A Methodology for Modeling Systems of Engineering based on Agents

Aguilar, José; Bessembel, I.; Cerrada, Mariela; Hidrobo, Francisco; Narciso, Flor

doi:10.4114/ia.v12i38.975

Cited by 5 publications

(1 citation statement)

References 25 publications

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“…Utilizing the MultiAgent Systems for INtegrated Automation (MASINA) methodology [34,35], we design the emergent control approach based on the RTM. MASINA requires two steps: (i) specifying the general architecture of the system to derive the MAS, and (ii) designing each agent.…”

Section: Specification Of the Masmentioning

confidence: 99%

An Autonomous Distributed Coordination Strategy for Sustainable Consumption in a Microgrid Based on a Bio-Inspired Approach

García,

Aguilar,

R-Moreno

2024

Energies

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Distributed energy resources have demonstrated their potential to mitigate the limitations of large, centralized generation systems. This is achieved through the geographical distribution of generation sources that capitalize on the potential of their respective environments to satisfy local demand. In a microgrid, the control problem is inherently distributed, rendering traditional control techniques inefficient due to the impracticality of central governance. Instead, coordination among its components is essential. The challenge involves enabling these components to operate under optimal conditions, such as charging batteries with surplus solar energy or deactivating controllable loads when market prices rise. Consequently, there is a pressing need for innovative distributed strategies like emergent control. Inspired by phenomena such as the environmentally responsive behavior of ants, emergent control involves decentralized coordination schemes. This paper introduces an emergent control strategy for microgrids, grounded in the response threshold model, to establish an autonomous distributed control approach. The results, utilizing our methodology, demonstrate seamless coordination among the diverse components of a microgrid. For instance, system resilience is evident in scenarios where, upon the failure of certain components, others commence operation. Moreover, in dynamic conditions, such as varying weather and economic factors, the microgrid adeptly adapts to meet demand fluctuations. Our emergent control scheme enhances response times, performance, and on/off delay times. In various test scenarios, Integrated Absolute Error (IAE) metrics of approximately 0.01% were achieved, indicating a negligible difference between supplied and demanded energy. Furthermore, our approach prioritizes the utilization of renewable sources, increasing their usage from 59.7% to 86.1%. This shift not only reduces reliance on the public grid but also leads to significant energy cost savings.

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Section: Specification Of the Masmentioning

confidence: 99%

An Autonomous Distributed Coordination Strategy for Sustainable Consumption in a Microgrid Based on a Bio-Inspired Approach

García,

Aguilar,

R-Moreno

2024

Energies

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Cloud Computing in Smart Educational Environments: Application in Learning Analytics as Service

Sánchez¹,

Aguilar²,

Cordero³

et al. 2016

New Advances in Information Systems and Technologies

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A generic architecture of an affective recommender system for e-learning environments

Salazar,

Aguilar,

Monsalve-Pulido

et al. 2023

Univ Access Inf Soc

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Personalization of suggestions of contents plays a key role in adaptive virtual learning environments. Good recommendations can raise the interest of students in the learning process, while, on the other hand, bad recommendations can have catastrophic results for the learning process. The affective state of the student is a very influential factor in the learning process. In this work, a generic architecture of an affective recommender system for e-learning environments is developed, to serve as a guide for future implementations of this kind of recommender system. Here, the affective characteristics of students are represented by their personalities, learning styles, emotional states, and expertise levels. Thus, the main contribution is the proposition of a generic architecture of an affective recommendation system for the educational field. The architecture is completely modular, which gives it great flexibility because the emotion engine is separated from the personal characteristics engine, and is not based on specific models of emotions. This work finishes with examples of use cases of the architecture. According to the results in these examples, our architecture is capable of analyzing the polarity of academic documents based on their content, determining the personal characteristics of students (including their emotions), and from there, recommending learning resources to students considering emotions as the main element of the process.

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A Methodology for Modeling Systems of Engineering based on Agents

Cited by 5 publications

References 25 publications

An Autonomous Distributed Coordination Strategy for Sustainable Consumption in a Microgrid Based on a Bio-Inspired Approach

An Autonomous Distributed Coordination Strategy for Sustainable Consumption in a Microgrid Based on a Bio-Inspired Approach

Cloud Computing in Smart Educational Environments: Application in Learning Analytics as Service

A generic architecture of an affective recommender system for e-learning environments

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