TY  - JOUR
A1  - Cheenakula, Dheeraja
A1  - Hoffstadt, Kevin
A1  - Krafft, Simone
A1  - Reinecke, Diana
A1  - Klose, Holger
A1  - Kuperjans, Isabel
A1  - Grömping, Markus
T1  - Anaerobic digestion of algal–bacterial biomass of an Algal Turf Scrubber system
JF  - Biomass Conversion and Biorefinery
N2  - This study investigated the anaerobic digestion of an algal–bacterial biofilm grown in artificial wastewater in an Algal Turf Scrubber (ATS). The ATS system was located in a greenhouse (50°54′19ʺN, 6°24′55ʺE, Germany) and was exposed to seasonal conditions during the experiment period. The methane (CH4) potential of untreated algal–bacterial biofilm (UAB) and thermally pretreated biofilm (PAB) using different microbial inocula was determined by anaerobic batch fermentation. Methane productivity of UAB differed significantly between microbial inocula of digested wastepaper, a mixture of manure and maize silage, anaerobic sewage sludge, and percolated green waste. UAB using sewage sludge as inoculum showed the highest methane productivity. The share of methane in biogas was dependent on inoculum. Using PAB, a strong positive impact on methane productivity was identified for the digested wastepaper (116.4%) and a mixture of manure and maize silage (107.4%) inocula. By contrast, the methane yield was significantly reduced for the digested anaerobic sewage sludge (50.6%) and percolated green waste (43.5%) inocula. To further evaluate the potential of algal–bacterial biofilm for biogas production in wastewater treatment and biogas plants in a circular bioeconomy, scale-up calculations were conducted. It was found that a 0.116 km2 ATS would be required in an average municipal wastewater treatment plant which can be viewed as problematic in terms of space consumption. However, a substantial amount of energy surplus (4.7–12.5 MWh a−1) can be gained through the addition of algal–bacterial biomass to the anaerobic digester of a municipal wastewater treatment plant. Wastewater treatment and subsequent energy production through algae show dominancy over conventional technologies.
KW  - Biogas
KW  - Methane
KW  - Algal Turf Scrubber
KW  - Algal–bacterial bioflm
KW  - Circular bioeconomy
Y1  - 2022
U6  - http://dx.doi.org/10.1007/s13399-022-03236-z
SN  - 2190-6823
N1  - Corresponding author: Dheeraja Cheenakula
VL  - 13
SP  - 15 Seiten
PB  - Springer
CY  - Berlin
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  -