Agent-based tool to reduce the maintenance cost of energy distribution networks

Chamoso, Pablo; Paz, Juan F. De; Bajo, Javier; Villarrubia, Gabriel

doi:10.1007/s10115-017-1120-7

Cited by 7 publications

(5 citation statements)

References 34 publications

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“…The other class of fault classification methods and electric power applications are based on emerging computational approaches such as machine learning (ML) or deep learning (DL) [5,7,17,18]. For example, in [6], the authors introduced a non-intrusive fault identification method in power transmission lines using PS-HST to extract high-frequency fault components.…”

Section: (A) (B)mentioning

confidence: 99%

Performance evaluation of machine learning for fault selection in power transmission lines

et al. 2022

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Learning methods have been increasingly used in power engineering to perform various tasks. In this paper, a fault selection procedure in double-circuit transmission lines employing different learning methods is accordingly proposed. In the proposed procedure, the discrete Fourier transform (DFT) is used to pre-process raw data from the transmission line before it is fed into the learning algorithm, which will detect and classify any fault based on a training period. The performance of different machine learning algorithms is then numerically compared through simulations. The comparison indicates that an artificial neural network (ANN) achieves remarkable accuracy of 98.47%. As a drawback, the ANN method cannot provide explainable results and is also not robust against noisy measurements. Subsequently, it is demonstrated that explainable results can be obtained with high accuracy by using rule-based learners such as the recently developed quantitative association rule mining algorithm (QARMA). The QARMA algorithm outperforms other explainable schemes, while attaining an accuracy of 98%. Besides, it was shown that QARMA leads to a very high accuracy of 97% for highly noisy data. The proposed method was also validated using data from an actual transmission line fault. In summary, the proposed two-step procedure using the DFT combined with either deep learning or rule-based algorithms can accurately and successfully perform fault selection tasks but indicating remarkable advantages of the QARMA due to its explainability and robustness against noise. Those aspects are extremely important if machine learning and other data-driven methods are to be employed in critical engineering applications.

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Section: (A) (B)mentioning

confidence: 99%

Performance evaluation of machine learning for fault selection in power transmission lines

et al. 2022

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“…To make this process more efficient, it develops a CBR-BDI agent that collaborates with a multi-agent system in conjunction with different algorithms to reduce the number of TT to be reviewed in an electrical network. Chamoso et al [34] also present an agent-based tool with a CBR cycle incorporated to reduce the maintenance cost of energy distribution networks.…”

Section: Energy Management Using Cbr Systemsmentioning

confidence: 99%

Multi-Agent-Based CBR Recommender System for Intelligent Energy Management in Buildings

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Navarro-Cáceres

et al. 2019

IEEE Systems Journal

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This paper proposes a novel case-based reasoning (CBR) recommender system for intelligent energy management in buildings. The proposed approach recommends the amount of energy reduction that should be applied in a building in each moment, by learning from previous similar cases. The k-nearest neighbor clustering algorithm is applied to identify the most similar past cases, and an approach based on support vector machines is used to optimize the weight of different parameters that characterize each case. An expert system composed by a set of ad hoc rules guarantees that the solution is adequate and applicable to the new case scenario. The proposed CBR methodology is modeled through a dedicated software agent, thus enabling its integration in a multi-agent systems society for the study of energy systems. Results show that the proposed approach is able to provide suitable recommendations on energy reduction, by comparing its results with a previous approach based on particle swarm optimization and with the real reduction in past cases. The applicability of the proposed approach in real scenarios is also assessed through the application of the results provided by the proposed approach on a house energy resources management system. Index Terms-Building energy management, case-based reasoning (CBR), energy efficiency, multi-agent systems (MAS).

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“…Igualmente, se obtiene una desviación estándar de 1,11 lo cual muestra una dispersión intermedia en las respuestas de la muestra. En referencia al indicador adaptabilidad la literatura establece que las organizaciones estudiadas se adaptan a las condiciones cambiantes presentadas por el mercado (Jimenez y Sanchez, 2007y Chamoso et al, 2018. Considerando los resultados anteriores, la media de la dimensión fortaleza de los vínculos de cooperación se ubica en 3,45, lo que demuestra que se encuentra presente de acuerdo con el baremo de interpretación.…”

Section: Fortaleza De Los Vínculos De Cooperación Empresarialunclassified

“…Para efectos del presente artículo, se analizan la fortaleza de los vínculos de cooperación organizacional, a partir de los siguientes indicadores: extensión(Aboal et al, 2018), intensidad(Missaoui et al, 2017), estabilidad(Lucas et al, 2018), renovación(Arrais et al, 2018), especializacióntotipotencia(Gonzalez et al 2007) y adaptabilidad(Chamoso et al, 2018y Ali y Ahmad, 2018. Los vínculos de cooperación organizacional corresponden a una estrategia para que las empresas solucionen problemas cuyas características necesitan de esfuerzos conjuntos que aprovechen sinergias.…”

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Elementos Estructurales y Funcionales de los Sistemas Multi-Agente para la Cooperación Organizacional en Medianas Empresas

et al. 2019

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ResumenSe analiza la presencia de los elementos estructurales y funcionales de los Sistemas Multi-Agente en las medianas empresas, identificando la oportunidad para fortalecer los vínculos de cooperación entre ellas. La investigación se fundamenta epistemológicamente en la escuela de pensamiento del positivismo lógico, con enfoque cuantitativo, desde el paradigma positivista, y de tipo descriptivo. La muestra corresponde a cuarenta y cuatro medianas empresas del municipio de Valledupar, Colombia, con capitales entre US$1.300.000 a US$ 4.000.000. Los resultados destacan la presencia de los elementos y funciones de los Sistemas Multi-Agente en las medianas empresas encuestadas. Adicionalmente, se demostró la presencia de los vínculos de cooperación organizacional, destacándose los indicadores de extensión, intensidad, renovación, especialización y adaptabilidad. Sin embargo, se observa una mediana presencia del indicador de estabilidad de los vínculos de cooperación. Esto constituye una oportunidad para el desarrollo de capacidades de cooperación, mecanismos de negociación, confianza mutua y aprovechamiento de sinergias. Palabras AbstractThe presence of the structural and functional elements of the Multi-Agent systems inside medium-sized companies, identifying the opportunity to strengthen the cooperation links between them. The research is epistemologically based on the school of logical positivism, with quantitative approach, and descriptive type. The sample are forty-four (44) medium-sized companies of the Valledupar municipality, Colombia, with capitals between US$ 1.300.000 and US$ 4.000.000. The results show the presence of the elements and functions of the Multi-Agent systems in the surveyed medium-sized companies. In addition, the presence of organizational cooperation links was demonstrated, especially to the characteristics of extension, intensity, renewal, specialization and adaptability. However, a low presence of the stability characteristic of cooperation links is observed. This represents an opportunity for the development of cooperation capacities, negotiation mechanisms, mutual trust and use of synergies.

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Agent-based tool to reduce the maintenance cost of energy distribution networks

Cited by 7 publications

References 34 publications

Performance evaluation of machine learning for fault selection in power transmission lines

Performance evaluation of machine learning for fault selection in power transmission lines

Multi-Agent-Based CBR Recommender System for Intelligent Energy Management in Buildings

Elementos Estructurales y Funcionales de los Sistemas Multi-Agente para la Cooperación Organizacional en Medianas Empresas

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