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Polygeneration systems in buildings: A survey on optimization approaches
HighlightsChallenges for polygeneration optimization for building applications.(Smart) polygeneration microgrid for building applications.Characteristics of optimization for micro- and small-scale polygeneration systems.Optimization techniques for micro- and small-scale polygeneration systems.Visons for (Smart) Polygeneration (Microgrid) optimization.
AbstractPolygeneration is an integrated process that produces two or more energy products from one or more primary energy sources (PES). Polygeneration systems have wide applications in utilities, industrial sectors and building sectors. However, there are still very limited applications of the powerful and practical optimization techniques in polygeneration systems of building sectors comparing to their wide applications in industrial sectors. System optimization is one of effective and reasonable tools to exploit the potential of polygeneration systems. Polygeneration offers potential to fulfill the ambitious target of zero energy building (ZEB) because the interdependence of different energy products can be utilized to provide advantage and flexibility to accommodate more renewable energy sources (RES) in the system. Polygeneration based ZEB can be treated as a type of Polygeneration Microgrid (PM) because PM represents a promising solution to supply electricity, heat and cooling efficiently using local energy sources, including RES. The development of PM is closely associated with building applications.Hence, the objective of the present paper is to give a comprehensive review for optimization techniques of polygeneration systems in buildings. The review was conducted based on integrated design, synthesis and operation optimization (IDSOO) for different scales of systems, ranging from the micro-scale for a single house to the large-scale for a residential complex, including PM to identify difference between traditional systems and PM in terms of optimization. The literature was classified according to solution techniques of IDSOO and characteristics of IDSOO in terms of decision variables, objective functions and constraints. The results showed that there is no significant difference between traditional systems and PM in terms of solution techniques while there is subtle difference between traditional systems and PM in terms of objective function and constraints. Optimization of PM has higher requirements for real-time management to integrate more RES. Optimization of micro- and small-scale systems are more complicated than large-scale ones because there are many constraints from technical, legal and policy viewpoints.
Polygeneration systems in buildings: A survey on optimization approaches
HighlightsChallenges for polygeneration optimization for building applications.(Smart) polygeneration microgrid for building applications.Characteristics of optimization for micro- and small-scale polygeneration systems.Optimization techniques for micro- and small-scale polygeneration systems.Visons for (Smart) Polygeneration (Microgrid) optimization.
AbstractPolygeneration is an integrated process that produces two or more energy products from one or more primary energy sources (PES). Polygeneration systems have wide applications in utilities, industrial sectors and building sectors. However, there are still very limited applications of the powerful and practical optimization techniques in polygeneration systems of building sectors comparing to their wide applications in industrial sectors. System optimization is one of effective and reasonable tools to exploit the potential of polygeneration systems. Polygeneration offers potential to fulfill the ambitious target of zero energy building (ZEB) because the interdependence of different energy products can be utilized to provide advantage and flexibility to accommodate more renewable energy sources (RES) in the system. Polygeneration based ZEB can be treated as a type of Polygeneration Microgrid (PM) because PM represents a promising solution to supply electricity, heat and cooling efficiently using local energy sources, including RES. The development of PM is closely associated with building applications.Hence, the objective of the present paper is to give a comprehensive review for optimization techniques of polygeneration systems in buildings. The review was conducted based on integrated design, synthesis and operation optimization (IDSOO) for different scales of systems, ranging from the micro-scale for a single house to the large-scale for a residential complex, including PM to identify difference between traditional systems and PM in terms of optimization. The literature was classified according to solution techniques of IDSOO and characteristics of IDSOO in terms of decision variables, objective functions and constraints. The results showed that there is no significant difference between traditional systems and PM in terms of solution techniques while there is subtle difference between traditional systems and PM in terms of objective function and constraints. Optimization of PM has higher requirements for real-time management to integrate more RES. Optimization of micro- and small-scale systems are more complicated than large-scale ones because there are many constraints from technical, legal and policy viewpoints.
Polygeneration systems in buildings: A survey on optimization approaches
Rong, Aiying (author) / Su, Yan (author)
Energy and Buildings ; 151 ; 439-454
2017-06-30
16 pages
Article (Journal)
Electronic Resource
English
AB , auxiliary boiler , AC , absorption chiller , APM , autonomous polygeneration grid , ATD , aggregate thermal demand (additional variables and constraints) , BB , branch and bound algorithm , BG , biomass gasification system (additional variables and constraints) , CCHP , combined cooling, heating and power , CHP , combined heat and power , DEMS , decentralized energy management system (design scheme for smart grid) , DES , distributed energy system(s) , DG , distributed generation , DH , district heating , DHC , district heating and cooling , DHP , district heating parameters (additional variables and constraints) , DSM , demand side management (additional variables and constraints) , EA , evolutionary algorithm , EABOT , energy analysis based optimization of trigeneration plant , EBC , energy in buildings and communities , EC , electric chiller , ED , economic dispatch , EE , energy efficiency (additional variables and constraints) , EEC , energy efficiency certificate (objective) , EEE , equivalent electrical efficiency of the CHP plant (additional variables and constraints) , EES , electric energy storage , EH , electric heater , Epsilon-c , epsilon-constraint , EU , European Union , FC , fuel cell , FCM , fuzzy cognitive map , FEL , following electric load , FTL , following thermal load , FW , fresh water (additional variables and constraints) , GA , genetic algorithm , GE , gas engine , GRG , generalized reduced gradient algorithm , GT , gas turbine , HO , hierarchical optimization , HP , heat pump , HRS , heat recovery system , HS , hydrogen storage , HU , heating unit , HVAC , heating, ventilation, air conditioning , HX , heat exchanger (additional variables and constraints) , IC , internal combustion engine , IDSOO , integrated design, synthesis and operation optimization , LCA , life cycle analysis (assessment) , IEA , international energy agency , IIF , independent of imported fuels (additional constraints) , LZEB , life-time zero energy building balance (additional constraints) , MAS , multi-agent system , MCUD , maximum contract utility demands (additional variables and constraints) , MDT , minimum down time , MILP , mixed integer linear programming , MINLP , mixed integer non-linear programming , MOO , multiple objective optimization , MPC , model predictive control , MPGA , multiple population genetic algorithm , MT , micro gas turbine , MUT , minimum up time , NSGA-II , non-dominated sorting genetic algorithm-II , ONF , ON/OFF state of the component (additional variables and constraints) , ONFG , the system is connected to the grid or not (additional variables and constraints) , ONFP , ON/OFF state of the polygeneration plant (additional variables and constraints) , O&M , operation and maintenance , PAT , pump as turbine , PEMFC , proton exchange membrane fuel cell , PEV , plug-in electrical vehicle , PES , primary energy sources , PF , Pareto Frontier , PGU , power generation unit , PHX , (local) power and hot water exchange (additional variables and constraints) , PM , polygeneration microgrid , PPP , plant process parameters (additional variables and constraints) , PS , peak shaving (one component of DSM) , PSO , particle swarm optimization , PTS , pricing tariff , PV , photovoltaics (solar) , PWT , potable water tank , RECC , ratio of electric cooling and cooling load (additional variables and constraints) , RUP , ramp-up of the polygeneration plant (additional variables and constraints) , RES , renewable energy source(s) , SA , sensitivity analysis , SCR , self consumption ratio , SE , Stirling engine , SEOE , scale effect on efficiency (additional constraints) , SG , smart grid , SH , solar heater , SOFC , solid oxide fuel cell , SOO , single objective optimization , SPM , Smart polygeneration microgrid , SS , start-up and shut-down of the component (additional variables and constraints) , STP1 , special tariff for polygeneration in terms of fuel (PES) , STP2 , special tariff for polygeneration in terms of sold power , STR2 , special tariff for RES in terms of sold power , ST , steam turbine , TAT , thermal activated technology , TES , thermal energy storage , UC , unit commitment , ZEB , zero energy buildings , Polygeneration system , (Smart) polygeneration microgrids , Zero energy building (ZEB) , Energy efficiency , Optimization techniques , Building applications
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