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  -