129 research outputs found
A novel learning automata game with local feedback for parallel optimization of hydropower production
Master's thesis Information- and communication technology IKT590 - University of Agder 2017Hydropower optimization for multi-reservoir systems is classi ed as a combinatorial
optimization problem with large state-space that is particularly
di cult to solve. There exist no golden standard when solving such problems,
and many proposed algorithms are domain speci c.
The literature describes several di erent techniques where linear programming
approaches are extensively discussed, but tends to succumb to the curse
of dimensionality problem when the state vector dimensions increase. This
thesis introduces LA LCS, a novel learning automata algorithm that utilizes
a parallel form of local feedback. This enables each individual automaton
to receive direct feedback, resulting in faster convergence. In addition, the
algorithm is implemented using a parallel architecture on a CUDA enabled
GPU, along with exhaustive and random search.
LA LCS has been veri ed through several scenarios. Experiments show that
the algorithm is able to quickly adapt and nd optimal production strategies
for problems of variable complexity. The algorithm is empirically veri ed
and shown to hold great promise for solving optimization problems, including
hydropower production strategies
A gradient boosting approach for optimal selection of bidding strategies in reservoir hydro
Power producers use a wide range of decision support systems to manage and
plan for sales in the day-ahead electricity market, and they are often faced
with the challenge of choosing the most advantageous bidding strategy for any
given day. The optimal solution is not known until after spot clearing. Results
from the models and strategy used, and their impact on profitability, can
either continuously be registered, or simulated with use of historic data.
Access to an increasing amount of data opens for the application of machine
learning models to predict the best combination of models and strategy for any
given day. In this article, historical performance of two given bidding
strategies over several years have been analyzed with a combination of domain
knowledge and machine learning techniques (gradient boosting and neural
networks). A wide range of variables accessible to the models prior to bidding
have been evaluated to predict the optimal strategy for a given day. Results
indicate that a machine learning model can learn to slightly outperform a
static strategy where one bidding method is chosen based on overall historic
performance
Optimal operation of dams/reservoirs emphasizing potential environmental and climate change impacts
Mahdi studied the potential ecological and climate change impacts on management of dams. He developed several new optimization frameworks in which benefits of dams are maximized, while above impacts are mitigated. Governments and consulting engineers can use the proposed frameworks for managing dams considering environmental challenges in river basins
Spatially explicit migration models of pike to support river management
De status van verschillende vissoorten in ons land, waaronder ook snoek (Esox lucius) voldoet niet aan de gestelde Europese vereisten. Behalve door een matige chemische waterkwaliteit komt dit voornamelijk door een ondermaatse habitatkwaliteit door habitatdegradatie, fragmentatie en obstructie. Rivierbeheerders plannen daarom maatregelen om het habitat te beschermen, te verbeteren of opnieuw toegankelijk te maken voor migrerende vissen. Habitatgeschiktheid- en soortverspreidingsmodellen kunnen helpen om het effect van deze maatregelen te voorspellen. Deze modellen zijn vaak niet in staat rekening te houden met factoren die gerelateerd zijn aan migratie en toegankelijkheid omdat ze niet ruimtelijk expliciet en dynamisch tegelijk zijn. In dit doctoraatsonderzoek evalueerden we de toepasbaarheid voor het simuleren van snoekmigratie van twee modelleertechnieken die wel geschikt lijken: Individueel Gebaseerde Modellen (IBMs) en Cellulaire Automaten (CAs). Daarnaast onderzochten we de migratiedynamiek, het habitatgebruik en de habitatpreferentie van volwassen snoeken ter ondersteuning van het rivierbeheer. Hiervoor werden veldgegevens verzameld van snoeken in de Ijzer (West-Vlaanderen) m.b.v. radiotelemetrie. De resultaten van dit onderzoek wijzen op een goede toepasbaarheid van IBMs en moeilijkheden bij het toepassen van de CAs voor de simulatie van snoekmigratie. De analyses van de veldgegevens tonen grote individuele verschillen in gedrag en onderlijnen het belang van habitatheterogeniteit en het toegankelijk maken van bestaande geschikte habitats voor volwassen snoeken. Dit onderzoek geeft meer inzicht in het ruimtelijk expliciet simuleren van snoekmigratie en levert kennis over de ecologie van snoek met directe suggesties voor rivierbeheerders
Hydrolink 2020/4. Artificial intelligent
Topic: Artificial Intelligenc
Global Warming
This book is intended to introduce the reader to examples of the range of practical problems posed by "Global Warming". It includes 11 chapters split into 5 sections. Section 1 outlines the recent changes in the Indian Monsoon, the importance of greenhouse gases to life, and the relative importance of changes in solar radiation in causing the changes. Section 2 discusses the changes to natural hazards such as floods, retreating glaciers and potential sea level changes. Section 3 examines planning cities and transportation systems in the light of the changes, while section 4 looks at alternative energy sources. Section 5 estimates the changes to the carbon pool in the alpine meadows of the Qinghai-Tibet Plateau. The 11 authors come from 9 different countries, so the examples are taken from a truly international set of problems
Integrated models, frameworks and decision support tools to guide management and planning in Northern Australia. Final report
[Extract] There is a lot of interest in developing northern Australia while also caring for the unique Australian landscape (Commonwealth of Australia 2015). However, trying to decide how to develop and protect at the same time can be a challenge. There are many modelling tools available to inform these decisions, including integrated models, frameworks, and decision support tools, but there are so many different kinds that itâs difficult to determine which might be best suited to inform different decisions. To support planning and development decisions across northern Australia, this project aimed to create resources to help end-users (practitioners) to assess:
1. the availability and suitability of particular modelling tools; and
2. the feasibility of using, developing, and maintaining different types of modelling tools
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