Participación de la capacidad fotovoltaica instalada en México: un análisis benchmarking

This paper aims to identify specific policies that promote the participation of installed PV capacity in Mexico's energy basket. We apply a benchmarking analysis, which provides a comparative perspective between Mexico and the countries with the highest installed PV capacity in the world. The analysis suggests that, in order to boost the participation of installed PV capacity, a long-term planning of the Mexican PV industry should be carried out, with Smart Electric Grids as the leading principle, focusing on PV electricity. In such plan, the starting point should consist of implementing four policies: a) capital subsidy, concession or rebate; b) tax credit for investment or production; c) public investment, and; d) the promotion of research and development of PV technology

Critical analysis for big data studies in construction: significant gaps in knowledge

Purpose The purpose of this paper is to identify the gaps and potential future research avenues in the big data research specifically in the construction industry. Design/methodology/approach The paper adopts systematic literature review (SLR) approach to observe and understand trends and extant patterns/themes in the big data analytics (BDA) research area particularly in construction-specific literature. Findings A significant rise in construction big data research is identified with an increasing trend in number of yearly articles. The main themes discussed were big data as a concept, big data analytical methods/techniques, big data opportunities – challenges and big data application. The paper emphasises “the implication of big data in to overall sustainability” as a gap that needs to be addressed. These implications are categorised as social, economic and environmental aspects. Research limitations/implications The SLR is carried out for construction technology and management research for the time period of 2007–2017 in Scopus and emerald databases only. Practical implications The paper enables practitioners to explore the key themes discussed around big data research as well as the practical applicability of big data techniques. The advances in existing big data research inform practitioners the current social, economic and environmental implications of big data which would ultimately help them to incorporate into their strategies to pursue competitive advantage. Identification of knowledge gaps helps keep the academic research move forward for a continuously evolving body of knowledge. The suggested new research avenues will inform future researchers for potential trending and untouched areas for research. Social implications Identification of knowledge gaps helps keep the academic research move forward for continuous improvement while learning. The continuously evolving body of knowledge is an asset to the society in terms of revealing the truth about emerging technologies. Originality/value There is currently no comprehensive review that addresses social, economic and environmental implications of big data in construction literature. Through this paper, these gaps are identified and filled in an understandable way. This paper establishes these gaps as key issues to consider for the continuous future improvement of big data research in the context of the construction industry

A practical exploration of the convergence of case-based reasoning and explainable artificial intelligence.

As Artificial Intelligence (AI) systems become increasingly complex, ensuring their decisions are transparent and understandable to users has become paramount. This paper explores the integration of Case-Based Reasoning (CBR) with Explainable Artificial Intelligence (XAI) through a real-world example, which presents an innovative CBR-driven XAI platform. This study investigates how CBR, a method that solves new problems based on the solutions of similar past problems, can be harnessed to enhance the explainability of AI systems. Though the literature has few works on the synergy between CBR and XAI, exploring the principles for developing a CBR-driven XAI platform is necessary. This exploration outlines the key features and functionalities, examines the alignment of CBR principles with XAI goals to make AI reasoning more transparent to users, and discusses methodological strategies for integrating CBR into XAI frameworks. Through a case study of our CBR-driven XAI platform, iSee: Intelligent Sharing of Explanation Experience, we demonstrate the practical application of these principles, highlighting the enhancement of system transparency and user trust. The platform elucidates the decision-making processes of AI models and adapts to provide explanations tailored to diverse user needs. Our findings emphasize the importance of interdisciplinary approaches in AI research and the significant role CBR can play in advancing the goals of XAI

Artificial Intelligence in Energy Demand Response: A Taxonomy of Input Data Requirements

The ongoing energy transition increases the share of renewable energy sources. To combat inherent intermittency of RES, increasing system flexibility forms a major opportunity. One way to provide flexibility is demand response (DR). Research already reflects several approaches of artificial intelligence (AI) for DR. However, these approaches often lack considerations concerning their applicability, i.e., necessary input data. To help putting these algorithms into practice, the objective of this paper is to analyze, how input data requirements of AI approaches in the field of DR can be systematized from a practice-oriented information systems perspective. Therefore, we develop a taxonomy consisting of eight dimensions encompassing 30 characteristics. Our taxonomy contributes to research by illustrating how future AI approaches in the field of DR should represent their input data requirements. For practitioners, our developed taxonomy adds value as a structuring tool, e.g., to verify applicability with respect to input data requirements

Framing success:The Netherlands railways experience

Here we introduce the success framework, an integral view on the critical success factors to accommodate flexibilities required for tacking with the dynamism of rail industry both technically and organisationally. The success framework adapts two basic strategies that contribute to success. First, a clear set of objectives across the stakeholders. Second, cooperation and co-creation of values for achieving the objectives. We propose an integral approach for identification and accomplishment of the critical success factors. The application of the framework is further explained through a case study

Generic bill of functions, materials, and operations for SAP2 configuration

International audienceMost available studies on configuration focus on either sales configuration specifying functional features or production configuration addressing product components. It has been well recognised that automating most of the activities associated with specification, engineering, and process planning of customised products and their interactions is one key in achieving product customisation. Thus, treating sales configuration and product configuration separately may not contribute to product customisation from a systematic view although they may lead to the improvement of individual stages. Recognising this limitation of existing studies, in this paper, we propose integrated SAles, Product and Production (SAP2) configuration, which helps achieve product customisation from a holistic view. Its rationale lies in automating consistently sales, product and production configuration activities in one system. In view of the importance of configuration models, we focus on the model underpinning SAP2 configuration called generic bill of functions, materials and operations (GBoFMO) and discuss it in detail. As the core of SAP2 configuration, GBoFMO can provide companies with an insight into organising the large volumes of data and knowledge in the life cycle of product family development. We also report a case study of light passenger aircrafts to illustrate the GBoFMO

The Role of Smart Systems in Enhancing the Performance of Knowledge Management in Libraries Based on the Adoption of Using Expert System and Robots

Purpose: This study aims to enhance the performance of Knowledge management (KM). Additionally, the advantages and the applications of this export system and the smart systems are analyzed.   Theoretical framework: Selecting an algorithm isn’t an easy process. With a deep exploration of techniques and algorithms, the appropriate algorithm should be chosen and implemented to ascertain the solution for the problems like analyzing the trend of the business, identifying the age group, and finding the most desired articles and publications.   Design/methodology/approach: Contented and Expressive review approaches are implemented to conduct the research. The investigators significantly studied the materials associated with robots and expert systems in the reference to knowledge management in libraries. The results are obtained using the data visualization tool tableau. the Genetic algorithm is also used to analyze the results.   Findings: Smart systems are not easy to implement in knowledge management because knowledge management contains a large number of datasets. It has to be categorized first, then needs to be analyzed and the decisions must be taken accordingly.   Research, Practical & Social implications: The expert systems and the robots are to be implemented in the KM so the knowledge management will have enhanced performance with the help of the implementation of smart systems.   Originality/value:  In the study, the Genetic algorithm is used to find the analysis results. This algorithm was chosen because it works well in a noisy environment and is also easy to understand along with this GA is compared with the neural network algorithm

Caracterización de la dinámica de las tecnologías implicadas en los vehículos eléctricos y el hidrógeno verde: una mirada hacia Latinoamérica.

132 p.Esta tesis se desarrolla en el contexto de la transformación energética que han emprendido los países a raíz del compromiso asumido en el marco de los Objetivos de Desarrollo Sostenible (ODS) y el Acuerdo de París (cuyo objetivo es responder a las urgencias del cambio climático), lo cual les ha llevado a plantear como prioridad la descarbonización de sus economías. Entre las principales estrategias lanzada por varias naciones se encuentran, la implementación de los vehículos eléctricos (EVs, por sus siglas en inglés) y el desarrollo del hidrógeno verde (H2V), como vector energético.El objetivo principal de esta tesis es analizar la dinámica de los flujos de conocimiento hacia y dentro de América Latina (LATAM), en el ámbito de las tecnologías implicadas en los EVs y el H2V. Para ello, se han empleado herramientas y métodos cienciométricos, bibliométricos y de patentometría, complementados con análisis estadísticos y el uso de diferentes herramientas de software (VOSviewer, Gephi, Vantage Point y Loglet Lab4), análisis de redes e indicadores de centralidad, indicadores para el análisis de patentes, el uso de las curvas tecnológicas (curva S), mapas de conocimiento, así como diferentes variables e indicadores relacionados con la transición energética, especialmente el Retorno Energético de la Inversión o Energy Return on Investment (EROI, por sus siglas en inglés)

Economics of Electricity Battery Storage

This chapter deals with the challenges and opportunities of energy storage, with a specific focus on the economics of batteries for storing electricity in the framework of the current energy transition. Storage technologies include a variety of solutions that have been used for different grid services, including frequency control, load following, and uninterrupted power supply. A recent interest is being triggered by the increasing grid balance requirements to integrate variable renewable sources and distributed generation. In parallel, lithium-ion batteries are experiencing a strong market expansion driven by an uptake of electric vehicles worldwide, which is leading to a strong decrease of production costs, making Li-ion batteries an attractive solution also for stationary storage applications