Impact of communication latency on distributed optimal power flow performance
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RESEARCH
Energy Informatics
Open Access
Impact of communication latency on distributed optimal power flow performance Clemens Korner1* , Catalin Gavriluta1 , Filip Pröstl Andrén1 , Marcus Meisel2,3 and Thilo Sauter2,4 From The 9th DACH+ Conference on Energy Informatics Sierre, Switzerland. 29-30 October 2020 *Correspondence: [email protected] 1 AIT Austrian Institute of Technology – Electric Energy Systems, Giefinggasse 2, 1210 Vienna, Austria Full list of author information is available at the end of the article
Abstract In this work, we study the performance of a distributed optimal power flow control algorithm with respect to realistic communication quality of service. By making use of a communication network simulator, namely “GNS3”, we created a framework that simulates both the controllers involved in the optimal power flow algorithm and the communication between them. Using this platform, we investigate and give insights into the convergence time of the distributed algorithm when applied to the IEEE 13 and IEEE 123 node test feeders. By leveraging the simulation results, we define parameters on the network quality of service, such that the distributed optimal power flow algorithm could be used for secondary or tertiary control. To deal with the complexity induced by a large number of components involved in these simulations, we present a methodology to automate and streamline the generation and the analysis of simulation scenarios. Keywords: Alternating direction method of multipliers, Communication quality of service, Distributed generation, Network simulator, Distributed optimal power flow
Introduction This section provides an overview of the two main topics which are covered by this paper and their related work. The first part is about the ongoing shift from large centralized power generation units to smaller more distributed generation. As a consequence, new decentralized and distributed control strategies have emerged which claim to solve most of the thereby arising problems. In the second part, we will discuss the need for proper communication network simulations for distributed control algorithms to evaluate their practical usability. These simulations are usually manually generated and include cumbersome and error-prone parametrization. The automatized preparation and generation of simulations can reduce the needed work and the time spent debugging. With the increased penetration of distributed generators based on renewable energy, the number of controllable devices in the electrical grid is increasing (Kraning et al. 2014). In 2017 in the European Union, 85% of the newly installed power generation fell within the category of renewable energy resources (European Environment Agency 2018). This © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, pr
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