Asynchronous Distributed Power Control of Multimicrogrid Systems

Abstract

Asynchrony widely exists in microgrids (MGs), such as non-identical sampling rates and communication delays, which challenges the MG control. This paper addresses the asynchronous distributed power control problem of hybrid microgrids, considering different kinds of asynchrony, such as non-identical sampling rates and random time delays. To this end, we first formulate the economic dispatch problem of MGs and devise a synchronous algorithm. Then, we analyze the impact of asynchrony and propose an asynchronous iteration algorithm based on the synchronous version. By introducing a random clock at each iteration, different types of asynchrony are fitted into a unified framework, where the asynchronous algorithm is converted into a fixed-point iteration problem with a nonexpansive operator, leading to a convergence proof. We further provide an upper bound estimation of the time delay of the communication. Moreover, the real-time implementation of the proposed algorithm in both AC and DC MGs is introduced. By measuring the frequency/voltage, the controller is simplified by reducing one order and adapt to the fast varying load demand. Finally, simulations on a benchmark MG and experiments are utilized to verify the effectiveness and advantages of the proposed algorithm. Index Terms-Asynchronous control, distributed control, multi-agent system, multi-microgrid networks, time delay. I. INTRODUCTION Multi-Microgrid systems or Microgrids (MGs) are clusters of distributed generators (DGs), energy storage systems and loads, which are generally categorized into three types: AC, DC and hybrid AC/DC MGs [1], [2]. A hybrid AC/DC MG has the advantage of reducing processes of multiple inverse conversions in the involved individual AC or DC grid [3]. Recently, the distributed power control for MGs has attracted more and more attention due to its fast response speed, privacy

Distributed Predictive Secondary Control for Imbalance Sharing in AC Microgrids

“…An analysis of the MG performance when the topology changes is shown in Section IV. Furthermore, an asynchronous communication protocol is used; thus, no global clock is necessary to ensure that the sharing of information is globally synchronized [39], [40].…”

An efficient distributed algorithm for economic dispatch considering communication asynchrony and time delays

“…In addition, common time delays can further lengthen the waiting time. Recently, a few methods for distributed ED have been reported [30][31][32][33] that adopt asynchronous iterations and remove the requirement of global clock synchronization. That is, the communications and updates of each agent are determined by its local clock, which is completely distributed and caters more to real applications.…”

“…[31], where agents can reuse the stored information when time delays occur. The authors of [32] introduced a random clock and developed a unified asynchronous framework for distributed ED in hybrid microgrids with time delays.…”

“…Compared with most of the existing distributed solutions to ED problems [10–14, 17, 18, 20–29] that require costly synchronous communications, the proposed distributed asynchronous algorithm can be executed without global clock synchronization. 2.Compared with existing distributed asynchronous algorithms for economic dispatch [30–33] that are only for undirected networks, the proposed distributed asynchronous algorithm is applicable to directed networks that cover more communication schemes in practice, for example, wireless networks and broadcast protocols. 3.The heavy‐ball momentum is further incorporated in algorithm design, to accelerate the convergence.…”

Convergence Analysis of Dual Decomposition Algorithm in Distributed Optimization: Asynchrony and Inexactness

“…1) Asynchrony in communication: In practice, the implementation of the DD-DO algorithm usually suffers from asynchrony due to packet drop, time delay in communications, and non-identical computational rates, etc. In this situation, the synchronous DD-DO algorithm may cause longer idle time since the coordinator and the agents have to wait for the latest information from their neighbors in order to execute the next iteration [14]. To circumvent this problem, an asynchronous DD-DO algorithm is proposed in [15] by updating the dual variables and solving subproblems immediately using the previously stored information, if the latest information happens to be unavailable.…”