Papers
Topics
Authors
Recent
Search
2000 character limit reached

Distributed and Asynchronous Operational Optimization of Networked Microgrids

Published 6 Feb 2021 in eess.SY, cs.DC, cs.SY, and math.OC | (2102.03496v1)

Abstract: Smart programmable microgrids (SPM) is an emerging technology for making microgrids more software-defined and less hardware-independent such that converting distributed energy resources (DERs) to networked community microgrids becomes affordable, autonomic, and secure. As one of the cornerstones of SPM, this paper pioneers a concept of software-defined operation optimization for networked microgrids, where operation objectives, grid connection, and DER participation will be defined by software and plug-and-play, and can be quickly reconfigured, based on the development of modularized and tightened models and a novel asynchronous price-based decomposition-and-coordination method. Key contributions include: (1) design the architecture of the operational optimization of networked microgrids which can be readily implemented to ensure the programmability of islanded microgrids in solving the distributed optimization models, (2) realize a novel discrete model of droop controller, and (3) introduce a powerful distributed and asynchronous method Distributed and Asynchronous Surrogate Lagrangian Relaxation (DA-SLR) to efficiently coordinate microgrids asynchronously. Two case studies are tested to demonstrate the efficiency of developed DA-SLR, and specifically, the testing results show the superiority of DA-SLR as compared to previous methods such as ADMM.

Citations (1)

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.