The sector of energy use in buildings accounts for a substantial portion of the global energy consumption and greenhouse gas (GHG) emissions, representing a large potential for energy savings and emissions reduction. In this sense, the concept of energy community (EC) has become gradually more attractive due to the potential of reducing both energy consumption and GHG emissions. In such a scenario, polygeneration systems emerge as advantageous energy supply systems. They can efficiently meet the energy demands of buildings by producing multiple energy services from a single energy resource and be supported by renewable energy sources (RES) and thermal energy storage (TES). However, defining an optimal configuration and operational strategy for polygeneration systems is a multifaceted task which becomes even more complex when considering the integration of buildings (powered by polygeneration systems) into an EC. The reasons for this include the several types of considered technologies, their interrelations, and the intrinsic dynamic behavior of buildings. On top of that, the issue of defining the best operational approach, for such complex systems, according to variations on the energy services demand still remains. Based on this framework, this thesis aims to define a method for defining the optimal synthesis and operation of polygeneration systems integrated into ECs, based on a mixed integer linear programming (MILP) model, and grounded on three main pillars: (i) the multi-objective optimization of an EC powered by polygeneration systems and sharing electricity, heating, and cooling among the buildings, (ii) the propose of a thermoeconomic analysis (through marginal costs) to evaluate the best operational strategy according to variations on the energy services demand, when there is thermal energy transfer through heating and/or cooling pipelines, and (iii) evaluate the role of such ECs in the economic and environmental aspects of a future Italian energy system scenario by using a local optimization approach. Therefore, the main contributions of this thesis are the multi-objective optimization of a complex and highly integrated polygeneration system aimed for ECs (and supported by thermal energy storages, district heating and cooling network pipelines, and the sharing of purchased and self-produced electricity among the buildings), the analysis and interpretation of the hourly marginal costs and, consequently, the definition of the best operation strategy for the case of energy demand variations in any building of the EC, and the outline of different optimal marginal paths through different modes of energy services production.

The sector of energy use in buildings accounts for a substantial portion of the global energy consumption and greenhouse gas (GHG) emissions, representing a large potential for energy savings and emissions reduction. In this sense, the concept of energy community (EC) has become gradually more attractive due to the potential of reducing both energy consumption and GHG emissions. In such a scenario, polygeneration systems emerge as advantageous energy supply systems. They can efficiently meet the energy demands of buildings by producing multiple energy services from a single energy resource and be supported by renewable energy sources (RES) and thermal energy storage (TES). However, defining an optimal configuration and operational strategy for polygeneration systems is a multifaceted task which becomes even more complex when considering the integration of buildings (powered by polygeneration systems) into an EC. The reasons for this include the several types of considered technologies, their interrelations, and the intrinsic dynamic behavior of buildings. On top of that, the issue of defining the best operational approach, for such complex systems, according to variations on the energy services demand still remains. Based on this framework, this thesis aims to define a method for defining the optimal synthesis and operation of polygeneration systems integrated into ECs, based on a mixed integer linear programming (MILP) model, and grounded on three main pillars: (i) the multi-objective optimization of an EC powered by polygeneration systems and sharing electricity, heating, and cooling among the buildings, (ii) the propose of a thermoeconomic analysis (through marginal costs) to evaluate the best operational strategy according to variations on the energy services demand, when there is thermal energy transfer through heating and/or cooling pipelines, and (iii) evaluate the role of such ECs in the economic and environmental aspects of a future Italian energy system scenario by using a local optimization approach. Therefore, the main contributions of this thesis are the multi-objective optimization of a complex and highly integrated polygeneration system aimed for ECs (and supported by thermal energy storages, district heating and cooling network pipelines, and the sharing of purchased and self-produced electricity among the buildings), the analysis and interpretation of the hourly marginal costs and, consequently, the definition of the best operation strategy for the case of energy demand variations in any building of the EC, and the outline of different optimal marginal paths through different modes of energy services production.

Optimal Synthesis, Operation, and Thermoeconomic Analysis of Distributed Polygeneration Systems for Energy Communities / DE SOUZA, RONELLY JOSÉ. - (2024 Jun 10).

Optimal Synthesis, Operation, and Thermoeconomic Analysis of Distributed Polygeneration Systems for Energy Communities

DE SOUZA, RONELLY JOSÉ
2024-06-10

Abstract

The sector of energy use in buildings accounts for a substantial portion of the global energy consumption and greenhouse gas (GHG) emissions, representing a large potential for energy savings and emissions reduction. In this sense, the concept of energy community (EC) has become gradually more attractive due to the potential of reducing both energy consumption and GHG emissions. In such a scenario, polygeneration systems emerge as advantageous energy supply systems. They can efficiently meet the energy demands of buildings by producing multiple energy services from a single energy resource and be supported by renewable energy sources (RES) and thermal energy storage (TES). However, defining an optimal configuration and operational strategy for polygeneration systems is a multifaceted task which becomes even more complex when considering the integration of buildings (powered by polygeneration systems) into an EC. The reasons for this include the several types of considered technologies, their interrelations, and the intrinsic dynamic behavior of buildings. On top of that, the issue of defining the best operational approach, for such complex systems, according to variations on the energy services demand still remains. Based on this framework, this thesis aims to define a method for defining the optimal synthesis and operation of polygeneration systems integrated into ECs, based on a mixed integer linear programming (MILP) model, and grounded on three main pillars: (i) the multi-objective optimization of an EC powered by polygeneration systems and sharing electricity, heating, and cooling among the buildings, (ii) the propose of a thermoeconomic analysis (through marginal costs) to evaluate the best operational strategy according to variations on the energy services demand, when there is thermal energy transfer through heating and/or cooling pipelines, and (iii) evaluate the role of such ECs in the economic and environmental aspects of a future Italian energy system scenario by using a local optimization approach. Therefore, the main contributions of this thesis are the multi-objective optimization of a complex and highly integrated polygeneration system aimed for ECs (and supported by thermal energy storages, district heating and cooling network pipelines, and the sharing of purchased and self-produced electricity among the buildings), the analysis and interpretation of the hourly marginal costs and, consequently, the definition of the best operation strategy for the case of energy demand variations in any building of the EC, and the outline of different optimal marginal paths through different modes of energy services production.
10-giu-2024
REINI, MAURO
36
2022/2023
Settore ING-IND/09 - Sistemi per l'Energia e L'Ambiente
Università degli Studi di Trieste
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3077578
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