Dr. Alexander Schuller
Alexander Schuller leitet seit Januar 2014 die Abteilung Information Management Systems (IPE-IMS) am FZI. In der Abteilung stehen insbesondere die Themen Anreizgestaltung (Prof. Christof Weinhardt) und Analytics (Prof. Thomas Setzer) in verschiedenen Domänen im Fokus der Arbeit. Darüber hinaus ist er Leiter der Forschungsgruppe Smart Grid & Energy Markets am Institut für Informationswirtschaft- und Marketing (IISM).
Vor seiner Beschäftigung am FZI studierte Alexander Schuller von 2002 - 2008 Wirtschaftsingenieurwesen mit den Schwerpunkten Informationswirtschaft und Energiewirtschaft an der Universität Karlsruhe, (TH). Seine Diplomarbeit verfasste er zum Thema: "Ein Planungsmodell zur optimalen Dimensionierung von Mikroenergienetzen" in der mittels eines gemischt ganzzahligen Optimierungsmodells die kostenoptimale Auslegung von teilautarken Netzzellen, sog. Microgrids analysiert wurde.
In der Zeit von 2009 - 2013 verfasste er seine Dissertation am IISM, am Lehrstuhl Prof. Weinhardt zum Themenbereich Ladekoordination von Elektrofahrzeugen zur Nutzung Erneuerbarer Energien. Während dieser Zeit war er auch Gastforscher in der Environmental Energy Technologies Division am Lawrence Berkeley National Laboratory.
Aktuelle Forschungs- und Projektthemen umfassen die Quantifizierung und ökonomische Bewertung von Lastverschiebepotential flexibler Lasten in dezentralen Anwendungsszenarien des Smart Grid (Quartiere, Netzzellen). Hinzu kommt die Betrachtung von Batterielebensdaueraspekten und Nutzerpräferenzen bei der Bewertung von Ladestrategien für Elektrofahrzeuge.
- Charging Coordination Paradigms of Electric VehiclesDetails
Schuller, Alexander, Springer Singapore, 2015
Zeitungs- oder Zeitschriftenartikel (6)
- Understanding user acceptance factors of electric vehicle smart chargingInfoDetails
Christian Will and Alexander Schuller, 2016
Abstract Smart charging has been the focus of considerable research efforts but so far there is little notion of users’ acceptance of the concept. This work considers potentially influential factors for the acceptance of smart charging from the literature and tests their viability employing a structural equation model, following the partial least squares approach. For a sample of 237 early electric vehicle adopters from Germany our results show that contributing to grid stability and the integration of renewable energy sources are key motivational factors for acceptance of smart charging. In addition, the individual need for flexibility should not be impaired through charging control. Further well known influential factors like economic incentives do not seem to have a significant impact in the sample group under scrutiny. These and further findings should be taken into account by aggregators when designing attractive business models that incentivize the participation of early adopters and ease market rollout.
- Quantifying Load Flexibility of Electric Vehicles for Renewable Energy IntegrationDetails
Schuller, Alexander and Flath, Christoph M. and Gottwalt, Sebastian, 2015
- Charging Strategies for Battery Electric Vehicles: Economic Benchmark and V2G PotentialDetails
Schuller, Alexander and Dietz, Benjamin and Flath, Christoph M. and Weinhardt, Christof, 2014
- E-Fahrzeugladestrategien zur Integration Erneuerbarer EnergienDetails
Hoeffer, Jan and Schuller, Alexander, 2014
- Assessing the Economic Potential of Electric Vehicles to Provide Ancillary Services: The Case of GermanyDetails
Schuller, Alexander and Rieger, Fabian, 2013
- Simulations in the Smart Grid Field Study MeRegio Simulationen im MeRegio Smart Grid FeldtestDetails
Hirsch, Christian and Hillemacher, Lutz and Block, Carsten and Schuller, Alexander and Möst, Dominik, 2010
- Mitigating Renewable Energy Generation Uncertainty by Deadline Differentiated PricingInfoDetails
Salah, Florian and Schuller, Alexander and Weinhardt Christof, 2016
Electric vehicles are an important option to enable sustainable individual mobility. In order to leverage this potential, electricity for charging of electric vehicles needs to be provided by local renewable energy sources. Information systems can enable an efficient coordination of demand and supply in this setting. Forecast errors regarding energy generation from these sources are common but can be addressed by temporal flexibility of electric vehicle charging. We use a pricing scheme called deadline differentiated pricing that incentivizes customers to accept job shifting of their charging processes. This approach is applied on a specific use case: A city car park offers charging spots for electric vehicles that is supplied by both a local photovoltaic system and conventionally from the grid. We evaluate the impact of energy generation forecast errors on operator profits based on the formulation of a stochastic mixed-integer optimization problem and empirical mobility and generation data. We show that deadline differentiated pricing is resilient to inaccurate forecasts for photovoltaic energy generation. Deadline differentiated pricing increases profits in all investigated scenarios by at least 8% as compared to a simple pricing approach. Additionally, it can increase the share of charging demand covered by renewable energy by up to 17%.
- Pricing of Demand Flexibility: Exploring the Impact of Electric Vehicle Customer DiversityInfoDetails
Salah, F. and Schuller, A. and Mauerer, M. and Weinhardt, C., 2016
Electric Vehicles (EVs) are a large, but also quite flexible load in the power system. Car parks constitute major future load clusters that need to coordinate charging requests from EVs according to local grid and supply conditions. For effective grid integration, it is necessary to understand how to influence the charging behavior of EV customers. A deadline differentiated pricing approach is employed to create incentives for EV customers to offer their load flexibility to the car park operator. We explore the effect of different utility diversity models and flexibility levels of EV customers in a car park scenario under consideration of local photovoltaic power generation. Our results indicate that a homogeneous customer utility model overestimates the car park operator profits by more than 17\% as compared to a realistic heterogeneous model. Furthermore, we observe that the car park type, and thus the customer parking time also drives the attained profits.
- Quality of Service Product Differentiation in Smart GridsDetails
Schuller, Alexander and Salah,Florian and Will, Christian and Flath, Christoph M., 2015
- Innovative Energy Product Differentiation in Smart GridsDetails
Flath, C.M. and Salah,F. and Schuller, A. and Will, C., 2015
- Assessing the Impact of EV Mobility Patterns on Renewable Energy Oriented Charging StrategiesDetails
Schuller, Alexander and Hoeffer, Jan, 2014
- Economic Evaluation of Local Photovoltaic Generation in Electric Vehicle Car ParksDetails
Steuer, Sebastian and Gärttner, Johannes and Schuller, Alexander and Schmeck, Hartmut and Weinhardt, Christof, 2014
- Assessing load flexibility in smart grids: Electric vehicles for renewable energy integrationDetails
Gottwalt, Sebastian and Schuller, Alexander and Flath, Christoph and Schmeck, Hartmut and Weinhardt, Christof, IEEE, 2013
- Renewable Energy for Electric Vehicles : Price Based Charging CoordinationDetails
Richstein, Joern C and Schuller, Alexander and Dinther, Clemens Van and Ketter, Wolfgang and Weinhardt, Christof, 2012
- Benchmarking electric vehicle charging control strategiesInfoDetails
Schuller, Alexander and Ilg, Jens and van Dinther, Clemens, IEEE, 2012
Electric vehicles (EVs) are expected to become an important part of individual mobility. In order to reduce CO2 emissions and release the full potential for sustainable mobility, EVs need to be charged with energy from renewable energy sources (RES). We employ a deterministic linear optimization approach with different coordination objectives for each simu- lation scenario. The objectives are to minimize the individual average charging costs, maximize the average use of wind power or minimize the average load factor for the charging times of each EV customer. Customers have real life driving profiles from the German mobility panel and are distinguished in employees and retired with their respective driving behavior. We find that the wind power share used for charging can be nearly doubled for both groups under the respective strategy. Average costs are increased in comparison to the cost oriented strategy but are considerably lower as in the uncoordinated charging case.
- Economic benchmark of charging strategies for battery electric vehiclesInfoDetails
Dietz, Benjamin and Ahlert, Klaus-Henning and Schuller, Alexander and Weinhardt, Christof, IEEE, 2011
This paper investigates a smart charging strategy and a Vehicle-to-Grid (V2G) strategy and benchmarks the economic benefits for the electric vehicle (EV) owner against a zero-intelligence charging strategy in a simulation-based analysis. Smart charging optimizes the timing of charging the EV and V2G additionally allows for reselling electricity to the energy market. The simulations build on more than 11,400 real driving profiles of German car drivers and the technical specification of three EVs that are currently available on the market or under field testing. This allows for a detailed and realistic analysis of when smart charging and V2G is feasible and whether EVs are suitable to fulfill the historic driving profiles. Hourly electricity prices for EV owners are simulated proportionally to wholesale market prices from the European Energy Exchange (EEX). The results show that smart charging strategies will reduce charging cost by more than 50\% in all simulated cases. V2G could provide significant revenues only for a small group of EV owners while resulting in short battery replacement cycles for these EVs.
- Assessment of Flexible Demand Response Business Cases in the Smart GridInfoDetails
Joetten, Gerrit and Weidlich, Anke and Filipova-Neumann, Lilia and Schuller, Alexander, CIRED, 2011
The purpose of this work is to assess three selected busi- ness cases in a smart grid environment that have been designed by project members of the EU co-funded SmartHouse/SmartGrid project. These cases cover ba- lancing services, demand side management and micro grid operations. Each business case and its individual technology architecture are evaluated with respect to expected costs and revenue. Results suggest that in the modeled reference scenario, there are profitable business cases and also cases which are not yet profitable under current conditions.
- Renewable Energy for Electric Vehicle Operation : A wind-power-based tariff for EV chargingInfoDetails
Schuller, Alexander and Ilg, Jens, Energy Science Center ETH Zürich, 2011
Electric vehicles (EV) are expected to replace an increasing share of internal combustion engine (ICE) vehicles in the near future. Amongst other reasons like reducing dependency on oil-producing countries, this significant change is driven by the need to emit less CO2. Therefore one main goal of this transformation of individual mobility is the use of renewable energy sources or ’green energy’ for charging EVs. We employ monetary incentives for EV owners to shift charging times into time slots of higher renewable energy infeed, i.e. wind power, in a deterministic simulation approach. For this reason we design a wind-infeed-based tariff. This tariff is applied under consideration of real life driving profiles obtained from the German mobility panel. Results show for two sociodemographic groups (employees, retired) that the usage of wind energy can be increased significantly
- The impact of charging strategies for electric vehicles on power distribution networksInfoDetails
Stroehle, Philipp and Becher, Silvio and Lamparter, Steffen and Schuller, Alexander and Weinhardt, Christof, Ieee, 2011
This work investigates four different generic charg- ing strategies for battery electric vehicles (BEVs) with respect to their economic performance and their impact on the local power distribution network of a residential area in southern Germany. The charging strategies are Simple Charging (uncontrolled), Smart Charging (cost minimal), Vehicle to Grid Charging (V2G) and Heuristic V2G Charging. The simulation setting includes a high share of local renewable generation as well as typical residential load patterns to which different penetration levels of BEVs are added for the evaluation. Prices are determined on a regional energy market with agents representing the participating households (including PV generation and BEVs) as well as the traditional supply for the local power distribution network via the point of common coupling (PCC). Results show that Smart and V2G Charging lead to cost reductions for electric mobility of 40 \% or 75\% respectively per week and household. At the same time additional stress is put on the distribution network which shows a need for further coordination of BEV charging.
- Marktintegration der Elektromobilität : Ein agentenbasierter Ansatz für das Smart GridInfoDetails
Schuller, Alexander, 2010
Dieser Beitrag geht auf die Möglichkeiten zur Marktintegration von Elek- trofahrzeugen im Rahmen einer kompetitiven Agentensimulation ein. Es werden die Entscheidungsprobleme eines EV-Brokers welcher eine Flotte von E-Fahrzeugen über Preissignale in ihrem Ladeverhalten beeinflussen kann, im Rahmen eines regionalen Handelsszenarios beschrieben. Die notwendigen Kompetenzen bezüglich Tarifgestal- tung und Optimierungsverfahren werden angesprochen und es wird auf weiterführende Arbeiten im Rahmen der Trading-Agent-Competition (TAC) Energy verwiesen.
- Electric Vehicle Charging Coordination - Economics of Renewable Energy IntegrationInfoDetails
Schuller, Alexander, 2013
This work investigates the potential application of EV load flexibility with respect to different coordination objectives. They include individual cost or conventional generator use minimization, given volatile supply from renewable sources. The evaluation shows that charging coordination can generate savings and increase the direct utilization of renewable energy sources. Allowing for resale of stored energy to the grid can further increase savings but is limited by battery wear conditions.
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- Charging Coordination Paradigms of Electric VehiclesDetails