• Energy Research

Abstract The number of households with photovoltaic battery storage systems is steadily growing, and so is the number of heat pump installations. An integrated home combines domestic battery systems and a heat pump for power-to-heat coupling. During winter, storage systems in an integrated home are not used to their full capacity due to low solar radiation. This potential can be used to enhance the economics by applying a dual-use scheme. In this publication, an integrated home that participates in the frequency control reserve market is investigated. A major advantage of integrated homes with power-to-heat coupling in comparison to standalone battery storages is the additional flexibility to absorb negative control reserve power in the heating sector. Seasonal variation of feed-in from photovoltaics is considered by an advanced strategy for variable provision of control reserve. Results show that a dual-use operation with participation in the control reserve market can increase the profitability of storage systems. Market participation leads to accelerated battery aging, mainly driven by increased calendar aging. This is overcompensated by the possible incomes. Under consideration of low costs for market participation, a constant provision of at least 3 kW of reserve power could be economical. A variable provision further enhances economic efficiency.

Large-scale stationary battery energy storage systems (BESS) continue to increase in number and size. Most systems have been put into operation for grid services because of their technical capabilities. With increasing and more dynamic energy prices, their use in short-term energy trading such as day-ahead and intraday trading has also been gaining importance. In current technical and economic simulations and trading models, batteries are often used as an energy reservoir that can charge and discharge a constant power specified by the energy over a certain time. However, this simplification can lead to wrong results and makes economic assessments difficult. In order to successfully use BESS in energy trading, their real operating ranges and limits must be investigated, since batteries respectively BESS cannot deliver the same power over the entire state of charge (SOC) range. With a performance test of our hybrid BESS M5BAT, we show the characteristic performance curves for different battery technologies and consequently suitable operating ranges in a large-scale system configuration. The results show the wide range of challenges such as battery aging and balancing states that occur in the real-world implementation of BESS. The lithium-ion batteries of the system under test have a remaining usable energy between 75 % and 90 %, depending on the type of lithium-ion battery, while the usable energy of the lead acid batteries is only 60 %. The lithium-ion batteries were able to deliver a constant power output in the SOC range between 10 % and 80 %, which is a necessary requirement in short-term energy trading. The lead-acid batteries could only be discharged at full power in the range of 100 %–50 % SOC and charged at full power between 0 % and 50 %. In the performance test, balancing was a limiting factor for lithium-ion batteries, while aging was the limiting factor for lead-acid batteries. Based on our findings, estimates for other existing BESS can be made to determine feasible operating ranges of these batteries for short-term energy trading. This also provides a guideline for individual tests that should be carried out on other BESS for verification. Applied energy 347, 121428 - (2023). doi:10.1016/j.apenergy.2023.121428 Published by Elsevier Science, Amsterdam [u.a.]

Enhancing electric vehicle infrastructure by forecasting the availability of charging stations can boost the attractiveness of electric vehicles. The transportation sector plays a crucial role in battling climate change. The majority of available prediction algorithms either achieve poor accuracy or predict the availability at certain points in time in the future. Both of these situations are not ideal and may potentially hinder the model’s applicability to real-world situations. This paper provides a new model for estimating the charging duration of charging events in real time, which may be used to estimate the waiting time of users at fully occupied charging stations. First, the prediction is made using the random forest regressor (RF), and then the prediction is enhanced utilizing the findings of the RF model and real-time information of the currently occurring charging events. We compare the proposed method with the RF model, which is the approach’s foundational model, and the best-performing prediction model of the light gradient boosting machine (LightGBM). Here, we make use of historical information of charging events gathered from 2079 charging stations across Germany’s 4602 fast-charging connectors. To reduce data bias, we specifically simulate prediction requests for 30% of the charging events with various characteristics that were not trained with the model. Overall, the suggested method performs better than both the RF and the LightGBM. In addition, the model’s structure is adaptable and can incorporate real-time information on charging events.

Abstract Residential home storage systems that increase solar self-consumption are a rapidly growing market in many countries around the world. This paper provides an in-depth overview about the market and technology development of home storage systems in Germany during the years 2013–2018. Based on the scientifically collected data of more than 20,000 individual home storage systems, quantitative evaluations of user preferences and industry trends are presented. The topics include market growth, choice of battery technology, typical system design, retail price development, purchase motivation, and user satisfaction. The presented data can be used to predict international markets or act as a foundation for studies regarding technology diffusion, grid effects, and multi-use scenarios of decentralized storage systems.

Electric vehicles are booming and with them the required public charging stations. Knowing how charging stations are used is crucial for operators of the charging stations themselves, navigation systems, electricity grids, and many more. Given that there are now 2.5 as many vehicles per charging station compared to 2017, the system needs to allocate charging points intelligently and efficiently. This paper presents representative data on energy consumption, arrival times, occupation, and profitability of charging stations in Germany by combining usage data of 27,800 installations. Charging happens mainly during the day and on weekdays for AC charging stations while DC fast-charging stations are more popular on the weekend. Fast-chargers service approximately 3 times as many vehicles per connection point while also being substantially more profitable due to higher achieved margins. For AC chargers, up to 20 kWh of energy are charged in an average charge event while DC fast-chargers supply approximately 40 kWh. Paper currently under review. Please check if full paper is available before citing. Accompanying data will be published alongside the full paper

Nature energy 9(11), 1438-1447 (2024). doi:10.1038/s41560-024-01620-9 Published by Nature Publishing Group, London