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

TL;DR

This paper introduces a two-stage centralized control scheme for distributed battery storage in low voltage grids, optimizing operation to reduce degradation and losses while ensuring grid stability amidst high photovoltaic input.

Contribution

It presents a novel two-stage control framework with a robust multi-period OPF and a linearized real-time OPF for efficient, secure battery management in low voltage distribution grids.

Findings

Reduced battery degradation by incorporating a degradation model.

Achieved 30% reduction in battery losses using detailed battery modeling.

Demonstrated effectiveness through a case study with two battery technologies.

Abstract

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.