Simulation of the operation of hydro plants in an electricity market using agent-based models

In recent years, the vast penetration of renewable energy sources has introduced a large degree of uncertainty into the power system, thus leading to increased trading activity in the continuous intra-day electricity market. In this paper, we propose an agent-based modeling framework to analyze the behavior and the interactions between renewable energy sources, consumers and thermal power plants in the European Continuous Intra-day (CID) market. Additionally, we propose a novel adaptive trading strategy that can be used by the agents that participate in CID market. The agents learn how to adapt their behavior according to the arrival of new information and how to react to changing market conditions by updating their willingness to trade. A comparative analysis was performed to study the behavior of agents when they adopt the proposed strategy as opposed to other benchmark strategies. The effects of unexpected outages and information asymmetry on the market evolution and the market liquidity were also investigated.

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Agent‐based models to investigate sound impact on marine animals: bridging the gap between effects on individual behaviour and population level consequences

Oikos ◽

10.1111/oik.08078 ◽

2021 ◽

Author(s):

Lars O. Mortensen ◽

Magda Ewa Chudzinska ◽

Hans Slabbekoorn ◽

Frank Thomsen

Keyword(s):

Population Level ◽

Agent Based Models ◽

Marine Animals ◽

Individual Behaviour ◽

Agent Based

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Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review

Microorganisms ◽

10.3390/microorganisms9020417 ◽

2021 ◽

Vol 9 (2) ◽

pp. 417

Author(s):

Sherli Koshy-Chenthittayil ◽

Linda Archambault ◽

Dhananjai Senthilkumar ◽

Reinhard Laubenbacher ◽

Pedro Mendes ◽

...

Keyword(s):

Species Interactions ◽

Computational Models ◽

Human Microbiome ◽

Agent Based Modeling ◽

Autonomous Agent ◽

Agent Based Models ◽

Agent Based ◽

Complex Interactions ◽

Mucosal Surfaces ◽

Living Organisms

The human microbiome has been a focus of intense study in recent years. Most of the living organisms comprising the microbiome exist in the form of biofilms on mucosal surfaces lining our digestive, respiratory, and genito-urinary tracts. While health-associated microbiota contribute to digestion, provide essential nutrients, and protect us from pathogens, disturbances due to illness or medical interventions contribute to infections, some that can be fatal. Myriad biological processes influence the make-up of the microbiota, for example: growth, division, death, and production of extracellular polymers (EPS), and metabolites. Inter-species interactions include competition, inhibition, and symbiosis. Computational models are becoming widely used to better understand these interactions. Agent-based modeling is a particularly useful computational approach to implement the various complex interactions in microbial communities when appropriately combined with an experimental approach. In these models, each cell is represented as an autonomous agent with its own set of rules, with different rules for each species. In this review, we will discuss innovations in agent-based modeling of biofilms and the microbiota in the past five years from the biological and mathematical perspectives and discuss how agent-based models can be further utilized to enhance our comprehension of the complex world of polymicrobial biofilms and the microbiome.

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