TY - CHAP A1 - Kasper, Katharina A1 - Schiffels, Johannes A1 - Krafft, Simone A1 - Kuperjans, Isabel A1 - Elbers, Gereon A1 - Selmer, Thorsten T1 - Biogas Production on Demand Regulated by Butyric Acid Addition T2 - IOP Conference Series: Earth and Environmental Science. Bd. 32 Y1 - 2016 U6 - http://dx.doi.org/10.1088/1755-1315/32/1/012009 SN - 1755-1315 N1 - ICARET 2016, International Conference on Advances in Renewable Energy and Technologies, Putrajaya, MY, Feb 23-25, 2016 VL - 32 SP - 012009/1 EP - 012009/4 ER - TY - CHAP A1 - Kreyer, Jörg A1 - Esch, Thomas T1 - Simulation Tool for Predictive Control Strategies for an ORCSystem in Heavy Duty Vehicles T2 - European GT Conference 2017 N2 - Scientific questions - How can a non-stationary heat offering in the commercial vehicle be used to reduce fuel consumption? - Which potentials offer route and environmental information among with predicted speed and load trajectories to increase the efficiency of a ORC-System? Methods - Desktop bound holistic simulation model for a heavy duty truck incl. an ORC System - Prediction of massflows, temperatures and mixture quality (AFR) of exhaust gas Y1 - 2017 N1 - European GT Conference 2017, 9.-10. Oktober 2017, Frankfurt a.M. ER - TY - CHAP A1 - Kumaran, P. A1 - Gopinathan, M. A1 - Razali, N. M. A1 - Kuperjans, Isabel A1 - Hariffin, B. A1 - Hamdan, H. T1 - Preliminary evaluation of atomization characteristics of improved biodiesel for gas turbine application T2 - IOP Conference Series: Earth and Environmental Science (EES) Y1 - 2013 U6 - http://dx.doi.org/10.1088/1755-1315/16/1/012014 SN - 1755-1315 VL - 16 IS - 1 SP - 012014/1 EP - 012014/4 PB - Institute of Physics Publishing (IOP) CY - London [u.a.] ER - TY - CHAP A1 - Maurer, Florian A1 - Miskiw, Kim K. A1 - Acosta, Rebeca Ramirez A1 - Harder, Nick A1 - Sander, Volker A1 - Lehnhoff, Sebastian ED - Jorgensen, Bo Norregaard ED - Pereira da Silva, Luiz Carlos ED - Ma, Zheng T1 - Market abstraction of energy markets and policies - application in an agent-based modeling toolbox T2 - EI.A 2023: Energy Informatics N2 - In light of emerging challenges in energy systems, markets are prone to changing dynamics and market design. Simulation models are commonly used to understand the changing dynamics of future electricity markets. However, existing market models were often created with specific use cases in mind, which limits their flexibility and usability. This can impose challenges for using a single model to compare different market designs. This paper introduces a new method of defining market designs for energy market simulations. The proposed concept makes it easy to incorporate different market designs into electricity market models by using relevant parameters derived from analyzing existing simulation tools, morphological categorization and ontologies. These parameters are then used to derive a market abstraction and integrate it into an agent-based simulation framework, allowing for a unified analysis of diverse market designs. Furthermore, we showcase the usability of integrating new types of long-term contracts and over-the-counter trading. To validate this approach, two case studies are demonstrated: a pay-as-clear market and a pay-as-bid long-term market. These examples demonstrate the capabilities of the proposed framework. KW - Energy market design KW - Agent-based simulation KW - Market modeling Y1 - 2023 SN - 978-3-031-48651-7 (Print) SN - 978-3-031-48652-4 (eBook) U6 - http://dx.doi.org/10.1007/978-3-031-48652-4_10 N1 - Energy Informatics Academy Conference, 6-8 December 23, Campinas, Brazil. N1 - Part of the Lecture Notes in Computer Science book series (LNCS,volume 14468). SP - 139 EP - 157 PB - Springer CY - Cham 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 - TY - CHAP A1 - Nierle, Elisabeth A1 - Pieper, Martin T1 - Measuring social impacts in engineering education to improve sustainability skills T2 - European Society for Engineering Education (SEFI) N2 - In times of social climate protection movements, such as Fridays for Future, the priorities of society, industry and higher education are currently changing. The consideration of sustainability challenges is increasing. In the context of sustainable development, social skills are crucial to achieving the United Nations Sustainable Development Goals (SDGs). In particular, the impact that educational activities have on people, communities and society is therefore coming to the fore. Research has shown that people with high levels of social competence are better able to manage stressful situations, maintain positive relationships and communicate effectively. They are also associated with better academic performance and career success. However, especially in engineering programs, the social pillar is underrepresented compared to the environmental and economic pillars. In response to these changes, higher education institutions should be more aware of their social impact - from individual forms of teaching to entire modules and degree programs. To specifically determine the potential for improvement and derive resulting change for further development, we present an initial framework for social impact measurement by transferring already established approaches from the business sector to the education sector. To demonstrate the applicability, we measure the key competencies taught in undergraduate engineering programs in Germany. The aim is to prepare the students for success in the modern world of work and their future contribution to sustainable development. Additionally, the university can include the results in its sustainability report. Our method can be applied to different teaching methods and enables their comparison. KW - Social impact measurement KW - Key competences KW - Sustainable engineering education KW - Future skills Y1 - 2023 U6 - http://dx.doi.org/10.21427/QPR4-0T22 N1 - 51st Annual Conference of the European Society for Engineering Education (SEFI) N1 - Corresponding Author: Elisabeth Nierle ER - TY - JOUR A1 - Nobis, Moritz A1 - Schmitt, Carlo A1 - Schemm, Ralf A1 - Schnettler, Armin T1 - Pan-European CVAR-constrained stochastic unit commitment in day-ahead and intraday electricity markets JF - Energies N2 - The fundamental modeling of energy systems through individual unit commitment decisions is crucial for energy system planning. However, current large-scale models are not capable of including uncertainties or even risk-averse behavior arising from forecasting errors of variable renewable energies. However, risks associated with uncertain forecasting errors have become increasingly relevant within the process of decarbonization. The intraday market serves to compensate for these forecasting errors. Thus, the uncertainty of forecasting errors results in uncertain intraday prices and quantities. Therefore, this paper proposes a two-stage risk-constrained stochastic optimization approach to fundamentally model unit commitment decisions facing an uncertain intraday market. By the nesting of Lagrangian relaxation and an extended Benders decomposition, this model can be applied to large-scale, e.g., pan-European, power systems. The approach is applied to scenarios for 2023—considering a full nuclear phase-out in Germany—and 2035—considering a full coal phase-out in Germany. First, the influence of the risk factors is evaluated. Furthermore, an evaluation of the market prices shows an increase in price levels as well as an increasing day-ahead-intraday spread in 2023 and in 2035. Finally, it is shown that intraday cross-border trading has a significant influence on trading volumes and prices and ensures a more efficient allocation of resources. Y1 - 2020 U6 - http://dx.doi.org/10.3390/en13092339 SN - 1996-1073 N1 - Special Issue Uncertainties and Risk Management in Competitive Energy Markets VL - 13 IS - Art. 2339 SP - 1 EP - 35 PB - MDPI CY - Basel ER - TY - CHAP A1 - Paulsen, Svea A1 - Hoffstadt, Kevin A1 - Krafft, Simone A1 - Leite, A. A1 - Zang, J. A1 - Fonseca-Zang, W. A1 - Kuperjans, Isabel T1 - Continuous biogas production from sugarcane as sole substrate T2 - Energy Reports Y1 - 2020 U6 - http://dx.doi.org/10.1016/j.egyr.2019.08.035 N1 - 6th International Conference on Energy and Environment Research, ICEER 2019, 22–25 July, University of Aveiro, Portugal VL - 6 IS - Supplement 1 SP - 153 EP - 158 PB - Elsevier ER - TY - BOOK A1 - Pieper, Martin T1 - Quantum mechanics: Introduction to mathematical formulation N2 - Anyone who has always wanted to understand the hieroglyphs on Sheldon's blackboard in the TV series The Big Bang Theory or who wanted to know exactly what the fate of Schrödinger's cat is all about will find a short, descriptive introduction to the world of quantum mechanics in this essential. The text particularly focuses on the mathematical description in the Hilbert space. The content goes beyond popular scientific presentations, but is nevertheless suitable for readers without special prior knowledge thanks to the clear examples. KW - Quantenmechanik KW - Hilbert Room KW - Postulates KW - Schrödingers cat KW - Operators Y1 - 2021 SN - 978-3-658-32644-9 SN - 978-3-658-32645-6 U6 - http://dx.doi.org/10.1007/978-3-658-32645-6 PB - Springer CY - Wiesbaden ER - 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 -