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The Educational Journal of Renewable Energy Short Reviews (EduJRESR, formally published as ‘EGU Journal of Renewable Energy Short Reviews’) is a teaching project rather than a regular scientific journal.
To publish in this journal, it is a premise to take part in the master course wind power, hydro power and biomass usage at the department of Energy, Building Services and Environmental Engineering of the Münster University of Applied Sciences.
Students receive an equivalent of 2.5 credit points (European Credit Transfer and Accumulation System – ECTS) for their engagement in the course and for publishing a short review article of at most 3 000 words in this periodical. The publication process closely mimics the typical publication procedure of a regular journal.
The peer-review process, however, is conducted within the group of course-participants.
Although being just an exercise, we think that publishing the outcome of this course in a citable manner is not only promoting the motivation of our students, but may also be a helpful source of introductory information for researchers and practitioners in the field of renewable energies. We encourage students to write their articles in English, but this is not mandatory. The reader will thus find a few articles in German language.
To further encourage students practicing English writing, perfect grammar is not part of the assessment.
We especially thank our students for working with LATEX on Overleaf, although LATEX is new to some of them. In this way, the editorial workload was reduced to a minimum. We also thank our students for sharing their work under the creative commons attribution licence (CC-BY). We appreciate their contribution to scientific information, being available to every person of the world, almost without barriers. We also thank the corresponding authors and publishers of the cited work, for granting permission.
Meanwhile, renewable energy sources such as hydropower, solar and wind energy and biomass are increasingly being used to reduce dependence on fossil fuels and thus counteract the ongoing global warming. However, these are also associated with environmental impacts. To that effect, this article takes a closer look at tidal power plants, which are classified as hydroelectric power plants, by conducting a systematic literature review. The results show that the strength and form of the environmental impact depends on the specific location and type of plant. Tidal power plants have an impact on the habitats of marine animals and thus influence their behavior and population. In addition, the operation of tidal power plants changes the sediment distribution, causes a reduction in current velocities and a change in current direction in the surrounding area and leads to a change in wave height. The construction of the power plants is associated with noise, which primarily causes changes in the behavior of some species. Furthermore, the electromagnetic fields generated can also affect marine life. In order to assess the environmental impact of tidal power plants in comparison to other renewable energies, further studies should focus on the environmental impact of the different technologies in relation to the energy yield.
This article discusses the use of artificial intelligence
in the wind energy industry, particularly in addressing
challenges and optimizing the expansion of renewable
energies in Germany. It highlights the application
of artificial intelligence in wind forecasts and yield
predictions, bird detection, wind turbine and farm
design, condition monitoring, and predictive maintenance.
Additionally, it introduces the “WindGISKI”
research project, which aims to use artificial intelligence
to identify new areas for wind turbines. The
project utilizes a neural network to analyze and predict
flight routes, potentially reducing bird mortality.
The document also emphasizes the potential broader
applications of “WindGISKI” in other fields of activity,
such as land use planning and city development.
Overall, it underscores the significant role of artificial
intelligence in addressing challenges in wind energy
and outlines the potential for artificial intelligence
to drive the expansion of renewable energies while
addressing key obstacles.
Wind turbine structures take a major role in the
modern conversion to renewable energy sources and
contribute to the creation of a greener world. In recent
years, the development and installation of wind
turbines have seen rapid growth. However, with the
increasing capacity and size of wind farms worldwide,
there are growing concerns about the safety and reliability
of these installations. Therefore, structural
health monitoring and the detection of damage to
wind turbines have gained considerable importance in
research. Wind turbine blades are particularly susceptible
to various types of damage due to environmental
influences. This article provides an overview of signal
responses, sensors used and non-destructive testing
techniques in the field of damage detection on wind
turbine blades. The intention of the article is to give
an insight into the possibilities of structural health
monitoring and at the same time to point out unsolved
problems in this field.
The preservation of water bodies continuity is fundamental
for aquatic communities, particularly for fish
populations. Various structures impede watercourse
continuity, impacting fish migration and habitat distribution.
Conventional fish passages often fall short
in diverse scenarios, prompting the development of
specialized solutions. This article proposes a criteria
catalog for these special fish passage solutions based
on DWA leaflet DWA-A 509. It discusses the need
for these solutions, presents a selection of specialized
options, and outlines criteria from DWA-M 509, construction
guidelines, and economic perspectives. It
scrutinizes criteria ranging from target fish species to
cost considerations. Three examples, including the
Runserau fish lift, the bristle ramp fish lock, and the
Fishcon sluice, illustrate these specialized solutions,
their functionalities, advantages, and drawbacks. Additionally,
the article compiles criteria from industry
standards and guidelines into a comprehensive evaluation
catalog. The criteria, when applied, assist in the
selection of suitable fish passage solutions based on
specific site conditions and fish species requirements.
This holistic approach aims to optimize fishway selection,
fostering the ecological sustainability of watercourses.
However, this catalog remains dynamic
and open to expansion with evolving research and
practical application, urging further exploration and
validation of these criteria through diverse case studies
and technological advancements in the field.
This study identifies supply options for sustainable urban energy systems, which are robust to external system changes. A multi-criteria optimization model is used to minimize greenhouse gas (GHG) emissions and financial costs of a reference system. Sensitivity analyses examine the impact of changing boundary conditions related to GHG emissions, energy prices, energy demands, and population density. Options that align with both financial and emission reduction and are robust to system changes are called “no-regret” options. Options sensitive to system changes are labeled as “potential-risk” options.
There is a conflict between minimizing GHG emissions and financial costs. In the reference case, the emission-optimized scenario enables a reduction of GHG emissions (-93%), but involves higher costs (+160%) compared to the financially-optimized scenario.
No-regret options include photovoltaic systems, decentralized heat pumps, thermal storages, electricity exchange between sub-systems and with higher-level systems, and reducing energy demands through building insulation, behavioral changes, or the decrease of living space per inhabitant. Potential-risk options include solar thermal systems, natural gas technologies, high-capacity battery storages, and hydrogen for building energy supply.
When energy prices rise, financially-optimized systems approach the least-emission system design. The maximum profitability of natural gas technologies was already reached before the 2022 European energy crisis.
Die Planung urbaner Energiesysteme wird durch die zunehmende Verbreitung sektorgekoppelter Technologien und neuer Verbrauchssektoren immer komplexer. Klassische Planungsmethoden kommen an ihre Grenzen. Die Energiesystemmodellierung (ESM) bietet eine Möglichkeit, ein Energiesystem hinsichtlich der Kosten und der Treibhausgas (THG)- Emissionen zu optimieren. Gleichzeitig ergibt sich aus der Energiewende und angestrebten THG-Neutralität ein akuter Handlungsbedarf. Dies gilt auch für die 1 500 Kasernen in Deutschland. Im Rahmen dieser Arbeit werden der bestehende Modellierungsprozess des Spreadsheet Energy System Model Generator (SESMG) erweitert, indem Herausforderungen der Modellierung und Optimierung von Kasernen identifiziert und Lösungsansätze hierzu entwickelt werden.
Diese Arbeit basiert auf der ESM einer realen Kaserne. Es kann das Urban District Upscaling Tool zur Erstellung der für den SESMG benötigten Modelldefinition verwendet werden. Die Open-Source Datenbank SESMG-Data, kann automatisch die benötigte Standard Parameter Tabelle mit zugehörigem Bericht generieren. Weiterhin wurde ein Energieaustauschmodell vorgestellt, das den Energieaustausch zwischen Kasernen eines Bilanzkreises ermöglicht. Ein Fokus liegt auf der Abbildung zukünftiger Ausbaupläne.
Dazu wurden kasernenspezifische Gebäudeprofile entwickelt, die gemittelte spezifische Energiebedarfe und weitere Parameter zur Berechnung der Wand-, Fenster-, und Dachfläche enthalten. Der spezifische Wärmebedarf kann durch einen Faktor an die Baualtersklasse angepasst werden. Mit Hilfe statistischer Kennwerte lässt sich ein geeignetes Standardlastprofil für verschiedene Gebäudeprofile auswählen. Zur Reduktion der Komponenten im Energiesystemoptimierungsmodell (ESOM) können die Dachflächenpotenziale von Photovoltaikanlagen zusammengefasst werden. Da Kasernen nur eine Bilanzgrenze besitzen, können zudem auch die Strombedarfe der einzelnen Gebäude zusammengefasst werden. Damit lassen sich gleichzeitig dezentrale Batteriespeicher als Komponente des ESOMs ausschließen. Die Potenzialflächen von Erdwärmepumpen können zusammengefasst werden, wobei Abstands- und Belastbarkeitsgrenzen eingehalten werden müssen.
Kasernen verfügen häufig über Bestandswärmenetze, die im ESOM gesondert berücksichtigt werden müssen. Um dieses Bestandswärmenetz abzubilden, können die Verteilleitungen manuell nachgezeichnet werden und in einer Vormodellierung mit dem SESMG mit geringeren Kosten angesetzt werden. Die in dieser Arbeit entwickelten Methoden sind allgemeingültig für Kasernen. Die Übertragbarkeit der kasernenspezifischen Gebäudeprofile ist aufgrund der unterschiedlichen Nutzung von Kasernen nur eingeschränkt möglich. Der bestehende Modellierungsprozess wurde um kasernenspezifische Prozessschritte erweitert und visualisiert. Zukünftige Modellierungen von Kasernen können zur Validierung der Ergebnisse und für weitere Anpassungen, wie z. B. die Erstellung einer kasernenspezifischen Datenbank, genutzt werden.
Die Transformation der Energiesysteme im Rahmen der Energiewende macht diese durch zusätzliche Komponenten und Wechselwirkungen immer komplexer. Das ökonomische und ökologische Potenzial, dass sich aus der Nutzung der Synergien dieser Komponenten ergeben kann, erfordert eine gemeinsame Betrachtung des gesamten Energiesystems hinsichtlich sämtlicher Energie- und Verbrauchssektoren.
Die Energiesystemmodellierung stellt eine geeignete Methode zur Modellierung und Optimierung dieser urbanen Energiesysteme dar. Mit dem „Spreadsheet Energy System Model Generator“ (SESMG) hat die FH Münster ein Open Source Tool entwickelt, das die Betrachtung urbaner Quartiere ermöglicht. Diese können hinsichtlich verschiedener Zielkriterien wie z. B. monetären Kosten und THG-Emissionen optimiert werden. Die tabellenbasierte Eingabe erfordert keine Programmierkenntnisse. Das implementierte Urban District Upscaling Tool erleichtert die effektive Modellierung auch größerer Systeme. Die automatisierte Ergebnisaufbereitung ermöglicht eine schnelle Analyse der Ergebnisse.
The annual wastewater flow that is treated by public
wastewater treatment plants in Germany amounts
to approx. 10 ∗ 10^9 m3/a and forms an ”artificial” hydropower
potential that can be used for energy generation
or recovery. In the context of this paper, energy
recovery in the outlet of wastewater treatment plants
is examined using the specific example of the water
wheel at the Warendorf central wastewater treatment
plant. The ”artificial” hydropower potential can be
roughly estimated at up to 20 to 105 GWh/a , whereby
this is largely dependent on the hydraulic gradient.
The strong variance results, among other things, from
the findings of the water wheel operation in Warendorf.
The decisive aspect here is the differential factor,
which describes the deviation between the theoretical
and actual energy yield of the water wheel. The
factor includes maintenance work, downtimes and insufficient
inflows, which are associated with a loss of
output. In the case study, the annual energy recovery
amounts to approx. 2 % of the annual electricity consumption
of the wastewater treatment plant and can
be estimated to 23,500 kWh (2022). In the context
of the economic analysis, it can be seen that despite
the ”low” yield, economic operation is possible if the
system is viewed as a long-term investment - payback
period of the example is approx. 14,5 years. The
27-year operation (1996 - 2023) of the water wheel
at the Warendorf central wastewater treatment plant
confirms this and important findings on successful
practical operation can be shown in the context of
this paper.