Theoretical dimensioning and sizing limits of hybrid energy storage systems

Aim of a storage hybridisation is a beneficial usage or combination of different storage technologies with various characteristics to downsize the overall system, decrease the costs or to increase the lifetime, system efficiency or performance. In this paper, the point of interest is a different ratio of power to energy (specific power) of two storages to create a hybrid energy storage system (HESS) with a resulting specific power that better matches the requirements of the application. The approach enables a downsizing of the overall system compared to a single storage system and consequently decreases costs. The paper presents a theoretical and analytical benchmark calculation that determines the maximum achievable hybridisation, i.e. possible spread in specific power, while retaining the original total energy and power capacities of an equivalent single storage system. The theory is independent from technology, topology, control strategy, and application and provides a unified view on hybrid energy storage systems. It serves as a pre-dimensioning tool and first step within a larger design process. Furthermore, it presents a general approach to choose storage combinations and to characterize the potential of an application for hybridisation. In this context, a Hybridisation Diagram is proposed and integral Hybridisation Parameters are introduced

Ragone plots revisited: A review of methodology and application across energy storage technologies

The term “Ragone plot” refers to a popular and helpful comparison framework that quantifies the energy–power relationship of an energy storage material, device, or system. While there is consensus on the general Ragone plot concept, many implementations are found in the literature. This article provides a systematic and comprehensive review of the Ragone plot methodology in the field of electric energy storage. A faceted taxonomy is developed, enabling existing and future Ragone plots to be unambiguously classified and contextualized. This review focuses on disseminating the methodology, discussing technology-specific aspects, and giving an overview of the further sizing and design methods developed based on Ragone plots. Additionally, this article identifies best practices for obtaining and presenting Ragone plots. This review is not limited to electrochemical energy storage, where the framework is traditionally applied, but also encompasses all other electric energy storage. Here, the Ragone plot can compactly quantify off-design performance and operational flexibility, independent of technology-specific performance indicators. This review is the first of its kind and can, therefore, guide future application of the Ragone plot framework in a consistent manner

Structured Analysis and Review of Filter-Based Control Strategies for Hybrid Energy Storage Systems

Hybrid energy storage systems (HESS), i.e., the combination of two different energy storage technologies, are widely discussed as a promising solution for energy storage problems. A common control scheme to allocate the power between these storages and the subject of this study is filter-based control, where a filter splits the input signal into a low-frequency and high-frequency part. It provides robust results and easy implementation, although more advanced strategies may perform better. Many publications use this controller for specific problems, but a structured analysis of this controller type that quantifies the advantages and disadvantages, traits, and setbacks is missing. This work fills this gap and structures, summarizes, and provides mathematical background and guidelines on filter-based control of hybrid energy storage systems. Numerical simulations are performed to quantify the impact of design variables, parameters, or the input signal by using a linear storage model with efficiency and self-discharge rate and a low-pass filter controller with constant energy feedback as a representative subtype of this control scheme. The present work proves the high cycle-reduction capabilities of filter-controlled HESS at the cost of overdimensioning compared to more advanced control strategies. It demonstrates that using a high-efficiency, high-power storage with a low self-discharge rate and high-energy storage leads to smaller overall dimensioning and losses than a single storage system. The study identifies the feedback factor of the controller as the most impacting design variable

Techno-economic and Environmental Comparison of Internal Combustion Engines and Solid Oxide Fuel Cells for Ship Applications

In order to quantify the economic and environmental impact of technology selection in ship power systems, four different battery-supported hybrid configurations including diesel and gas combustion engines, as well as natural gas fueled solid oxide fuel cells (SOFCs) are modeled and analyzed. The investigations include component investments, maintenance and operational costs, as well as the components’ and fuels’ carbon footprints, operational greenhouse gases and other relevant emissions. Dynamic energy system models are used to derive economically optimal system designs for an appropriate technology comparison in a cruise ship case study. The assessment is conducted for a cruise ship case study with technology parameters for the near future and 2050. Results indicate that the auxiliary power system based on diesel combustion is inferior both economically and environmentally compared to SOFCs or gas combustion engines. While latter are the most cost efficient, SOFC application provides an environmental improvement without the need for a new fuel such as hydrogen. In a final outlook for the year 2050, SOFCs economically overtake gas combustion engines on the condition that their investment costs decrease and synthetic fuels are introduced to the market as a low emission solution

Choosing the right model for unified flexibility modeling

Using aggregated flexibility from distributed small-scale power devices is an extensively discussed approach to meet the challenges in modern and increasingly stochastic energy systems. It is crucial to be able to model and map the flexibility of the respective power devices in a unified form to increase the value of the cumulative flexibility from different small-scale power devices by aggregation. In order to identify the most suitable approach for unified flexibility modeling we present a framework to evaluate and compare the advantages and disadvantages of already existing modeling approaches in different levels of detail. As an introduction to flexibility modeling and as a basis for the evaluation process we initially provide a comprehensive overview of the broad range of flexibility models described in scientific literature. Subsequently, five selected modeling approaches allowing the generation of a unified flexibility representation for different power devices are presented in detail. By using an evaluation metric we assess the suitability of the selected approaches for unified flexibility modeling and their applicability. To allow a more detailed performance analysis, the best evaluated models are implemented and simulations with different small-scale devices are performed. The results shown in this paper highlight the heterogeneity of modeling concepts deriving from the various interpretations of flexibility in scientific literature. Due to the varying complexity of the modeling approaches, different flexibility potentials are identified, necessitating a combination of approaches to capture the entire spectrum of the flexibility of different small-scale power devices. Furthermore, it is demonstrated that a complex model does not necessarily lead to the discovery of higher flexibility potentials, and recommendations are given on how to choose an appropriate model. © 2022, The Author(s)

ESTSS—energy system time series suite: a declustered, application-independent, semi-artificial load profile benchmark set

Abstract This paper introduces an univariate application-independent set of load profiles or time series derived from real-world energy system data. The generation involved a two-step process: manifolding the initial dataset through signal processors to increase diversity and heterogeneity, followed by a declustering process that removes data redundancy. The study employed common feature engineering and machine learning techniques: the time series are transformed into a normalized feature space, followed by a dimensionality reduction via hierarchical clustering, and optimization. The resulting dataset is uniformly distributed across multiple feature space dimensions while retaining typical time and frequency domain characteristics inherent in energy system time series. This data serves various purposes, including algorithm testing, uncovering functional relationships between time series features and system performance, and training machine learning models. Two case studies demonstrate the claims: one focused on the suitability of hybrid energy storage systems and the other on quantifying the onsite hydrogen supply cost in green hydrogen production sites. The declustering algorithm, although a bys study, shows promise for further scientific exploration. The data and source code are openly accessible, providing a robust platform for future comparative studies. This work also offers smaller subsets for computationally intensive research. Data and source code can be found at https://github.com/s-guenther/estss and https://zenodo.org/records/10213145

Choosing the right model for unified flexibility modeling

Abstract Using aggregated flexibility from distributed small-scale power devices is an extensively discussed approach to meet the challenges in modern and increasingly stochastic energy systems. It is crucial to be able to model and map the flexibility of the respective power devices in a unified form to increase the value of the cumulative flexibility from different small-scale power devices by aggregation. In order to identify the most suitable approach for unified flexibility modeling we present a framework to evaluate and compare the advantages and disadvantages of already existing modeling approaches in different levels of detail. As an introduction to flexibility modeling and as a basis for the evaluation process we initially provide a comprehensive overview of the broad range of flexibility models described in scientific literature. Subsequently, five selected modeling approaches allowing the generation of a unified flexibility representation for different power devices are presented in detail. By using an evaluation metric we assess the suitability of the selected approaches for unified flexibility modeling and their applicability. To allow a more detailed performance analysis, the best evaluated models are implemented and simulations with different small-scale devices are performed. The results shown in this paper highlight the heterogeneity of modeling concepts deriving from the various interpretations of flexibility in scientific literature. Due to the varying complexity of the modeling approaches, different flexibility potentials are identified, necessitating a combination of approaches to capture the entire spectrum of the flexibility of different small-scale power devices. Furthermore, it is demonstrated that a complex model does not necessarily lead to the discovery of higher flexibility potentials, and recommendations are given on how to choose an appropriate model