Involving Environmental Assessment in the Optimal Design of Domestic Cogeneration Systems

Abstract

This paper presents a multi-objective optimization formulation for designing domestic cogeneration systems to satisfy thermal and electric energy demands. The proposed model is formulated as a multi-objective mixed-integer nonlinear programming model, which incorporates as economic objective function the minimization of the total annual cost, which includes the capital costs for the new units and the thermal storage system as well as the operating and maintenance costs. The model also incorporates an environmental objective function, which accounts for the life cycle assessment through the Eco-indicator 99 method to account for the damages to the resources, human health, and ecosystem quality. The proposed model allows considering the interaction with the external users and the external electric grid. The optimization formulation is solved to generate design alternatives to establish tradeoffs among the considered objectives.

Perspectives for Implementing Distributed Generation in Developing Countries through Modeling Techniques

“…57,96,100,121,140,142,143 The second one is to monetize the environmental impact according to local policies or using the ones for developed countries such as carbon tax or bonus. 137,139,141 The third strategy is to use methodologies based on parameters of emissions associated with the resources and pollution generated by the implementation of the facility, 120,136,138 such as the Life Cycle Assessment (LCA). The monetization approach, despite the carbon tax, has been used as a popular policy for controlling the externalities associated with energy production, has been criticized due to the arbitrary economic value used, which is defined by negotiations between policy makers, and is a current topic of discussion for the environmental policy efficiency.…”

“…49,57,162,163 Multiobjective approaches have become fundamental for reaching the trade-off between the economic performance of the system and the environmental impact associated with the implementation and operation of new technologies. The general approaches include exploring different Pareto optimal solutions for presenting configurations, besides the economic behavior of the system, that minimizes the emissions 40,51,57,80,84,97,119,121,136,140,141,143,163 and water consumption, 57,100,163 as well as integral approaches considering multiple environmental impacts, such as the ones based on life cycle assessment methodologies. 120,136 Also, multiobjective techniques have considered accounting for social aspects for developing DG systems.…”

“…The general approaches include exploring different Pareto optimal solutions for presenting configurations, besides the economic behavior of the system, that minimizes the emissions 40,51,57,80,84,97,119,121,136,140,141,143,163 and water consumption, 57,100,163 as well as integral approaches considering multiple environmental impacts, such as the ones based on life cycle assessment methodologies. 120,136 Also, multiobjective techniques have considered accounting for social aspects for developing DG systems. Different than the environmental approach, the social approach includes multiple and different objectives, which have been addressed considering a compromise in respect to the economic and environmental performance of the system.…”

“…The reduction of emissions, as the general environmental impact, has been addressed using three strategies. The first one is measuring and controlling the direct emissions associated with the fuel consumption. ,,,,,, The second one is to monetize the environmental impact according to local policies or using the ones for developed countries such as carbon tax or bonus. ,, The third strategy is to use methodologies based on parameters of emissions associated with the resources and pollution generated by the implementation of the facility, ,, such as the Life Cycle Assessment (LCA).…”

“…The multiobjective strategies present two approaches. The first one is to present multiple Pareto points for exploring the behavior of the system under different conditions and the effects of the objective functions. ,,,,,,,,,, In this approach, the researcher defines the criteria for solving the problem and presents the set of solutions to the decision makers who choose a specific Pareto point as the best solution that reaches the trade-off between the conflict objective functions according with their specific interest. The second one is to define the interest and priorities of the decision makers or the particular solution area for defining a set of specific solutions for the problem. ,,,,, In this way, it is possible to show how the priorities of the decision makers affect the performance of the system and to avoid computing multiple Pareto solutions which are out of the interest area. ,,, …”