An integrated approach for the analysis and control of grid connected energy storage systems

Abstract

© 2015 The Authors.This paper presents an integrated modelling methodology which includes reduced-order models of a lithium ion battery and a power electronic converter, connected to a 35-bus distribution network model. The literature contains many examples of isolated modelling of individual energy storage mediums, power electronic interfaces and control algorithms for energy storage. However, when assessing the performance of a complete energy storage system, the interaction between components gives rise to a range of phenomena that are difficult to quantify if studied in isolation. This paper proposes an integrated electro-thermo-chemical modelling methodology that seeks to address this problem directly by integrating reduced-order models of battery cell chemistry, power electronic circuits and grid operation into a computationally efficient framework. The framework is capable of simulation speeds over 100 times faster than real-time and captures phenomena typically not observed in simpler battery and power converter models or non-integrated frameworks. All simulations are performed using real system load profiles recorded in the United Kingdom. To illustrate the advantages inherent in such a modelling approach, two specific interconnected effects are investigated: the effect of the choice of battery float state-of-charge on overall system efficiency and the rate of battery degradation (capacity/power fade). Higher state-of-charge operation offers improved efficiency due to lower polarisation losses of the battery and lower losses in the converter, however, an increase in the rate of battery degradation is observed due to the accelerated growth of the solid-electrolyte interphase layer. We demonstrate that grid control objectives can be met in several different ways, but that the choices made can result in a substantial improvement in system roundtrip efficiency, with up to a 43% reduction in losses, or reduction in battery degradation by a factor of two, depending on battery system use case

Lithium-Ion Battery Storage for the Grid—A Review of Stationary Battery Storage System Design Tailored for Applications in Modern Power Grids

“…Despite improved capabilities of these emerging approaches, it is still believed, that for simulations of the aging behavior of a full LIB storage system or an automotive battery pack high accuracy of a single battery cell model is essential [54,57]. The different approaches show individual strength and drawbacks, and Table 4 summarizes some indicators for comparison at a short glance.…”

“…Recently, non-empirical Physical-Chemical Models (PCM) have gained increasing interest [51][52][53]. Despite the usage of PCM models for aging prediction may allow giving a more detailed insight to cell internal loss mechanisms and how to circumvent these, it remains most challenging to find a valid parametrization of such models and to scale the cell internal models to the application relevant level of a full battery system [52,54,55].…”

“…In fact, present state-of-art BESS simulations and modeling tools available typically do not include all key components of the system under study. Instead, most studies focus on a specific system performance aspect, e.g., cell aging [54], power electronics losses [89], or economic evaluations [13,14]. Model approaches should be carefully selected in terms of the covered mechanisms and goals of the work.…”

“…In most contributions analyzed, not all components are included for simplification purposes or due to the unavailability of required data. e.g., Patsios et al [54] evaluated a storage system simulation based on a single-particle cell model including calendar aging effects (cf. PCM modeling, Section 2.2) combined with discrete time power electronics models.…”

Comprehensive Modeling of Temperature-Dependent Degradation Mechanisms in Lithium Iron Phosphate Batteries

“…Physicochemical models that include aging mechanisms are based on a detailed set of parameters which are often not readily available, computationally costly and require experimental parameterization of degradation rates. [2][3][4] Instead, purely empirical models can be parameterized without knowledge of internal cell setup through extensive testing. Several purely empirical studies capture calendar aging 5,6 or cycle aging 7,8 without evaluating interdependencies.…”