Optimal Planning and Economic Evaluation of Trigeneration Districts

Maria Teresa Vespucci (), Stefano Zigrino (), Francesca Bazzocchi and Alberto Gelmini ()
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Maria Teresa Vespucci: University of Bergamo
Stefano Zigrino: University of Bergamo
Francesca Bazzocchi: Ricerca sul Sistema Energetico (RSE) SpA
Alberto Gelmini: Ricerca sul Sistema Energetico (RSE) SpA

Chapter Chapter 11 in Handbook of Risk Management in Energy Production and Trading, 2013, pp 259-282 from Springer

Abstract: Abstract Trigeneration, or combined cooling, heat and power (CCHP), is the process by which electricity, heating and cooling are simultaneously generated from the combustion of a fuel. Trigeneration systems for serving the electricity, thermal and cooling loads in residential districts are a possible solution to enhance energy efficiency, reduce fossil fuel consumption and increase the use of renewable energy sources in the residential sector. Technical, economical and financial issues have to be taken into account when planning a trigeneration system or when expanding an existing generation system. In this chapter a two-step decision support procedure is presented for analysing alternative system configurations. The first step is based on a mixed integer linear programming model that allows to describe the system components in great detail and computes the annual optimal dispatch of the distributed generation system with a hourly discretization, taking into account load profiles, fuel costs and technical constraints. The optimal dispatch is then used for the economic evaluation of the investment, taking into account prices of commodities, taxation, incentives and financial aspects. The procedure allows to compare alternative plant configurations and can be used as a simulation tool, for assessing the system sensitivity to variations of model parameters (e.g. incentives and ratio debt/equity).

Keywords: Heat Pump; Trigeneration System; Mixed Integer Linear Programming Model; Cooling Load; Binary Parameter (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/978-1-4614-9035-7_11

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