Optimization of multi-generation systems for generation of power, heating, and cooling.

MANASSALDI, JUAN I.; MUSSATI, SERGIO F.; MOROSUK, TATIANA; MUSSATI, MIGUEL C.

Congreso; ASME's International Mechanical Engineering Congress & Exposition (IMECE); 2023

ASME

Meeting worldwide demands for freshwater, electricity and food has been identified as a major challenge for society over the coming decades. Currently, there is an increased interest in geothermal energy utilization for several applications from single power plant to complex combined power-heat plants. There are two main types of geothermal power plants are: a) dry steam power plants which use pressurized steam directly from geothermal reservoirs to drive turbines for electricity generation, and b) flash steam power plants that use hot water from geothermal reservoirs which is pumped to the surface, and then it is separated into water and steam; the steam is used to drive turbines and generate electricity whereas the is cooled and re-injected into the geothermal reservoir to be heated again. In both types of plants, the extraction and re-injection processes are repeated continuously, producing a steady source of renewable energy.At present, geothermal energy-based tri-generation systems can promote energy-saving and decrease carbon emissions. Combined cooling, heating, power (CCHP) systems for seawater desalination are conceived as high-efficiency energy systems. This paper addresses the optimization of a tri-generation system based on geothermal energy, including an organic flash cycle, a vapor compression cooling cycle, a two-phase ejector-based cooling cycle, and a multi stage flash MSF desalination unit for generating electrical power, freshwater, and cooling load. To do this, a multi-objective nonlinear mathematical programming (NLP) optimization is developed and is fully implemented in GAMS – general algebraic modeling system – which is a high level modeling environment widely used in Process System Engineering PSE. CONOPT is used as NLP deterministic solver. As optimization criteria, aspects such as economy, potential of energy-saving, and environmental protection are investigated. As result, the optimal installed capacity and operating strategies are obtained. Finally, a sensitivity analysis of the key model parameters such as seawater conditions – salinity and temperature – and electricity/freshwater demands on the exergetic, economic, and environmental criteria is discussed.