A Control Algorithm for a Heterogeneous Virtual Battery Storage Providing FCR Power - Schlund, Jonas; German, Reinhard (Proceedings of the 2017 International Conference on Smart Grid and Smart Cities, 2017)
We consider a virtual battery energy storage consisting of individual storage systems used for both, maximization of household PV-power own-consumption and provision of frequency containment reserve power. The frequency containment reserve power provision is managed by a central controller by setting benchmarks for each individual storage and also autonomously by each individual system based on the frequency deviation to its nominal value. In previous work, we showed that in such a system, a uniform frequency containment reserve power dispersion to all individual storage systems causes high losses due to the bad efficiency of the rectifiers in low part-load operation and that this issue can be solved by only using subsets of the virtual battery energy storage for frequency containment reserve power provision. This paper suggests a generalized control algorithm, which is also applicable in systems with heterogeneous individual storages and can easily be parametrized and utilized in different systems. We show analytically that the algorithm disperses the power in a way that each participating unit operates close to the optimal operating point no matter the power limits and energy contents of the individual storages. We also show in detailed simulations that this new algorithm works better than the previously proposed one in case of homogeneous systems.
Keywords: frequency containment reserve power; virtual battery energy storage; decentralized energy systems; efficiency; photovoltaic own-consumption

A distributed ledger based platform for community-driven flexibility provision - Schlund, Jonas; German, Reinhard (Energy Informatics, 2019)
In this paper we propose and analyze a community-driven platform for flexibility provision based on a distributed ledger. We introduce and analyze the platform for the use case of a self-organized decentralized virtual power plant consisting of a local community of individual prosumers with photovoltaic-storages located on a low voltage feeder. Like a virtual power plant, it aggregates small-scale assets and is able to provide ancillary services in the form of active power provision to the electrical power system. However, the decentralized virtual power plant provides a direct flexibility market access of the distributed assets without the need for a third party. Thus, balancing group managers or system operators can directly interact with the distributed assets in an aggregated way without the need for an aggregator. The solution approach uses a heuristic algorithm for the coordination combined with a distributed ledger and democratic consensus within the community.
Keywords: Flexibility platform; Virtual power plant; Community energy; Ancillary services; Blockchain; Smart contract; Photovoltaics; Battery systems

Analyzing the Charging Flexibility Potential of Different Electric Vehicle Fleets Using Real-World Charging Data - Barthel, Vincent; Schlund, Jonas; Landes, Philipp; Brandmeier, Veronika; Pruckner, Marco (Energies, 2021)
A successful transformation of the energy and transportation sector is one of the main targets for our society today. Battery electric vehicles can play a key role in future renewable-based energy supply systems because of their ability to store electrical power. Additionally, they provide significant charging flexibility due to the long parking durations. In this paper, we provide insights into the temporal and power-specific flexibility behavior of three different vehicle fleets. These fleets are pool vehicles of office employees, a public authority, and a logistics company. Several parameters, such as the average charging power per charging event or the average plug-in duration per charging event, are discussed. Additionally, we investigate different charging rates and their impact on the temporal flexibility of the charging events. The data analysis shows that the logistics site has the most homogeneous charging profile as well as high charging flexibility, in contrast to the office and public agency site. The results are of significant importance for future applications in the field of smart charging and ancillary services provision.
CRIS-Team WoS Importer:2021-09-10
Keywords: electric vehicles; vehicle grid integration; charging flexibility; data analysis; optimization; smart charging

Benefits of Virtual Community Energy Storages compared to Individual Batteries based on Behaviour Based Synthetic Load Profiles - Schlund, Jonas; Pflugradt, Noah; Steber, David; Muntwyler, Urs; German, Reinhard (Proceedings of the 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe), 2018)
This paper focuses on a low-voltage grid area consisting of 500 distributed households with both photovoltaics and a battery. If every household focuses only on its self-consumption, the batteries run inefficiently and the grid is stressed unnecessarily. Thus, the batteries within the considered area are connected to form a virtual community energy storage. To simulate such an environment, individual and realistic load profiles for each household are needed. This paper presents a novel, behavior based load profile generator to get such profiles. It is shown that these profiles aggregate to the German standardized load profile H0. An already existing simulation model of decentralized households is adapted in order to include community controllers, which aggregate and distribute the corresponding power flows in order to run the batteries efficiently and avoid unnecessary power flows. The whole low-voltage grid area is simulated for various community sizes within the area. Utilizing community power leads to a better overall efficiency, a decrease in the workload of the grid and a higher self-sufficiency within the considered area. These benefits can already be achieved at small community sizes.<br

Blockchain-based orchestration of distributed assets in electrical power systems - Schlund, Jonas (Energy Informatics, 2018)
For historical reasons, power systems are designed, controlled and operated centrally. A coordination of the rising number of increasingly heterogeneous, small-scale and citizen- or company-owned assets is not possible with this approach, especially not in the distribution system. The goal of the PhD project presented in this extended abstract is to find out how well distributed approaches perform in orchestrating distributed assets in future power systems from a holistic point of view in comparison to centralized approaches. The research questions are defined and the planned methodology of the project is presented. The most promising use cases in this context are identified, the concept of a decentralized virtual power plant is proposed as a new use case for providing flexibility with small-scale assets and the first ideas for an evaluation framework are presented. Next steps in the project are refining the evaluation framework and evolving the yet existing lab setups. Once these are completed, simulation models can be developed and the main research questions can be answered in detail.
Keywords: Decentralized power supply; Distributed ledger technology; Blockchain; Cellular concept; Renewable energies

Coordinating E-Mobility Charging for Frequency Containment Reserve Power Provision - Schlund, Jonas; Steinert, Ronny; Pruckner, Marco (Proceedings of the Ninth International Conference on Future Energy Systems, 2018)
In this paper we present a novel approach of coordinating battery electric vehicle charging processes as an ancillary service for the grid. This concept enables a mass integration of battery electric vehicles into the electrical power system and mobilizes flexibility options for large scale frequency stability. Therefore we consider and simulate a virtual power plant consisting of 65 private and optionally according public charging stations. The object oriented model includes a stochastic availability model based on publicly available data, a routing model of battery electric vehicles, a model for the electricity consumption and the battery and a model for the charging stations with different charging plans. These charging stations are controlled by an adapted version of a previously developed virtual power plant controller. Our extensive simulations show, that such a system consisting of private charging stations is able to provide frequency containment reserve power in a trustworthy way if either provided with back-up power by stationary batteries or supported by public charging stations. For offering 1MWfrequency containment reserve power in total and 1.5 kW per vehicle, 25 kW of back-up power is necessary. In this case the participating 667 battery electric vehicles need to perform an additional equivalent annual mileage of 1573 km in average.
Keywords: ancillary services; battery electric vehicles; bidirectional charging stations; frequency containment reserve power; vehicle-to-grid

Development and Evaluation of a Smart Charging Strategy for an Electric Vehicle Fleet Based on Reinforcement Learning - Tuchnitz, Felix; Ebell, Niklas; Schlund, Jonas; Pruckner, Marco (Applied Energy, 2021)
Governments are currently subsidizing growth in the electric car market and the associated infrastructure in order to accelerate the transition to more sustainable mobility. To avoid the grid overload that results from simultaneously charging too many electric vehicles, there is a need for smart charging coordination systems. In this paper, we propose a charging coordination system based on Reinforcement Learning using an artificial neural network as a function approximator. Taking into account the baseload present in the power grid, a central agent creates forward-looking, coordinated charging schedules for an electric vehicle fleet of any size. In contrast to optimization-based charging strategies, system dynamics such as future arrivals, departures, and energy consumption do not have to be known beforehand. We implement and compare a range of parameter variants that differ in terms of the reward function and prioritized experience. Subsequently, we use a case study to compare our Reinforcement Learning algorithm with several other charging strategies. The Reinforcement Learning-based charging coordination system is shown to perform very well. All electric vehicles have enough energy for their next trip on departure and charging is carried out almost exclusively during the load valleys at night. Compared with an uncontrolled charging strategy, the Reinforcement Learning algorithm reduces the variance of the total load by 65%. The performance of our Reinforcement Learning concept comes close to that of an optimization-based charging strategy. However, an optimization algorithm needs to know certain information beforehand, such as the vehicle’s departure time and its energy requirement on arriving at the charging station. Our novel Reinforcement Learning-based charging coordination system therefore offers a flexible, easily adaptable, and scalable approach for an electric vehicle fleet under realistic operating condition
Keywords: Machine Learning; Reinforcement Learning; Electric vehicle; Smart charging; Valley filling; Load balancing

ETHome: Open-source Blockchain Based Energy Community Controller - Schlund, Jonas; Ammon, Lorenz; German, Reinhard (Proceedings of the Ninth International Conference on Future Energy Systems, 2018)
This paper describes the proof of concept of a blockchain based organization of a local low voltage energy community. The focus of the concept is efficient use of shared resources to minimize external dependence, and not energy trading. A previously proposed control algorithm, which exploits the power dependency of the efficiency of electrical energy storages, is implemented as a smart contract on a private instance of an Ethereum blockchain to coordinate the operation. It is implemented using four connected Raspberry Pis representing the participating households with pre-given electrical load and photovoltaic conversion as well as a battery. Each household runs an Ethereum full node and an interfacing software. Only the energy technology components are simulated, while the blockchain is actually running on the Raspberry Pis in order to mind the full complexity of the technology. %As consensus algorithms both proof-of-work and the more energy-efficient proof-of-authority are compared. The practicability is proved in a test run and positive effects on the efficiency and the self-sufficiency within the community are observed. A first cost-benefit estimate is given and a further research agenda is presented.
Keywords: battery efficiency; blockchain; energy community; open-source

FlexAbility - Modeling and Maximizing the Bidirectional Flexibility Availability of Unidirectional Charging of Large Pools of Electric Vehicles - Schlund, Jonas; Pruckner, Marco; German, Reinhard (Proceedings of the Eleventh ACM International Conference on Future Energy Systems, 2020)
We propose a new methodology for modeling flexibility availability (FlexAbility) of decentralized electric loads, e.g., electric vehicle charging, with an intuitive visualization method. The approach includes a novel method for aggregating and disaggregating flexibility that is more accurate and less complex than existing approaches. In addition, it is suitable for online flexibility determination and dispatch. It is the first which enables to consider a total energy constraint per individual load. We enable the determination of guaranteed aggregated FlexAbility over a time horizon by means of calculating flexibility dispatch paths. We then propose a method for maximizing the bidirectional power flexibility of unidirectional charging for generic applications in the power grid. We combine both new methods in a simulation model of electric vehicles with realistic mobility behavior.We are the first to provide an evaluation of the bidirectional power flexibility from unidirectional charging of electric vehicles, which is found to be bounded by the minimal capability to decrease charging power. We show that there is a trade-off between power and energy flexibility. Today, 20 thousand of the typical electric vehicles in Germany are able to keep bidirectional power flexibility of at least 1.3 MW available during a whole year. The general modeling approach is applicable for other flexible loads with flexible profiles and a total energy constraint as wel
Keywords: flexibility; electric vehicles; simulation; smart charging

Flexibles Laden: Wie Elektrofahrzeuge Treiber der Energiewende werden können - Schlund, Jonas; Pruckner, Marco; German, Reinhard (2019)

Including a virtual battery storage into thermal unit commitment - Steber, David; Pruckner, Marco; Schlund, Jonas; Bazan, Peter; German, Reinhard (Computer Science - Research and Development, 2017)
UnivIS-Import:2017-12-18:Pub.2017.tech.IMMD.IMMD7.includ
Keywords: CO_22emissions; Distributed generation management; Energy networks; Grid integration of storage; Virtual battery storage; Virtual power plant

Increasing the Efficiency of a Virtual Battery Storage Providing Frequency Containment Reserve Power by Applying a Clustering Algorithm - Schlund, Jonas; Steber, David; Bazan, Peter; German, Reinhard (Proceedings of the 7th Innovative Smart Grid Technologies Asia, 2017)
We consider a virtual battery energy storage consisting of individual storage systems used for both, maximization of household PV-power self-consumption and provision of frequency containment reserve power. A central controller manages the frequency containment reserve power provision by setting benchmarks for each individual storage every 15 minutes. The individual storage systems provide frequency containment reserve power autonomously based on the frequency deviation to its nominal value and the given benchmark. A uniform frequency containment reserve power dispersion to all individual storage systems causes marginal power requests most of the time, which lead to high losses due to the bad efficiency of the rectifiers in low part-load operation. Therefore, this paper suggests an algorithm for only using subsets of the virtual battery energy storage with a certain amount of individual systems for frequency containment reserve power provision (“clustering”). The algorithm aims at improving the efficiency and is able to reduce both the charging and the discharging losses by more than 10 percentage points. In addition it balances the states of charge of the individual storages and increases the self-consumption of PV-power of the households. These results are derived from detailed simulations of the system.
Keywords: frequency containment reserve power; virtual battery energy storage; clustering; efficiency; photovoltaic self-consumption

Investigation, modeling and simulation of redox-flow, lithium-ion and lead-acid battery systems for home storage applications - Schlund, Jonas; Betzin, Christopher; Wolfschmidt, Holger; Veerashekar, Kishan; Luther, Matthias (Proceedings of the 11th International Renewable Energy Storage Conference (IRES 2017), 2017)
In this paper three different storage system solutions were investigated, modeled and simulated in order to describe their operational behavior and benefits for home storage applications. A redox-flow, a lithium-ion and a lead-acid battery were connected via converters with the grid. Their total performance was analyzed and correlations between the efficiency and the power as well as the performance limits and the state of charge were determined by the means of test runs. The real capacity and the losses of all single components were ascertained in the laboratory. Hence, the results of the measurements represent a quantified assessment of the state-of-the art of storage technologies. On the basis of the test results mathematical models of the storage systems were developed. They reproduce the influences of the different components separately and are capable of being parameterized and scaled within certain limits of power and energy content. The models were validated by the means of a five-day experiment and reached an accuracy of prediction with a mistake of an upper bound of 3.3 % in average for the three different systems. The operation of the storage systems in a private household with a photovoltaic system was simulated over one year with the developed models. The average efficiency factors reach approximately 53 % (redox-flow), 72 % (lithiumion) and 67 % (lead acid). The simulations showed that the self-sufficiency-rate and the self-consumption-rate can be improved to 60 % and 45 % respectively at the given setup of a 5 kWp photovoltaic system and a usable battery capacity of 8 kW
Keywords: energy storage; pv home storage; battery; redox-flow; lithium-ion

MiniDES - Lightweight Python Simulation Framework for Interconnected Renewable Resources - Schlund, Jonas; Reisenweber, Julian; German, Reinhard (Proceedings of the IEEE Green Energy and Smart Systems Conference 2019, 2019)
Photovoltaic systems and battery storages are increasingly installed on distribution feeders. As the digitization of the grid evolves, collective control paradigms of distributed assets become possible. The proposed simulator MiniDES is a generic python framework to model and interconnect such distributed assets in flexible control scenarios and modular simulation setups. An integrated aggregator model allows for versatile queries, different state-dependent control setups as well as postprocessing all data obtained during simulation. The framework is available as open source, portable and offers a template with household scenarios to build upon. In addition, the simulator can easily be coupled with the electric power system simulator OpenDSS in order to include a power flow analysis. An exemplary case study collectively optimizes the inverter power of a 20 household community, each with a rooftop photovoltaic plant and a battery, and achieves loss savings of 33% as well as considerable increases in self-sufficiency in comparison to the individual control case. The according power flow analysis showed that the increased line losses caused by the increased grid utilization of the collective control case are negligible compared to the loss savings. In addition, our simulation shows that the beneficial community control is economically infeasible with a conventional price mechanism and that economic feasibility can be achieved by introducing a more dynamic price mechanis
Keywords: renewable energy; smart grid; simulation framework; solar power; energy storage; optimization

Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids - Spitzer, Martin; Schlund, Jonas; Apostolaki-Iosifidou, Elpiniki; Pruckner, Marco (Energies, 2019)
All over the world the reduction of greenhouse gas (GHG) emissions, especially in the transportation sector, becomes more and more important. Electric vehicles will be one of the key factors to mitigate GHG emissions due to their higher efficiency in contrast to internal combustion engine vehicles. On the other hand, uncoordinated charging will put more strain on electrical distribution grids and possible congestions in the grid become more likely. In this paper, we analyze the impact of uncoordinated charging, as well as optimization-based coordination strategies on the voltage stability and phase unbalances of a representative European semi-urban low voltage grid. Therefore, we model the low voltage grid as a three-phase system and take realistic arrival and departure times of the electric vehicle fleet into account. Subsequently, we compare different coordinated charging strategies with regard to their optimization objectives, e.g., cost reduction or GHG emissions reduction. Results show that possible congestion problems can be solved by coordinated charging. Additionally, depending on the objective, the costs can be reduced by more than 50% and the GHG emissions by around 40%.

Reinforcement Learning Control Algorithm for a PV-Battery-System Providing Frequency Containment Reserve Power - Ebell, Niklas; Heinrich, Felix; Schlund, Jonas; Pruckner, Marco (2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 2018)
Rooftop-installed photovoltaic systems for residential buildings with battery energy storage system are increasing. Controlling power flows of volatile and unpredictable renewable energy sources in such a system is challenging. Therefore, in this paper we present an algorithm based on Reinforcement Learning to control the power flows of a residential household with a battery energy storage system and a photovoltaic system using neural networks as a function approximation. In a nondeterministic environment the optimal choice of a series of actions to be taken is complex. Training a Reinforcement Learning algorithm, these complex patterns can be learned. The task of the energy storage is to reduce the energy feedin to the electric grid as well as to improve power system stability by providing frequency containment reserve power to the transmission system operator. Our model includes the profiles of the grid’s frequency, photovoltaic power generation and the electric load of two different households for one year. The first household is used to train the algorithm and to adjust the weights of the neural network to estimate the state-action values. The second household is used to test the functionality of the algorithm on unseen data. To evaluate the behavior of the Reinforcement Learning algorithm the results are compared to a simulation of rule-based control. As a result, after 300 episodes of training, the algorithm is able to reduce the energy consumption from the grid up to 7:8% compared to the rule-based control system managing the system’s power flows. <br
Keywords: Reinforcement Learning; Energy Storage System; Frequency Containment Reserve Power; SARSA

Smart Charging and Renewable Grid Integration - A Case Study Based on Real-Data of the Island of Porto Santo - Strobel, Leo; Schlund, Jonas; Brandmeier, Veronika; Schreiber, Michael; Pruckner, Marco (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 2021)
The penetration of battery electric vehicles is increasing. Due to their ability to store electrical power and to shift charging events, they offer a wide range of opportunities with regard to renewable grid integration and lowering the overall CO2 emissions. This is particularly evident for isolated microgrids, such as the Portuguese island of Porto Santo. In this paper, we conduct a data analysis of real-world charging data of 20 electric vehicles operated on the island of Porto Santo. We provide insights into the charging behavior of different users and analyze the opportunity of smart charging for better renewable grid integration using linear optimization models. The data analysis shows that drivers prefer home rather than publicly available charging stations, flexible charging events occur mostly overnight and the charging flexibility of the fleet decreases over the project duration. With regard to make charging more flexible, we can see that smart charging can help to raise the share of electricity generated by renewable energy sources for charging the electric vehicles to up to 33%.
CRIS-Team Scopus Importer:2021-05-28
Keywords: Electric vehicles; Grid integration; Smart charging; Vehicle-2-Grid