Modeling and Optimal Operation of Distributed Battery Storage in Low Voltage Grids

• Published in: arXiv.org
• Main Authors: tenbacher, Philipp, Mathieu, Johanna L, Andersson, Göran
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 16.03.2017
• Subjects: Batteries; Computer Science - Systems and Control; Degradation; Energy storage; Linear programming; Linearization; Low voltage; Overloading; Photovoltaic cells; Power flow; Predictive control; Scheduling; Solar cells
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.1603.06468

Due to high power in-feed from photovoltaics, it can be expected that more battery systems will be installed in the distribution grid in near future to mitigate voltage violations and thermal line and transformer overloading. In this paper, we present a two-stage centralized model predictive control scheme for distributed battery storage that consists of a scheduling entity and a real-time control entity. To guarantee secure grid operation, we solve a robust multi-period optimal power flow (OPF) for the scheduling stage that minimizes battery degradation and maximizes photovoltaic utilization subject to grid constraints. The real-time controller solves a real-time OPF taking into account storage allocation profiles from the scheduler, a detailed battery model, and real-time measurements. To reduce the computational complexity of the controllers, we present a linearized OPF that approximates the nonlinear AC-OPF into a linear programming problem. Through a case study, we show, for two different battery technologies, that we can substantially reduce battery degradation when we incorporate a battery degradation model. A further finding is that we can reduce battery losses by 30% by using the detailed battery model in the real-time control stage.