Abstract
In this paper, we consider the optimal coordination problem for distributed energy resources (DERs), including distributed generators and energy storages. We first propose an algorithm based on the push-sum and gradient method to solve the optimal DER coordination problem in a distributed manner. In the proposed algorithm, each DER only maintains a set of variables and updates them through information exchange with a few neighboring DERs over a time-varying directed communication network. We show that the proposed distributed algorithm with appropriately chosen diminishing step sizes solves the optimal DER coordination problem if the time-varying directed communication network is uniformly jointly strongly connected. Moreover, in order to improve the convergence speed and to reduce the communication burden, we propose an accelerated distributed algorithm with a fixed step size. We show that the new proposed algorithm exponentially solves the optimal DER coordination problem if the cost functions satisfy an additional assumption and the selected step size is less than a certain critical value. Both proposed distributed algorithms are validated and evaluated using the IEEE 39-bus system.
| Original language | English |
|---|---|
| Article number | 8731737 |
| Pages (from-to) | 1124-1134 |
| Number of pages | 11 |
| Journal | IEEE Transactions on Control of Network Systems |
| Volume | 6 |
| Issue number | 3 |
| DOIs | |
| State | Published - Sep 2019 |
Funding
Manuscript received January 4, 2019; revised May 16, 2019; accepted May 26, 2019. Date of publication June 5, 2019; date of current version September 17, 2019. This work was supported in part by the Ralph E. Powe Junior Faculty Enhancement Award for the Oak Ridge Associated Universities, in part by the National Science Foundation under Grant CMMI-1763093 and Grant ECCS-1611423, in part by the National Natural Science Foundation of China under Grant 61733018 and Grant 61573344, in part by the Knut and Alice Wallenberg Foundation, and in part by the Swedish Research Council. This work was authored by UT-Battelle, LLC, under Contract DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). Some preliminary work was presented in the conference version of this paper [1]. Recommended by Associate Editor M. Chertkov. (Corresponding author: Di Wu.) T. Yang is with the Department of Electrical Engineering, University of North Texas, Denton, TX 76203 USA (e-mail:,[email protected]).
| Funders | Funder number |
|---|---|
| National Science Foundation | CMMI-1763093, 1763093, ECCS-1611423 |
| U.S. Department of Energy | |
| Oak Ridge Associated Universities | |
| National Natural Science Foundation of China | 61733018, 61573344 |
| Knut och Alice Wallenbergs Stiftelse | |
| Vetenskapsrådet | DE-AC05-00OR22725 |
Keywords
- Distributed coordination
- energy storage (ES)
- multiagent systems
- multistep optimization
- push-sum and gradient method
- smart grid