Abstract
The present work provides a series of theoretical improvements of a control strategy in order to optimize the time of use of solar air-conditioning by an ejector distributed in multiple solar collectors of vacuum tubes for the residential sector, which will allow us to reduce carbon-dioxide emissions, costs and electrical energy consumption. In a solar ejector cooling system, the instability of the solar source of energy causes an operational conflict between the solar thermal system and ejector cooling cycle. A fuzzy control structure for the supervisory ejector cycle and multi-collector control system is developed: the first control is applied to control the mass flow of the generator and the evaporator for different cooling capacities (3, 3.5, 4, 4.5 and 5 kW) and set a temperature reference according to the operating conditions; the second is applied to keep a constant temperature power source that feeds the low-grade ejector cooling cycle using R134aas refrigerant. For the present work, the temperature of the generator oscillates between 65 °C and 90 °C, a condenser temperature of 30 °C and an evaporator temperature of 10 °C. For the purpose of optimization, there are different levels of performance for time of use: the Mode 0 (economic) gives a performance of 17.55 h, Mode 5 (maximum cooling power) 14.86 h and variable mode (variable mode of capacities) 16.25 h, on average. Simulations are done in MATLAB-Simulink applying fuzzy logic for a mathematical model of the thermal balance. They are compared with two different types of solar radiation: real radiation and disturbed radiation.
Highlights
Mechanical vapor compression consumes exorbitant amounts of high-grade energy [1,2]
This system requires a constant temperature source of energy for the process, which should be independent of weather conditions and shade. This controller follows a temperature reference, which is fixed by another governor control, with the objective of optimizing the use of time, taking into account the operation of the ejector-based refrigeration cycle, which will take advantage of the physical resources and will minimize the costs of operation and maintenance. These systems are difficult to control due to certain factors such as the nonlinear solar thermal characteristic and perturbations, in which the system is subjected to energy and the changes that arise in the dynamics of the process over time and optimal operating conditions of the refrigeration cycle
We develop an intelligent control system based on fuzzy logic, for the synthesis of a nonlinear dynamic system model integrated with the operation of a refrigeration cycle
Summary
Mechanical vapor compression consumes exorbitant amounts of high-grade energy [1,2]. The high consumption of nonrenewable energy from fossil fuels, such as gas and oil, is a part of the remarkable deterioration of the planet, resulting in an increased temperature and higher rates of carbon-dioxide emissions (CO2 ) [3,4,5]. The main idea of the present work is to develop an intelligent control system for better use of multiple solar collectors of vacuum tubes for solar air-conditioning applications by an ejector This system requires a constant temperature source of energy for the process, which should be independent of weather conditions and shade. This controller follows a temperature reference, which is fixed by another governor control, with the objective of optimizing the use of time, taking into account the operation of the ejector-based refrigeration cycle, which will take advantage of the physical resources and will minimize the costs of operation and maintenance These systems are difficult to control due to certain factors such as the nonlinear solar thermal characteristic and perturbations, in which the system is subjected to energy and the changes that arise in the dynamics of the process over time and optimal operating conditions of the refrigeration cycle.
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