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Volume 15: Sustainable Products and Processes

DOI: 10.1115/imece2007-41885

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Technical and Economical Analysis of a Micro-CHP Facility Based on Dynamic Simulation: A Case Study

Proceedings article published in 2007 by Heejin Cho ORCID, Rogelio Luck, Louay M. Chamra
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Combined Heating and Power (CHP) generation systems have been widely recognized as a key alternative for heat and electricity generation due to their outstanding energy efficiency, reduced emissions, and relative independence from centralized power grids. Similar to CHP systems, micro-CHP (micro-Cooling, Heating, and Power) systems consist of power cogeneration systems and thermally-activated components such as absorption chillers, water tanks, boilers and air handling units. There have been many studies in regard to steady-state models following load profiles in order to demonstrate the economic advantage of CHP systems. However, there has not been much work using dynamic simulation of CHP systems, which include the transient response of the building along with the rest of the CHP components. This paper presents both technical and economical results from the dynamic simulation of the micro-CHP system used to model the test facility at Mississippi State University (MSU). The results are compared to a dynamic model using a conventional heating and cooling system. TRNSYS, a dynamic simulation program, is used to simulate the time response of the micro-CHP system based on the transient heating, cooling, and electric power demand of a test facility. The performance and costs of a conventional heating and cooling system are assessed using TRNSYS and the results are then compared against the simulated performance of the micro-CHP system. Details of the simulation model include geometric and material information (e.g., size and type of walls and windows), internal gains (following the equipment and occupancy schedules), local weather information (e.g., ambient temperature, relative humidity, and solar radiation), and estimated infiltration of the test facility.