388436 Multi-Objective Optimization of CHP Systems for Housing Complexes

Monday, November 17, 2014: 5:35 PM
M304 (Marriott Marquis Atlanta)
Luis Fabian Fuentes-Cortes1, José María Ponce-Ortega2, Medardo Serna-González2 and Carlos Rubio-Maya3, (1)Chemical Engineering, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Mexico, (2)Chemical Engineering Department, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacan, Mexico, (3)Mechanical Engineering, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Mexico

Energy demand in the residential sector of Mexico is defined by the requirements of electricity and hot water for domestic use (HWS). These requirements may be satisfied by a cogeneration system (CHP). However, the implementation of such systems presents a particular problem.

On one hand, due to the nature of the domestic user, the energy demand is not uniform throughout the day and the season of the year, presenting differences between electricity demand and hot water demand. On the other hand, the costs of investment in such systems can become elevated to the domestic consumer. In addition, although the CHP systems have good efficiency compared to conventional power generation schemes, due to the use of fossil fuels continue to generate greenhouse gases emissions (GHG).

The above mentioned problems can be solved by using optimization models in the design stage. In this paper, the design of a CHP system, which consists of a diesel internal combustion and thermal storage tank, is presented. The thermal storage tank is used to smooth the gaps between electricity demand and hot water demand. The system interacts with the network of the electric company through a scheme in which the surplus power is sold or bought to cover missing energy demands.

The optimization model uses as objective functions to maximize the net present value (NPV) of the CHP system and minimize the generation of GHG emissions. As independent variables the schedule scheme operating internal combustion engine and the volume of thermal storage tank used. The partial load of the internal combustion engine and the temperature inside the thermal storage tank is restricted. The model has been solved by NLP models and genetic algorithms. Additionally, in order to make a comparison over conventional generation, the rate of primary energy savings (IPES) and avoided GHG emissions are calculated. Furthermore, the relationship between the temperature of hot water supply, the operation scheme of the primary drive and the volume of the thermal storage tank are shown.

A case study from the state of Michoacan in Mexico was considered to prove the proposed approach, this case study consists of a residential l complex of 1,110 houses; and the results show that there economically and environmentally attractive solutions with the implementation of the proposed approach.

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See more of this Session: Achieving Sustainable Buildings through Chemical Engineering
See more of this Group/Topical: Environmental Division