Consensus-based Distributed Algorithm Research Articles

A novel distributed finite-time economic dispatch for DC microgrids with time delays

This paper delineates an advanced distributed control paradigm for finite-time generation cost optimization in DC Microgrids (MGs), taking into account time delays. Firstly, to enhance system stability with time delays, Artstein's reduction approch is utilized to convert the time-delayed system into an equivalent delay-free model. Subsequently, a finite-time consensus-based distributed algorithm for cost optimization is formulated to equilibrate the incremental costs (ICs) of all distributed generators (DGs) in a predefined convergence time, while adhering to the DGs' capacity limits. Moreover, a distributed control mechanism for finite-time voltage stabilization is developed for sustaining the balance between the generated powers and consumptions across the MG. Rigorous convergence analysis proves that the proposed controller maintains finite-time stability. The efficacy of this innovative control strategy is substantiated through a series of comprehensive case studies.Top of Form

A resilient convex combination for consensus-based distributed algorithms

Consider a set of vectors in $ \mathbb{R}^n $, partitioned into two classes: normal vectors and malicious vectors, for which the number of malicious vectors is bounded but their identities are unknown. The paper provides an efficient way for achieving a resilient convex combination, which is a convex combination of only normal vectors. Compared with existing approaches based on Tverberg points, the proposed method based on the intersection of convex hulls has lower computational complexity. Simulations suggest that the proposed method can be applied to achieve resilience of consensus-based distributed algorithms against Byzantine attacks based only on agents' locally available information.

Resilient Consensus-Based Time Synchronization in Asynchronous Sensor Networks

This paper addresses the time synchronization problem of asynchronous wireless sensor networks (WSNs) under false data injection attacks. First, we extend the fundamental metric of r-robustness with the notion of trusted links and then show that the structural robustness of networks can be significantly improved without adding additional links after setting a small subset of links to be trusted. Then, for a more practical case where the intercommunication topologies between each sensor node are time-varying, we develop a resilient consensus-based distributed algorithm where the sampling period is allowed to be chosen by each sensor independently and it is shown that the time synchronization problem for WSNs can be solved via the proposed controller. Numerical simulations are conducted to illustrate the effectiveness of our proposed method.

A Novel Consensus-Based Distributed Algorithm for Economic Dispatch Based on Local Estimation of Power Mismatch

This paper proposes a novel consensus-based distributed control algorithm for solving the economic dispatch problem of distributed generators. A legacy central controller can be eliminated in order to avoid a single point of failure, relieve computational burden, maintain data privacy, and support plug-and-play functionalities. The optimal economic dispatch is achieved by allowing the iterative coordination of local agents (consumers and distributed generators). As coordination information, the local estimation of power mismatch is shared among distributed generators through communication networks and does not contain any private information, ultimately contributing to a fair electricity market. Additionally, the proposed distributed algorithm is particularly designed for easy implementation and configuration of a large number of agents in which the distributed decision making can be implemented in a simple proportional-integral (PI) or integral (I) controller. In MATLAB/Simulink simulation, the accuracy of the proposed distributed algorithm is demonstrated in a 29-node system in comparison with the centralized algorithm. Scalability and a fast convergence rate are also demonstrated in a 1400-node case study. Further, the experimental test demonstrates the practical performance of the proposed distributed algorithm using the VOLTTRON platform and a cluster of low-cost credit-card-size single-board PCs.

Minimum-Time Consensus-Based Approach for Power System Applications

This paper presents minimum-time consensus-based distributed algorithms for power system applications, such as load shedding and economic dispatch. The proposed algorithms are capable of solving these problems in a minimum number of time steps instead of asymptotically as in most of the existing studies. Moreover, these algorithms are applicable to both undirected and directed communication networks. Simulation results are used to validate the proposed algorithms.

Multiperiod Scheduling for Wireless Sensor Networks: A Distributed Consensus Approach

In wireless sensor networks, many sensors face energy constraints and can switch among different work modes to save energy. How to properly schedule work modes is important for network utility maximization (NUM) in the long run. This paper proposes multiperiod scheduling to maximize total network utility by considering energy constraints and periodic sensing requirements. This NUM problem presents challenging mixed-integer programming, and it is difficult to solve by using a centralized approach under complete information. Thus, we first simplify the multiperiod problem to an equivalent single-period problem, and then further reduce it to a pure-integer programming problem, which can be solved easily in a centralized way. As for the cases without a centralized coordinator among all sensors, we propose an average consensus-based distributed algorithm (ACDA) to distributively schedule the work modes of all sensors using only local information. We prove that ACDA converges exponentially fast and reaches global optimum as long as the energy consumption of running the algorithm is ignorable. The proposed distributed solution is also robust against packet drop, node failures, and the changes of communication topology. Extensive simulation results have also shown the effectiveness of the proposed distributed algorithms.