TY - JOUR A1 - Rieke, Christian A1 - Stollenwerk, Dominik A1 - Dahmen, Markus A1 - Pieper, Martin T1 - Modeling and optimization of a biogas plant for a demand-driven energy supply JF - Energy N2 - Due to the Renewable Energy Act, in Germany it is planned to increase the amount of renewable energy carriers up to 60%. One of the main problems is the fluctuating supply of wind and solar energy. Here biogas plants provide a solution, because a demand-driven supply is possible. Before running such a plant, it is necessary to simulate and optimize the process. This paper provides a new model of a biogas plant, which is as accurate as the standard ADM1 model. The advantage compared to ADM1 is that it is based on only four parameters compared to 28. Applying this model, an optimization was installed, which allows a demand-driven supply by biogas plants. Finally the results are confirmed by several experiments and measurements with a real test plant. Y1 - 2018 U6 - http://dx.doi.org/10.1016/j.energy.2017.12.073 SN - 0360-5442 VL - 145 SP - 657 EP - 664 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Rupp, Matthias A1 - Handschuh, Nils A1 - Rieke, Christian A1 - Kuperjans, Isabel T1 - Contribution of country-specific electricity mix and charging time to environmental impact of battery electric vehicles: A case study of electric buses in Germany JF - Applied Energy Y1 - 2019 U6 - http://dx.doi.org/10.1016/j.apenergy.2019.01.059 SN - 0306-2619 VL - 237 SP - 618 EP - 634 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Dotzauer, Martin A1 - Pfeiffer, Diana A1 - Lauer, Markus A1 - Pohl, Marcel A1 - Mauky, Eric A1 - Bär, Katharina A1 - Sonnleitner, Matthias A1 - Zörner, Wilfried A1 - Hudde, Jessica A1 - Schwarz, Björn A1 - Faßauer, Burkhardt A1 - Dahmen, Markus A1 - Rieke, Christian A1 - Herbert, Johannes A1 - Thrän, Daniela T1 - How to measure flexibility – Performance indicators for demand driven power generation from biogas plants JF - Renewable Energy Y1 - 2019 U6 - http://dx.doi.org/10.1016/j.renene.2018.10.021 SN - 0960-1481 SP - 135 EP - 146 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Rupp, Matthias A1 - Rieke, Christian A1 - Handschuh, Nils A1 - Kuperjans, Isabel T1 - Economic and ecological optimization of electric bus charging considering variable electricity prices and CO₂eq intensities JF - Transportation Research Part D: Transport and Environment N2 - In many cities, diesel buses are being replaced by electric buses with the aim of reducing local emissions and thus improving air quality. The protection of the environment and the health of the population is the highest priority of our society. For the transport companies that operate these buses, not only ecological issues but also economic issues are of great importance. Due to the high purchase costs of electric buses compared to conventional buses, operators are forced to use electric vehicles in a targeted manner in order to ensure amortization over the service life of the vehicles. A compromise between ecology and economy must be found in order to both protect the environment and ensure economical operation of the buses. In this study, we present a new methodology for optimizing the vehicles’ charging time as a function of the parameters CO₂eq emissions and electricity costs. Based on recorded driving profiles in daily bus operation, the energy demands of conventional and electric buses are calculated for the passenger transportation in the city of Aachen in 2017. Different charging scenarios are defined to analyze the influence of the temporal variability of CO₂eq intensity and electricity price on the environmental impact and economy of the bus. For every individual day of a year, charging periods with the lowest and highest costs and emissions are identified and recommendations for daily bus operation are made. To enable both the ecological and economical operation of the bus, the parameters of electricity price and CO₂ are weighted differently, and several charging periods are proposed, taking into account the priorities previously set. A sensitivity analysis is carried out to evaluate the influence of selected parameters and to derive recommendations for improving the ecological and economic balance of the battery-powered electric vehicle. In all scenarios, the optimization of the charging period results in energy cost savings of a maximum of 13.6% compared to charging at a fixed electricity price. The savings potential of CO₂eq emissions is similar, at 14.9%. From an economic point of view, charging between 2 a.m. and 4 a.m. results in the lowest energy costs on average. The CO₂eq intensity is also low in this period, but midday charging leads to the largest savings in CO₂eq emissions. From a life cycle perspective, the electric bus is not economically competitive with the conventional bus. However, from an ecological point of view, the electric bus saves on average 37.5% CO₂eq emissions over its service life compared to the diesel bus. The reduction potential is maximized if the electric vehicle exclusively consumes electricity from solar and wind power. Y1 - 2020 U6 - http://dx.doi.org/10.1016/j.trd.2020.102293 SN - 1361-9209 VL - 81 IS - Article 102293 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Stollenwerk, Dominik A1 - Franzke, Till A1 - Maurer, Florian A1 - Reinkensmeier, Sebastian A1 - Kim, Franken A1 - Tambornino, Philipp A1 - Haas, Florian A1 - Rieke, Christian A1 - Hermanuz, Andreas A1 - Borchert, Jörg A1 - Ritz, Thomas A1 - Sander, Volker ED - Proff, Heike T1 - Smarte Ladesäulen : Netz- und Marktdienliches öffentliches Laden T2 - Towards the New Normal in Mobility : Technische und betriebswirtschaftliche Aspekte N2 - Stand 01.01.2022 sind in Deutschland 618.460 elektrisch angetriebene KFZ zugelassen. Insgesamt sind derzeit 48.540.878 KFZ zugelassen, was einer Elektromobilitätsquote von ca. 1,2 % entspricht. Derzeit werden Elektromobile über Ladestationen oder Steckdosen mit dem Stromnetz verbunden und üblicherweise mit der vollen Ladekapazität des Anschlusses aufgeladen, bis das Batteriemanagementsystem des Fahrzeugs abhängig vom Ladezustand der Batterie die Ladeleistung reduziert. Y1 - 2023 SN - 978-3-658-39437-0 (Print) SN - 978-3-658-39438-7 (Online) U6 - http://dx.doi.org/10.1007/978-3-658-39438-7_18 SP - 287 EP - 304 PB - Springer Gabler CY - Wiesbaden ER - TY - JOUR A1 - Maurer, Florian A1 - Rieke, Christian A1 - Schemm, Ralf A1 - Stollenwerk, Dominik T1 - Analysis of an urban grid with high photovoltaic and e-mobility penetration JF - Energies N2 - This study analyses the expected utilization of an urban distribution grid under high penetration of photovoltaic and e-mobility with charging infrastructure on a residential level. The grid utilization and the corresponding power flow are evaluated, while varying the control strategies and photovoltaic installed capacity in different scenarios. Four scenarios are used to analyze the impact of e-mobility. The individual mobility demand is modelled based on the largest German studies on mobility “Mobilität in Deutschland”, which is carried out every 5 years. To estimate the ramp-up of photovoltaic generation, a potential analysis of the roof surfaces in the supply area is carried out via an evaluation of an open solar potential study. The photovoltaic feed-in time series is derived individually for each installed system in a resolution of 15 min. The residential consumption is estimated using historical smart meter data, which are collected in London between 2012 and 2014. For a realistic charging demand, each residential household decides daily on the state of charge if their vehicle requires to be charged. The resulting charging time series depends on the underlying behavior scenario. Market prices and mobility demand are therefore used as scenario input parameters for a utility function based on the current state of charge to model individual behavior. The aggregated electricity demand is the starting point of the power flow calculation. The evaluation is carried out for an urban region with approximately 3100 residents. The analysis shows that increased penetration of photovoltaics combined with a flexible and adaptive charging strategy can maximize PV usage and reduce the need for congestion-related intervention by the grid operator by reducing the amount of kWh charged from the grid by 30% which reduces the average price of a charged kWh by 35% to 14 ct/kWh from 21.8 ct/kWh without PV optimization. The resulting grid congestions are managed by implementing an intelligent price or control signal. The analysis took place using data from a real German grid with 10 subgrids. The entire software can be adapted for the analysis of different distribution grids and is publicly available as an open-source software library on GitHub. KW - distribution grid simulation KW - smart-charging KW - e-mobility Y1 - 2023 U6 - http://dx.doi.org/10.3390/en16083380 SN - 1996-1073 N1 - This article belongs to the Special Issue "Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids" N1 - Corresponding author: Florian Maurer VL - 16 IS - 8 PB - MDPI CY - Basel ER -