Modeling and optimization of a hybrid system for the energy supply of a “Green” building

► The system model is embedded in a dynamic decision model. ► The model has been applied to a specific case study. ► Optimal results are reported for two main cases: the presence/absence of the energy storage system. Renewable energy sources (RES) are an “indigenous” environmental option, economical...

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Vydáno v:Energy conversion and management Ročník 64; s. 351 - 363
Hlavní autoři: Dagdougui, Hanane, Minciardi, Riccardo, Ouammi, Ahmed, Robba, Michela, Sacile, Roberto
Médium: Journal Article
Jazyk:angličtina
Vydáno: Kidlington Elsevier Ltd 01.12.2012
Elsevier
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ISSN:0196-8904, 1879-2227
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Abstract ► The system model is embedded in a dynamic decision model. ► The model has been applied to a specific case study. ► Optimal results are reported for two main cases: the presence/absence of the energy storage system. Renewable energy sources (RES) are an “indigenous” environmental option, economically competitive with conventional power generation where good wind and solar resources are available. Hybrid systems can help in improving the economic and environmental sustainability of renewable energy systems to fulfill the energy demand. The aim of this paper is to present a dynamic model able to integrate different RES and one storage device to feed a “Green” building for its thermal and electrical energy needs in a sustainable way. The system model is embedded in a dynamic decision model and is used to optimize a quite complex hybrid system connected to the grid which can exploit different renewable energy sources. A Model Predictive Control (MPC) is adopted to find the optimal solution. The optimization model has been applied to a case study where electric energy is also used to pump water for domestic use. Optimal results are reported for two main cases: the presence/absence of the energy storage system.
AbstractList Renewable energy sources (RES) are an “indigenous” environmental option, economically competitive with conventional power generation where good wind and solar resources are available. Hybrid systems can help in improving the economic and environmental sustainability of renewable energy systems to fulfill the energy demand. The aim of this paper is to present a dynamic model able to integrate different RES and one storage device to feed a “Green” building for its thermal and electrical energy needs in a sustainable way. The system model is embedded in a dynamic decision model and is used to optimize a quite complex hybrid system connected to the grid which can exploit different renewable energy sources. A Model Predictive Control (MPC) is adopted to find the optimal solution. The optimization model has been applied to a case study where electric energy is also used to pump water for domestic use. Optimal results are reported for two main cases: the presence/absence of the energy storage system.
► The system model is embedded in a dynamic decision model. ► The model has been applied to a specific case study. ► Optimal results are reported for two main cases: the presence/absence of the energy storage system. Renewable energy sources (RES) are an “indigenous” environmental option, economically competitive with conventional power generation where good wind and solar resources are available. Hybrid systems can help in improving the economic and environmental sustainability of renewable energy systems to fulfill the energy demand. The aim of this paper is to present a dynamic model able to integrate different RES and one storage device to feed a “Green” building for its thermal and electrical energy needs in a sustainable way. The system model is embedded in a dynamic decision model and is used to optimize a quite complex hybrid system connected to the grid which can exploit different renewable energy sources. A Model Predictive Control (MPC) is adopted to find the optimal solution. The optimization model has been applied to a case study where electric energy is also used to pump water for domestic use. Optimal results are reported for two main cases: the presence/absence of the energy storage system.
Author Robba, Michela
Sacile, Roberto
Dagdougui, Hanane
Ouammi, Ahmed
Minciardi, Riccardo
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  givenname: Riccardo
  surname: Minciardi
  fullname: Minciardi, Riccardo
  organization: Department of Communication, Computer and System Sciences (DIST), Faculty of Engineering, University of Genoa, Genoa, Italy
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  givenname: Ahmed
  surname: Ouammi
  fullname: Ouammi, Ahmed
  email: ouammi@cnrst.ma
  organization: Unité des Technologies et Economie des Energies Renouvelables, CNRST BP 8027 NU Rabat, Morocco
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  givenname: Michela
  surname: Robba
  fullname: Robba, Michela
  organization: Department of Communication, Computer and System Sciences (DIST), Faculty of Engineering, University of Genoa, Genoa, Italy
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  givenname: Roberto
  surname: Sacile
  fullname: Sacile, Roberto
  organization: Department of Communication, Computer and System Sciences (DIST), Faculty of Engineering, University of Genoa, Genoa, Italy
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Keywords Decision support systems
Renewable energy systems
Green building
Smart grid
Optimization
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Snippet ► The system model is embedded in a dynamic decision model. ► The model has been applied to a specific case study. ► Optimal results are reported for two main...
Renewable energy sources (RES) are an “indigenous” environmental option, economically competitive with conventional power generation where good wind and solar...
Renewable energy sources (RES) are an "indigenous" environmental option, economically competitive with conventional power generation where good wind and solar...
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SubjectTerms Applied sciences
case studies
Crisis and risk management
Decision support systems
dynamic models
Energy
Environmental Sciences
environmental sustainability
Exact sciences and technology
Green building
Humanities and Social Sciences
Optimization
power generation
renewable energy sources
Renewable energy systems
Smart grid
wind
Title Modeling and optimization of a hybrid system for the energy supply of a “Green” building
URI https://dx.doi.org/10.1016/j.enconman.2012.05.017
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