Development of an environmental and economic optimization model for distributed generation energy systems

Abstract

The reduction of pollutant emissions is one of the current main targets fixed by the most important international authorities. The reduction of the energy needs in the residential-tertiary sector can help achieving this goal, as it represents one of the dominant energy consuming sectors in industrialized societies. However the adoption of an energy system still depend on technical and economical evaluations, while environmental considerations are not taken into consideration yet. For this reason, a development of a tool for the selection of an energy system which allows the reduction of the overall costs containing in the meanwhile the pollutant emissions could help reaching the environmental targets. The thesis proposes a methodology for the Multiobjective optimization of a Dis- tributed Generation Energy System. Such a system is normally constituted by several users connected to each other and to a central unit through a District Heating Network. Furthermore, each unit can be equipped with an internal production unit for the production of its energy needs. Therefore, the determination of the optimal energy system requires the simultaneous optimization of the synthesis, design and operation of the whole energy system. The total annual cost for owning, operating and maintaining the whole system is considered as economic objective function, while the total annual operation CO2 emissions is considered as environmental objective function. An optimization MILP model for the optimization of tertiary sector Distributed Generation Energy Systems is developed and is applied to a real case study, made up of nine tertiary sector users located in a small town city center situated in the North-East of Italy. A preliminary energy audit allowed the determination of the users\u2019 energy needs. The energy system is optimized for different configurations in order to understand how different components affect the optimal solution

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