Now showing items 1-9 of 9

    • Activity-aware HVAC power demand forecasting 

      Sala Cardoso, Enric; Delgado Prieto, Miquel; Kampouropoulos, Konstantinos; Romeral Martínez, José Luis (2018-07-01)
      Article
      Open Access
      The forecasting of the thermal power demand is essential to support the development of advanced strategies for the management of local resources on the consumer side, such as heating ventilation and air conditioning (HVAC) ...
    • Advanced energy management strategies for HVAC systems in smart buildings 

      Sala Cardoso, Enric (Universitat Politècnica de Catalunya, 2019-12-16)
      Doctoral thesis
      Open Access
      The efficacy of the energy management systems at dealing with energy consumption in buildings has been a topic with a growing interest in recent years due to the ever-increasing global energy demand and the large percentage ...
    • Constrained-size torque maximization in SynRM machines by means of genetic algorithms 

      López Torres, Carlos; Sala Cardoso, Enric; García Espinosa, Antonio; Romeral Martínez, José Luis (2015)
      Conference report
      Restricted access - publisher's policy
      Synchronous Reluctance Motors have always been an alternative to more mainstream machines such as the Permanent Magnet Synchronous Motor, but until recently they have not found their right place in industrial applications. ...
    • Estimation of fuel consumption in a hybrid electric refuse collector vehicle using a real drive cycle 

      Cortez, Ernest; Moreno Eguilaz, Juan Manuel; Soriano, Francisco; Sala Cardoso, Enric (IEEE Press, 2016)
      Conference report
      Open Access
    • Industrial process monitoring by means of recurrent neural networks and Self Organizing Maps 

      Zurita Millán, Daniel; Sala Cardoso, Enric; Cariño Corrales, Jesús Adolfo; Delgado Prieto, Miquel; Ortega Redondo, Juan Antonio (IEEE Press, 2016)
      Conference report
      Open Access
      Industrial manufacturing plants often suffer from reliability problems during their day-to-day operations which have the potential for causing a great impact on the effectiveness and performance of the overall process and ...
    • Multiobjective optimization of multi-carrier energy system using a combination of ANFIS and genetic algorithms 

      Kampouropoulos, Konstantinos; Andrade, Fabio; Sala Cardoso, Enric; García Espinosa, Antonio; Romeral Martínez, José Luis (Institute of Electrical and Electronics Engineers (IEEE), 2018-05-01)
      Article
      Open Access
      This paper presents a novel method for the energy optimization of multi-carrier energy systems. The presented method combines an adaptive neuro-fuzzy inference system, to model and forecast the power demand of a plant, and ...
    • Optimal control of energy hub systems by use of SQP algorithm and energy prediction 

      Kampouropoulos, Konstantinos; Sala Cardoso, Enric; Andrade, Fabio; Romeral Martínez, José Luis (2014)
      Conference report
      Restricted access - publisher's policy
      This paper presents an energy optimization methodology applied on industrial plants with multiple energy carriers. The methodology combines an adaptive neuro-fuzzy inference system to calculate the short-term load forecasting ...
    • Predictive chiller operation: a data-driven loading and scheduling approach 

      Sala Cardoso, Enric; Delgado Prieto, Miquel; Kampouropoulos, Konstantinos; Romeral Martínez, José Luis (2019-01-01)
      Article
      Restricted access - publisher's policy
      The proper sequencing and optimal loading of chillers is one of the major avenues for energy efficiency improvement in existing heating, ventilating and air conditioning installations. The main enabler for the success of ...
    • Smart multi-model approach based on adaptive neuro-fuzzy inference systems and genetic algorithms 

      Sala Cardoso, Enric; Kampouropoulos, Konstantinos; Giacometto Torres, Francisco; Romeral Martínez, José Luis (2014)
      Conference report
      Restricted access - publisher's policy
      A model of power demand represents the foundation of any intelligent Energy Management System, and its accuracy is the key factor determining the performance of such system. In order to improve the accuracy of the modeling ...