Ponències/Comunicacions de congressoshttp://hdl.handle.net/2117/1847442024-03-28T10:38:46Z2024-03-28T10:38:46ZInterval-censored covariates in regression modelsLangohr, KlausToloba López-Egea, AndreaGómez Melis, Guadalupehttp://hdl.handle.net/2117/3954702023-11-12T03:25:01Z2023-10-27T14:05:42ZInterval-censored covariates in regression models
Langohr, Klaus; Toloba López-Egea, Andrea; Gómez Melis, Guadalupe
Interval-censored time-to-event data are common whenever the event of interest is a silent event that cannot be observed directly. Here, we present an estimation method for generalized linear models with interval-censored covariates that is applied to data from a metabolomic study.
2023-10-27T14:05:42ZLangohr, KlausToloba López-Egea, AndreaGómez Melis, GuadalupeInterval-censored time-to-event data are common whenever the event of interest is a silent event that cannot be observed directly. Here, we present an estimation method for generalized linear models with interval-censored covariates that is applied to data from a metabolomic study.Mixed nonlinear modelling in food engineering: determination of the salting time of boneless dry-cured Cerretan hamsEspuña Soler, Francesc XavierAcosta Argueta, Lesly MaríaSánchez Espigares, Josep AntonTort-Martorell Llabrés, Xavierhttp://hdl.handle.net/2117/3946122023-10-22T11:00:33Z2023-10-04T13:34:04ZMixed nonlinear modelling in food engineering: determination of the salting time of boneless dry-cured Cerretan hams
Espuña Soler, Francesc Xavier; Acosta Argueta, Lesly María; Sánchez Espigares, Josep Anton; Tort-Martorell Llabrés, Xavier
A great challenge in producing a good cured ham is to reduce the variability of the salt content between pieces of ham and to obtain homogeneity in terms of flavour and quality in general. This reduction in variability would imply a reduction in salt content, a recommendation of the World Health Organisation (WHO, 2007). This work focuses on the salting process of boneless Cerretan hams and our aim is two-fold: 1) to build a mathematical model that enables —through predictions— the reduction of the variability of salt between pieces, and 2) to determine an ‘appropriate’ salting time for each ham. We propose a novel strategy within the ham industry to determine appropriate hams extraction time from the salting pile and we postulate that it is statistically and practically advantageous to the habitual hams extraction strategy (removal based on fat and weight classification and all at the same time). We build a non-linear mixed (NLM) model that, according to the final salt uptake target of 1.7%, would allow to decide each ham extraction time depending on the initial weight and fat, plus the weight decrease on day one. This model has to be applicable in industrial production, albeit in an approximate form. To account better for the salting-time estimated uncertainty, we run a nonparametric bootstrap. A further aim is to extrapolate the use of the NLM modelling methodology and proposed novel extraction strategy to other boneless hams industrial production systems in Europe.
2023-10-04T13:34:04ZEspuña Soler, Francesc XavierAcosta Argueta, Lesly MaríaSánchez Espigares, Josep AntonTort-Martorell Llabrés, XavierA great challenge in producing a good cured ham is to reduce the variability of the salt content between pieces of ham and to obtain homogeneity in terms of flavour and quality in general. This reduction in variability would imply a reduction in salt content, a recommendation of the World Health Organisation (WHO, 2007). This work focuses on the salting process of boneless Cerretan hams and our aim is two-fold: 1) to build a mathematical model that enables —through predictions— the reduction of the variability of salt between pieces, and 2) to determine an ‘appropriate’ salting time for each ham. We propose a novel strategy within the ham industry to determine appropriate hams extraction time from the salting pile and we postulate that it is statistically and practically advantageous to the habitual hams extraction strategy (removal based on fat and weight classification and all at the same time). We build a non-linear mixed (NLM) model that, according to the final salt uptake target of 1.7%, would allow to decide each ham extraction time depending on the initial weight and fat, plus the weight decrease on day one. This model has to be applicable in industrial production, albeit in an approximate form. To account better for the salting-time estimated uncertainty, we run a nonparametric bootstrap. A further aim is to extrapolate the use of the NLM modelling methodology and proposed novel extraction strategy to other boneless hams industrial production systems in Europe.An approach based on simulation and optimization to integrate ride-pooling with public transport for a cooperative approachLorente García, EsterBarceló Bugeda, JaimeCodina Sancho, EsteveNoëkel, Klaushttp://hdl.handle.net/2117/3919762023-10-08T10:20:36Z2023-07-24T07:46:37ZAn approach based on simulation and optimization to integrate ride-pooling with public transport for a cooperative approach
Lorente García, Ester; Barceló Bugeda, Jaime; Codina Sancho, Esteve; Noëkel, Klaus
Mobility as a Service (MaaS), appeared as a tool to provide more efficient solutions in large urban areas, but, it hasn’t always been the case. The International Union of Public Transport (UITP) and the International Transport Forum (ITF) proposed policies to use such services as feeders for public transport, raising the challenge of how to integrate them. Ride-pooling, a type of Demand Responsive Transport, coordinated with public transport could be a solution. This paper explores how to model such intermodal system by an agent-based intermodal simulator that manages service requests while accounting for vehicle capabilities, transit schedules, and time constraints, integrated with an intermodal dispatcher defined by an optimization model, which proposes the best-combined solution.
2023-07-24T07:46:37ZLorente García, EsterBarceló Bugeda, JaimeCodina Sancho, EsteveNoëkel, KlausMobility as a Service (MaaS), appeared as a tool to provide more efficient solutions in large urban areas, but, it hasn’t always been the case. The International Union of Public Transport (UITP) and the International Transport Forum (ITF) proposed policies to use such services as feeders for public transport, raising the challenge of how to integrate them. Ride-pooling, a type of Demand Responsive Transport, coordinated with public transport could be a solution. This paper explores how to model such intermodal system by an agent-based intermodal simulator that manages service requests while accounting for vehicle capabilities, transit schedules, and time constraints, integrated with an intermodal dispatcher defined by an optimization model, which proposes the best-combined solution.A simulation system for intermodal assignment of public transport and ride pooling servicesLorente García, EsterBarceló Bugeda, JaumeCodina Sancho, EsteveKlaus, Nökelhttp://hdl.handle.net/2117/3747322023-10-08T03:10:55Z2022-10-20T11:37:51ZA simulation system for intermodal assignment of public transport and ride pooling services
Lorente García, Ester; Barceló Bugeda, Jaume; Codina Sancho, Esteve; Klaus, Nökel
2022-10-20T11:37:51ZLorente García, EsterBarceló Bugeda, JaumeCodina Sancho, EsteveKlaus, NökelIntegration of a microgrid laboratory into an aggregation platform and analysis of the potential for flexibilityEtxandi Santolaya, MaiteColet, AlbaBarbero, MattiaCorchero García, Cristinahttp://hdl.handle.net/2117/3678072023-07-30T03:15:23Z2022-05-28T11:44:20ZIntegration of a microgrid laboratory into an aggregation platform and analysis of the potential for flexibility
Etxandi Santolaya, Maite; Colet, Alba; Barbero, Mattia; Corchero García, Cristina
The increase of Renewable Energy Sources (RES) has given momentum to demand-side flexibility, led by Demand Response (DR), to counteract the uncertainties of the new electricity system. Meanwhile, consumers, with the help of Demand Aggregators (DA), are becoming active participants by engaging in flexibility actions. As a tool for the experimental assessment of DR, this work integrates a microgrid laboratory with an aggregation platform. To test the environment created and analyse the impact of DR, two consumers have been defined using virtual, emulated and real elements: a residential user with a Heating Ventilation and Air Conditioning (HVAC) unit and a prosumer equipped with Photovoltaic (PV) panels and a second-life battery.
2022-05-28T11:44:20ZEtxandi Santolaya, MaiteColet, AlbaBarbero, MattiaCorchero García, CristinaThe increase of Renewable Energy Sources (RES) has given momentum to demand-side flexibility, led by Demand Response (DR), to counteract the uncertainties of the new electricity system. Meanwhile, consumers, with the help of Demand Aggregators (DA), are becoming active participants by engaging in flexibility actions. As a tool for the experimental assessment of DR, this work integrates a microgrid laboratory with an aggregation platform. To test the environment created and analyse the impact of DR, two consumers have been defined using virtual, emulated and real elements: a residential user with a Heating Ventilation and Air Conditioning (HVAC) unit and a prosumer equipped with Photovoltaic (PV) panels and a second-life battery.Business case of adopting corporate sustainability measures: a multi-study through a bibliometric research and literature reviewBarroso del Toro, AlbertoTort-Martorell Llabrés, XavierCanela, Miguel Angelhttp://hdl.handle.net/2117/3665702023-07-30T09:32:07Z2022-04-29T07:44:40ZBusiness case of adopting corporate sustainability measures: a multi-study through a bibliometric research and literature review
Barroso del Toro, Alberto; Tort-Martorell Llabrés, Xavier; Canela, Miguel Angel
Has invested in Corporate Sustainability a positive economic return? If so, where is it hitting? Are the benefits only attributable to the environment or also to the shareholders?. This research aims to write a state of the art about the economic impact of being sustainable. We will analyze the 200 most cited peer-reviewed articles about 'Corporate Sustainability Performance' using the Scopus database until May 2018. We will perform a bibliometric study and an expert classification to get detailed research on Corporate Sustainability and economic performance. The expert analysis's most outstanding conclusion is that 70% of the companies introducing sustainability measures have an operational or financial positive economic impact.
2022-04-29T07:44:40ZBarroso del Toro, AlbertoTort-Martorell Llabrés, XavierCanela, Miguel AngelHas invested in Corporate Sustainability a positive economic return? If so, where is it hitting? Are the benefits only attributable to the environment or also to the shareholders?. This research aims to write a state of the art about the economic impact of being sustainable. We will analyze the 200 most cited peer-reviewed articles about 'Corporate Sustainability Performance' using the Scopus database until May 2018. We will perform a bibliometric study and an expert classification to get detailed research on Corporate Sustainability and economic performance. The expert analysis's most outstanding conclusion is that 70% of the companies introducing sustainability measures have an operational or financial positive economic impact.Analysis and visual exploration of prediction algorithms for public bicycle sharing systemsCortez Ordóñez, Alexandra PiedadVázquez Alcocer, Pere Pauhttp://hdl.handle.net/2117/3633012023-12-24T03:58:16Z2022-03-02T12:52:52ZAnalysis and visual exploration of prediction algorithms for public bicycle sharing systems
Cortez Ordóñez, Alexandra Piedad; Vázquez Alcocer, Pere Pau
Public bicycle sharing systems have become an increasingly popular means of transportation in many cities around the world. However, the information shown in mobile apps or websites is commonly limited to the system’s current status and is of little use for both citizens and responsible planning entities. The vast amount of data produced by these managing systems makes it feasible to elaborate and present predictive models that may help its users in the decision-making process. For example, if a user finds a station empty, the application could provide an estimation of when a new bicycle would be available. In this paper, we explore the suitability of several prediction algorithms applied to this case of bicycle availability, and we present a web-based tool to visually explore their prediction errors under different time frames. Even though a quick quantitative analysis may initially suggest that Random Forest yields a lower error, our visual exploration interface allows us to perform a more thorough analysis and detect subtle but relevant differences between algorithms depending on variables such as the station’s behavior, hourly intervals, days, or types of days (weekdays and weekends). This case illustrates the potential of visual representation together with quantitative metrics to compare prediction algorithms with a higher level of detail, which can, in turn, assist application designers and decision-makers to dynamically adjust the best model for their specific scenarios.
2022-03-02T12:52:52ZCortez Ordóñez, Alexandra PiedadVázquez Alcocer, Pere PauPublic bicycle sharing systems have become an increasingly popular means of transportation in many cities around the world. However, the information shown in mobile apps or websites is commonly limited to the system’s current status and is of little use for both citizens and responsible planning entities. The vast amount of data produced by these managing systems makes it feasible to elaborate and present predictive models that may help its users in the decision-making process. For example, if a user finds a station empty, the application could provide an estimation of when a new bicycle would be available. In this paper, we explore the suitability of several prediction algorithms applied to this case of bicycle availability, and we present a web-based tool to visually explore their prediction errors under different time frames. Even though a quick quantitative analysis may initially suggest that Random Forest yields a lower error, our visual exploration interface allows us to perform a more thorough analysis and detect subtle but relevant differences between algorithms depending on variables such as the station’s behavior, hourly intervals, days, or types of days (weekdays and weekends). This case illustrates the potential of visual representation together with quantitative metrics to compare prediction algorithms with a higher level of detail, which can, in turn, assist application designers and decision-makers to dynamically adjust the best model for their specific scenarios.Detection of spike imbalance prices in the French electricity market using machine-learning methodsBarbero, MattiaGuillain, PierreCorchero García, CristinaPerroy, Edouardhttp://hdl.handle.net/2117/3530932023-07-30T04:37:41Z2021-10-06T08:47:43ZDetection of spike imbalance prices in the French electricity market using machine-learning methods
Barbero, Mattia; Guillain, Pierre; Corchero García, Cristina; Perroy, Edouard
Electricity price is a key factor in determining short¿term operating schedules and bidding strategies in competitive electricity markets for retailers, Balance Responsible Parties and Aggregators. However, forecasting spike prices in imbalance markets may prove particularly challenging, due to the nature of the service. This study proposes a new day-ahead classification method to detect winter spike prices occurrences using an ensemble of Support Vector Machine, Random Forest and Extreme Gradient Boosting. Results over 2019 imbalance prices show that the method can correctly forecast almost half of the days in which a spike price occurred, with just 25% of false positives. Economic results are even more encouraging as the real value of the correctly predicted spike days is about six times higher than that of the days wrongly predicted, having almost the same number of days.
2021-10-06T08:47:43ZBarbero, MattiaGuillain, PierreCorchero García, CristinaPerroy, EdouardElectricity price is a key factor in determining short¿term operating schedules and bidding strategies in competitive electricity markets for retailers, Balance Responsible Parties and Aggregators. However, forecasting spike prices in imbalance markets may prove particularly challenging, due to the nature of the service. This study proposes a new day-ahead classification method to detect winter spike prices occurrences using an ensemble of Support Vector Machine, Random Forest and Extreme Gradient Boosting. Results over 2019 imbalance prices show that the method can correctly forecast almost half of the days in which a spike price occurred, with just 25% of false positives. Economic results are even more encouraging as the real value of the correctly predicted spike days is about six times higher than that of the days wrongly predicted, having almost the same number of days.Data-driven demand flexibility estimation in a commercial buildings from air conditioning and lighting systemBarbero, MattiaRebillas-Loredo, VictoriaValdés, RogerCorchero García, Cristinahttp://hdl.handle.net/2117/3528592023-07-30T02:35:41Z2021-10-01T08:41:09ZData-driven demand flexibility estimation in a commercial buildings from air conditioning and lighting system
Barbero, Mattia; Rebillas-Loredo, Victoria; Valdés, Roger; Corchero García, Cristina
Renewable and distributed energy sources, with photovoltaic in the first place, are leading the energy transition. However, they alone will hardly find the way to success in this challenge because of their intrinsic limitations, such as their dependency on weather condition and the unpredictability of their production. Demand Response services are considered crucial for the integration of renewable sources in the grid. This study presents a methodology to evaluate potential flexibility in commercial buildings by managing air conditioning and lighting systems of the site. The study proposes two different data-driven approaches to evaluate flexibility depending on the technology considered. For lighting systems, flexibility is evaluated using the XGBoost classification algorithm combined with a piecewise function. The thermal behavior of the building is modeled with a simplified RC equivalent state-space model. For both algorithms, preprocessing showed to be a critical part of the process, which is explained stage-by-stage in the paper. Results show that the lighting flexibility algorithm is very reliable, reaching an average error of less than 1 % during the months considered. The simplified thermal modeling proposed shows promising results, having less than 0.2 o C of RMSE error for the internal temperature forecast. In addition, results show the flexibility potentiality of the building, which is potentially able to shift up to 23 % of its power consumption during certain hours of the day. This opens huge opportunities for taking advantage from dynamic tariffs, increase self-consumption from renewable sources or participate in flexibility markets to reduce buildings' electricity bill and help renewable integration.
2021-10-01T08:41:09ZBarbero, MattiaRebillas-Loredo, VictoriaValdés, RogerCorchero García, CristinaRenewable and distributed energy sources, with photovoltaic in the first place, are leading the energy transition. However, they alone will hardly find the way to success in this challenge because of their intrinsic limitations, such as their dependency on weather condition and the unpredictability of their production. Demand Response services are considered crucial for the integration of renewable sources in the grid. This study presents a methodology to evaluate potential flexibility in commercial buildings by managing air conditioning and lighting systems of the site. The study proposes two different data-driven approaches to evaluate flexibility depending on the technology considered. For lighting systems, flexibility is evaluated using the XGBoost classification algorithm combined with a piecewise function. The thermal behavior of the building is modeled with a simplified RC equivalent state-space model. For both algorithms, preprocessing showed to be a critical part of the process, which is explained stage-by-stage in the paper. Results show that the lighting flexibility algorithm is very reliable, reaching an average error of less than 1 % during the months considered. The simplified thermal modeling proposed shows promising results, having less than 0.2 o C of RMSE error for the internal temperature forecast. In addition, results show the flexibility potentiality of the building, which is potentially able to shift up to 23 % of its power consumption during certain hours of the day. This opens huge opportunities for taking advantage from dynamic tariffs, increase self-consumption from renewable sources or participate in flexibility markets to reduce buildings' electricity bill and help renewable integration.Estudio de mercados de flexibilidad de la demanda y algoritmos de agregadoresCanals Casals, LlucBarbero, MattiaCorchero García, CristinaIgualada González, Lucíahttp://hdl.handle.net/2117/3521472023-07-30T08:33:12Z2021-09-23T11:30:58ZEstudio de mercados de flexibilidad de la demanda y algoritmos de agregadores
Canals Casals, Lluc; Barbero, Mattia; Corchero García, Cristina; Igualada González, Lucía
La flexibilidad de la demanda implica, siempre, un desplazamiento de la misma buscando un beneficio, aunque este beneficio se pueda obtener por medios distintos: el arbitraje de precios aprovechando la fluctuación del precio de la electricidad o la participación en mercados secundarios o de ajustes. Ambas opciones pueden facilitarse con la implementación de sistemas de gestión inteligentes de la energía, pero la segunda opción presenta ciertas dificultades añadidas además de coordinarse con el operador. El estado de madurez de los mercados de flexibilidad de la demanda es el primer escollo a superar. Aunque Europa esté potenciando su implementación, solamente unos pocos países tienen un marco regulatorio que permita la gestión de la demanda y menos aún que permitan una gestión agregada de la demanda. La gestión de la demanda agregada aparece como respuesta a otra dificultad, el requisito de participación con un mínimo de potencia, capacidad y duración que existe en todos los mercados secundarios. Este valor mínimo se exige para que el cambio en la demanda tenga un impacto significativo en la red. La demanda agregada da la oportunidad de participar en estos mercados a la mayor parte de los consumidores que, en condiciones normales, nunca alcanzarían dichos límites. Otras limitaciones como la duración de la activación de la flexibilidad, el número de activaciones o la velocidad de respuesta también pueden encontrar un buen aliado en la figura del agregador de demanda. Por otro lado, el agregador tiene el reto de saber gestionar bien sus recursos (edificios, generadores, etc.). Existen 2 líneas típicas de investigación, agregadores con pleno conocimiento de la realidad de las fuentes y agregadores que, sin conocer nada, reciben ofertas por parte de los consumidores para ofrecer los servicios. El proyecto SABINA presenta una solución que exige poco conocimiento de las fuentes persiguiendo una reducción del impacto ambiental
2021-09-23T11:30:58ZCanals Casals, LlucBarbero, MattiaCorchero García, CristinaIgualada González, LucíaLa flexibilidad de la demanda implica, siempre, un desplazamiento de la misma buscando un beneficio, aunque este beneficio se pueda obtener por medios distintos: el arbitraje de precios aprovechando la fluctuación del precio de la electricidad o la participación en mercados secundarios o de ajustes. Ambas opciones pueden facilitarse con la implementación de sistemas de gestión inteligentes de la energía, pero la segunda opción presenta ciertas dificultades añadidas además de coordinarse con el operador. El estado de madurez de los mercados de flexibilidad de la demanda es el primer escollo a superar. Aunque Europa esté potenciando su implementación, solamente unos pocos países tienen un marco regulatorio que permita la gestión de la demanda y menos aún que permitan una gestión agregada de la demanda. La gestión de la demanda agregada aparece como respuesta a otra dificultad, el requisito de participación con un mínimo de potencia, capacidad y duración que existe en todos los mercados secundarios. Este valor mínimo se exige para que el cambio en la demanda tenga un impacto significativo en la red. La demanda agregada da la oportunidad de participar en estos mercados a la mayor parte de los consumidores que, en condiciones normales, nunca alcanzarían dichos límites. Otras limitaciones como la duración de la activación de la flexibilidad, el número de activaciones o la velocidad de respuesta también pueden encontrar un buen aliado en la figura del agregador de demanda. Por otro lado, el agregador tiene el reto de saber gestionar bien sus recursos (edificios, generadores, etc.). Existen 2 líneas típicas de investigación, agregadores con pleno conocimiento de la realidad de las fuentes y agregadores que, sin conocer nada, reciben ofertas por parte de los consumidores para ofrecer los servicios. El proyecto SABINA presenta una solución que exige poco conocimiento de las fuentes persiguiendo una reducción del impacto ambiental