Multi-objective, multi-period optimization of biomass conversion technologies using evolutionary algorithms and mixed integer linear programming (MILP)

The design and operation of energy systems are key issues for matching energy supply and demand. A systematic procedure, including process design and energy integration techniques for sizing and operation optimization of poly-generation technologies is presented in this paper. The integration of bio...

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Vydané v:	Applied thermal engineering Ročník 50; číslo 2; s. 1504 - 1513
Hlavní autori:	Fazlollahi, Samira, Maréchal, François
Médium:	Journal Article Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	Kidlington Elsevier Ltd 01.02.2013 Elsevier
Predmet:	Applied sciences Biomass Biomass conversion technologies CO2 mitigation Conversion Design engineering Energy Energy. Thermal use of fuels Engines and turbines Equipments for energy generation and conversion: thermal, electrical, mechanical energy, etc Evolutionary algorithm Exact sciences and technology Heat transfer Mixed integer Mixed integer linear programming Natural energy Optimization Poly-generation systems Sizing Supply and demand Theoretical studies. Data and constants. Metering Thermal engineering CO2 mitigation Poly-generation systems Mixed integer linear programming Evolutionary algorithm Biomass conversion technologies Costs Profitability Pollution control Biomass Pollutant emission Modeling Optimization Energy supply Energy conservation Gasification Gas engine Steam turbine mitigation Pollution prevention Linear programming CO Algorithm Case study Integer programming Combined cycle Renewable energy Supply demand balance Rankine cycle Primary energy Electric power production Gas turbine Cost analysis Natural gas
ISSN:	1359-4311
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Abstract	The design and operation of energy systems are key issues for matching energy supply and demand. A systematic procedure, including process design and energy integration techniques for sizing and operation optimization of poly-generation technologies is presented in this paper. The integration of biomass resources as well as a simultaneous multi-objective and multi-period optimization, are the novelty of this work. Considering all these concepts in an optimization model makes it difficult to solve. The decomposition approach is used to deal with this complexity. Several options for integrating biomass in the energy system, namely back pressure steam turbines, biomass rankine cycles (BRC), biomass integrated gasification gas engines (BIGGE), biomass integrated gasification gas turbines, production of synthetic natural gas (SNG) and biomass integrated gasification combined cycles (BIGCC), are considered in this paper. The goal is to simultaneously minimize costs and CO2 emission using multi-objective evolutionary algorithms (EMOO) and Mixed Integer Linear Programming (MILP). Finally the proposed model is demonstrated by means of a case study. The results show that the simultaneous production of electricity and heat with biomass and natural gas are reliable upon the established assumptions. Furthermore, higher primary energy savings and CO2 emission reduction, 40%, are obtained through the gradual increase of renewable energy sources as opposed to natural gas usage. However, higher economic profitability, 52%, is achieved with natural gas-based technologies. ► Proposing a systematic procedure for the preliminary design of integrated urban energy systems. ► The consideration of the decomposition approach, with the multi-periods and multi-objective aspects. ► Results show the simultaneous production of electricity and heat with biomass and natural gas are reliable upon the established assumptions. ► Higher primary energy savings and CO2 emission reduction are obtained through the gradual increase of renewable energy. ► Higher economic profitability is yet achieved with natural gas-based technologies.
AbstractList	The design and operation of energy systems are key issues for matching energy supply and demand. A systematic procedure, including process design and energy integration techniques for sizing and operation optimization of poly-generation technologies is presented in this paper. The integration of biomass resources as well as a simultaneous multi-objective and multi-period optimization, are the novelty of this work. Considering all these concepts in an optimization model makes it difficult to solve. The decomposition approach is used to deal with this complexity. The design and operation of energy systems are key issues for matching energy supply and demand. A systematic procedure, including process design and energy integration techniques for sizing and operation optimization of poly-generation technologies is presented in this paper. The integration of biomass resources as well as a simultaneous multi-objective and multi-period optimization, are the novelty of this work. Considering all these concepts in an optimization model makes it difficult to solve. The decomposition approach is used to deal with this complexity. Several options for integrating biomass in the energy system, namely back pressure steam turbines, biomass rankine cycles (BRC), biomass integrated gasification gas engines (BIGGE), biomass integrated gasification gas turbines, production of synthetic natural gas (SNG) and biomass integrated gasification combined cycles (BIGCC), are considered in this paper. The goal is to simultaneously minimize costs and CO2 emission using multi-objective evolutionary algorithms (EMOO) and Mixed Integer Linear Programming (MILP). Finally the proposed model is demonstrated by means of a case study. The results show that the simultaneous production of electricity and heat with biomass and natural gas are reliable upon the established assumptions. Furthermore, higher primary energy savings and CO2 emission reduction, 40%, are obtained through the gradual increase of renewable energy sources as opposed to natural gas usage. However, higher economic profitability, 52%, is achieved with natural gas-based technologies. ► Proposing a systematic procedure for the preliminary design of integrated urban energy systems. ► The consideration of the decomposition approach, with the multi-periods and multi-objective aspects. ► Results show the simultaneous production of electricity and heat with biomass and natural gas are reliable upon the established assumptions. ► Higher primary energy savings and CO2 emission reduction are obtained through the gradual increase of renewable energy. ► Higher economic profitability is yet achieved with natural gas-based technologies.
Author	Maréchal, François Fazlollahi, Samira
Author_xml	– sequence: 1 givenname: Samira surname: Fazlollahi fullname: Fazlollahi, Samira email: samira.fazlollahi@epfl.ch organization: Veolia Environnement Recherche et Innovation (VERI), 291 avenue Dreyfous Ducas, 78520 Limay, France – sequence: 2 givenname: François surname: Maréchal fullname: Maréchal, François email: francois.marechal@epfl.ch organization: Ecole Polytechnique Federale de Lausanne, LENI-IGM-STI-EPFL Station 9- 1015 Lausanne, Switzerland
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Keywords	CO2 mitigation Poly-generation systems Mixed integer linear programming Evolutionary algorithm Biomass conversion technologies Costs Profitability Pollution control Biomass Pollutant emission Modeling Optimization Energy supply Energy conservation Gasification Gas engine Steam turbine mitigation Pollution prevention Linear programming CO Algorithm Case study Integer programming Combined cycle Renewable energy Supply demand balance Rankine cycle Primary energy Electric power production Gas turbine Cost analysis Natural gas
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SubjectTerms	Applied sciences Biomass Biomass conversion technologies CO2 mitigation Conversion Design engineering Energy Energy. Thermal use of fuels Engines and turbines Equipments for energy generation and conversion: thermal, electrical, mechanical energy, etc Evolutionary algorithm Exact sciences and technology Heat transfer Mixed integer Mixed integer linear programming Natural energy Optimization Poly-generation systems Sizing Supply and demand Theoretical studies. Data and constants. Metering Thermal engineering
Title	Multi-objective, multi-period optimization of biomass conversion technologies using evolutionary algorithms and mixed integer linear programming (MILP)
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