Hesse, Holger
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Battery energy storage systems have gained increasing interest for serving grid support in various application tasks. In particular, systems based on lithium-ion batteries have evolved rapidly with a wide range of cell technologies and system architectures available on the market. On the application side, different tasks for storage deployment demand distinct properties of the storage system. This review aims to serve as a guideline for best choice of battery technology, system design and operation for lithium-ion based storage systems to match a specific system application. Starting with an overview to lithium-ion battery technologies and their characteristics with respect to performance and aging, the storage system design is analyzed in detail based on an evaluation of real-world projects. Typical storage system applications are grouped and classified with respect to the challenges posed to the battery system. Publicly available modeling tools for technical and economic analysis are presented. A brief analysis of optimization approaches aims to point out challenges and potential solution techniques for system sizing, positioning and dispatch operation. For all areas reviewed herein, expected improvements and possible future developments are highlighted. In order to extract the full potential of stationary battery storage systems and to enable increased profitability of systems, future research should aim to a holistic system level approach combining not only performance tuning on a battery cell level and careful analysis of the application requirements, but also consider a proper selection of storage sub-components as well as an optimized system operation strategy.
Battery energy storage systems (BESS) coupled with rooftop-mounted residential photovoltaic (PV) generation, designated as PV-BESS, draw increasing attention and market penetration as more and more such systems become available. The manifold BESS deployed to date rely on a variety of different battery technologies, show a great variation of battery size, and power electronics dimensioning. However, given today’s high investment costs of BESS, a well-matched design and adequate sizing of the storage systems are prerequisites to allow profitability for the end-user. The economic viability of a PV-BESS depends also on the battery operation, storage technology, and aging of the system. In this paper, a general method for comprehensive PV-BESS techno-economic analysis and optimization is presented and applied to the state-of-art PV-BESS to determine its optimal parameters. Using a linear optimization method, a cost-optimal sizing of the battery and power electronics is derived based on solar energy availability and local demand. At the same time, the power flow optimization reveals the best storage operation patterns considering a trade-off between energy purchase, feed-in remuneration, and battery aging. Using up to date technology-specific aging information and the investment cost of battery and inverter systems, three mature battery chemistries are compared; a lead-acid (PbA) system and two lithium-ion systems, one with lithium-iron-phosphate (LFP) and another with lithium-nickel-manganese-cobalt (NMC) cathode. The results show that different storage technology and component sizing provide the best economic performances, depending on the scenario of load demand and PV generation.
Due to their decreasing cost, lithium-ion batteries (LiB) are becoming increasingly attractive for grid-scale applications. In this paper, we investigate the use of LiB for providing secondary reserve and show how the achieved cost savings could be increased by using model-based optimization techniques. In particular, we compare a maximum use dispatch strategy with two different cost-minimizing strategies. For the estimation of state-dependent battery usage cost, we combine an existing electro-thermal LiB model of a mature lithium-iron-phosphate battery cell with corresponding semiempirical calendar and cycle aging models. We estimate the benefit of storage operation from the system operator's point of view by gauging the avoided cost of activated reserve. Our evaluation is based on two years worth of data from the German reserve market. The proposed cost minimizing dispatch strategies yield significantly better results than a dispatch strategy that maximizes battery utilization.
This article proposes a basic concept for the multi-use of stationary battery storage systems with multiple stakeholders to improve the economic value of battery storage systems. An auction market is suggested, where segments of the energy storage system and rights of use are auctioned. The blockchain technology is incorporated to develop a generic, low-cost concept that enables distinct obligations between the stakeholders caused by the technical operation of the battery storage system. Smart contracts allow flexible sharing of the battery storage system and increase the system’s utilization ratio in the presence of prediction uncertainties.
Assessment of residential battery storage systems and operation strategies considering battery aging
(2020)
With the increasing popularity of combining residential photovoltaic systems with battery storages, research, industry, and customers look for ways to determine if such an investment is economically profitable. Simulation programs may serve to predict the profitability and lifetime of the system. In this paper, we use techno-economic analysis with a specific account of battery degradation to determine profitability and lifetime of a residential photovoltaic (PV) battery system under different energy management and tariff regimes. This work presents two case studies: the first being a techno-economic comparison for a residential PV-battery system in New South Wales, Australia and Germany, and the second analyzing the profitability and degradation impact of three different operation strategies for a battery storage in Australia. The results reveal that site-specific conditions (i.e., geographical and energy-economic constraints) may have a significant impact on the ideal system configuration and ultimately the anticipated battery lifetime. Furthermore, statistical analysis of different storage operation strategies applied to various prosumer load and generation profiles reveals the effects of storage dispatch strategies on battery aging.
The rapid decentralization of energy generation and storage facilitates an opportunity to redesign existing energy systems. Here, peer-to-peer energy trading in local markets offers advantages for demand response and flexibility of energy delivery, yet it still faces problems of customer acceptance, namely, concerns over sharing control of batteries and the degradation impacts of increased cycles. To help overcome these hurdles, this research develops a techno-economic model that optimizes the interplay between peer-to-peer trading and energy management systems in a community. The model distinguishes between two decision making approaches in a local electricity market: decentral, where the household retains full control over its storages, and central, where the flexibilities are fully leveraged to maximize the community benefit. Both approaches demonstrate the significant monetary benefit of peer-to-peer trading, with the central approach reaching the greatest profitability potential. Negative effects on the battery lifetime only occur in the central case with bidirectional vehicles, and the degradation is comparatively slight.
Driven by the need for a sustainable energy transition and a paradigm shift in the energy and mobility sectors, the popularity of electric vehicles is on the rise. Learning curve effects and falling investment costs further accelerate the deployment of electric vehicles with lithium-ion batteries; and as a multi-purpose technology, they are predestined for serving multiple applications. In this work we present an electric vehicle multi-use approach for a German commercial electricity consumer with an electric vehicle fleet. We analyze which behind-the-meter and in front-of-the-meter applications are particularly suitable for electric vehicles from a techno-economic point of view. In addition to providing the mobility service, we investigate the applications self-consumption increase, peak shaving, frequency regulation, and spot market trading. For the implementation of the approach, we introduce a model predictive control framework in which a mixed-integer linear programming algorithm is combined with a semi-empirical degradation model. The approach is analyzed with the investigation of fleet sizes from 1 to 150 vehicles, different application combinations, possible energy shift between the energy partitions, bidirectional charging schemes, and degradation awareness formulations. The results show that the deployment flexibility and application synergies increase with the number of stacked services, leading to additional annual cash flows of up to 2224 EUR per electric vehicle as well as battery lifetime improvements.
Unlocking the Potential of Battery Storage With the Dynamic Stacking of Multiple Applications
(2020)
The ability of a battery energy storage system (BESS) to serve multiple applications makes it a promising technology to enable the sustainable energy transition. However, high investment costs are a considerable barrier to BESS deployment, and few profitable application scenarios exist at present. Here, we show that by tapping into multiple revenue streams using the dynamic stacking of applications, profitable operation is viable under current regulatory conditions. We develop a multi-use optimization framework which distinguishes between behind-the-meter and in-front-of-the-meter applications and considers how power capacity is allotted in addition to energy capacity allocation. The algorithm uses a rolling horizon optimization with an integrated degradation model and is fed with real-world data from a stationary lithium-ion battery in Germany. When combining peak shaving with frequency containment reserve, a net present value per Euro invested of 1.00 is achieved, and 1.24 with the addition of arbitrage trading on the intraday continuous market.
In the context of the increased acceptance and usage of electric vehicles (EVs), vehicle-to-building (V2B) has proven to be a new and promising use case. Although this topic is already being discussed in literature, there is still a lack of experience on how such a system, of allowing bidirectional power flows between an EV and building, will work in a residential environment. The challenge is to optimize the interplay of electrical load, photovoltaic (PV) generation, EV, and optionally a home energy storage system (HES). In total, fourteen different scenarios are explored for a German household. A two-step approach is used, which combines a computationally efficient linear optimizer with a detailed modelling of the non-linear effects on the battery. The change in battery degradation, storage system efficiency, and operating expenses (OPEX) as a result of different, unidirectional and bidirectional, EV charging schemes is examined for both an EV battery and a HES. The simulations show that optimizing unidirectional charging can improve the OPEX by 15%. The addition of V2B leads to a further 11% cost reduction, however, this corresponds with a 12% decrease in EV battery lifetime. Techno-economic analysis reveals that the V2B charging solution with no HES leads to strong self-consumption improvements (EUR 1381 savings over ten years), whereas, this charging scheme would not be justified for a residential prosumer with a HES (only EUR 160 savings).
Self-consumption of household photovoltaic (PV) storage systems has become profitable for residential owners under the trends of limited feed-in power and decreasing PV feed-in tariffs. For individual PV-storage systems, the challenge mainly lies in managing surplus generation of battery and grid power flow, ideally without relying on error-prone forecasts for both generation and consumption. Considering the large variation in power profiles of different houses in a neighborhood, the strategy is also supposed to be beneficial and applicable for the entire community. In this study, an adaptable battery charging control strategy is designed in order to obtain minimum costs for houses without any meteorological or load forecasts. Based on fuzzy logic control (FLC), battery state-of-charge (SOC) and the variation of SOC (∆SOC) are taken as input variables to dynamically determine output charging power with minimum costs. The proposed FLC-based algorithm benefits from the charging battery as much as possible during the daytime, and meanwhile properly preserves the capacity at midday when there is high possibility of curtailment loss. In addition, due to distinct power profiles in each individual house, input membership functions of FLC are improved by particle swarm optimization (PSO) to achieve better overall performance. A neighborhood with 74 houses in Germany is set up as a scenario for comparison to prior studies. Without forecasts of generation and consumption power, the proposed method leads to minimum costs in 98.6% of houses in the community, and attains the lowest average expenses for a single house each year.
SimSES: A holistic simulation framework for modeling and analyzing stationary energy storage systems
(2022)
The increasing feed-in of intermittent renewable energy sources into the electricity grids worldwide is currently leading to technical challenges. Stationary energy storage systems provide a cost-effective and efficient solution in order to facilitate the growing penetration of renewable energy sources. Major technical and economical challenges for energy storage systems are related to lifetime, efficiency, and monetary returns. Holistic simulation tools are needed in order to address these challenges before investing in energy storage systems. One of these tools is SimSES, a holistic simulation framework specialized in evaluating energy storage technologies technically and economically. With a modular approach, SimSES covers various topologies, system components, and storage technologies embedded in an energy storage application. This contribution shows the capabilities and benefits of SimSES by providing in-depth knowledge of the implementations and models. Selected functionalities are demonstrated, with two use cases showing the easy-to-use simulation framework while providing detailed technical analysis for expert users. Hybrid energy storage systems consisting of lithium-ion and redox-flow batteries are investigated in a peak shaving application, while various system topologies are analyzed in a frequency containment reserve application. The results for the peak shaving case study show a benefit in favor of the hybrid system in terms of overall cost and degradation behavior in applications that have a comparatively low energy throughput during lifetime. In terms of system topology, a cascaded converter approach shows significant improvements in efficiency for the frequency containment reserve application.