by choosing the proper convergence coefficient, a faster rate of convergence can be achieved. Simulations are carried out on standard IEEE test systems to illustrate the efficacy of the RFDCA approach on both smaller and larger systems.
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05 Mar 2007
TL;DR: A theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees is provided.
Abstract: This paper provides a theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees. An overview of basic concepts of information consensus in networks and methods of convergence and performance analysis for the algorithms are provided. Our analysis framework is based on tools from matrix theory, algebraic graph theory, and control theory. We discuss the connections between consensus problems in networked dynamic systems and diverse applications including synchronization of coupled oscillators, flocking, formation control, fast consensus in small-world networks, Markov processes and gossip-based algorithms, load balancing in networks, rendezvous in space, distributed sensor fusion in sensor networks, and belief propagation. We establish direct connections between spectral and structural properties of complex networks and the speed of information diffusion of consensus algorithms. A brief introduction is provided on networked systems with nonlocal information flow that are considerably faster than distributed systems with lattice-type nearest neighbor interactions. Simulation results are presented that demonstrate the role of small-world effects on the speed of consensus algorithms and cooperative control of multivehicle formations
8,696 citations
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Abstract: MATPOWER is an open-source Matlab-based power system simulation package that provides a high-level set of power flow, optimal power flow (OPF), and other tools targeted toward researchers, educators, and students. The OPF architecture is designed to be extensible, making it easy to add user-defined variables, costs, and constraints to the standard OPF problem. This paper presents the details of the network modeling and problem formulations used by MATPOWER, including its extensible OPF architecture. This structure is used internally to implement several extensions to the standard OPF problem, including piece-wise linear cost functions, dispatchable loads, generator capability curves, and branch angle difference limits. Simulation results are presented for a number of test cases comparing the performance of several available OPF solvers and demonstrating MATPOWER's ability to solve large-scale AC and DC OPF problems.
4,645 citations
TL;DR: The mathematical formulation of the incremental cost consensus algorithm, which is able to solve the conventional centralized economic dispatch problem in a distributed manner, and the results of several case studies show that the difference between network topologies will influence the convergence rate of the ICC algorithm.
Abstract: In a smart grid, effective distributed control algorithms could be embedded in distributed controllers to properly allocate electrical power among connected buses autonomously. By selecting the incremental cost of each generation unit as the consensus variable, the incremental cost consensus (ICC) algorithm is able to solve the conventional centralized economic dispatch problem in a distributed manner. The mathematical formulation of the algorithm has been presented in this paper. The results of several case studies have also been presented to show that the difference between network topologies will influence the convergence rate of the ICC algorithm.
528 citations
TL;DR: A novel consensus based algorithm to solve EDP in a distributed fashion, where the quadratic cost functions are adopted in the problem formulation, and the strongly connected communication topology is used for the information exchange.
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496 citations
TL;DR: A novel fully distributed multiagent based load restoration algorithm that can be applied to systems of any size and structure and compared against existing algorithms and a particle swarm optimization based algorithm is proposed.
Abstract: Once a fault in microgrids has been cleared, it is necessary to restore the unfaulted but out-of-service loads as much as possible in a timely manner. This paper proposes a novel fully distributed multiagent based load restoration algorithm. According to the algorithm, each agent makes synchronized load restoration decision according to discovered information. During the information discovery process, agents only communicate with their direct neighbors, and the global information is discovered based on the Average-Consensus Theorem. In this way, total net power, indexes and demands of loads that are ready for restoration can be obtained. Then the load restoration problem can be modeled and solved using existing algorithms for the 0-1 Knapsack problem. To achieve adaptivity and stability, a distributed algorithm for coefficient setting is proposed and compared against existing algorithms and a particle swarm optimization based algorithm. Theoretically, the proposed load restoration algorithm can be applied to systems of any size and structure. Simulation studies with power systems of different scale demonstrate the effectiveness of the proposed algorithm.
272 citations
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