Abstract
Within the last decade, domestic energy management has gained a lot of attention. As the complexity of the solar thermal system in terms of the number of system components and energy sources increases, understanding how to manage the cooperation of all the components in order to improve the global efficiency measurements is of crucial importance. Here, the question is how to define an optimal size of the main components in a solar thermal system in order to minimize system cost. Unlike the existing approaches, we propose the use of a novel algorithm called Gravitational Search Algorithm (GSA) to analyze the accurate sizing of energy components, i.e. collector size, tank volume and Auxiliary Power Unit (APU). The objective is to maximize solar fraction, minimize the energy consumption and installation costs subject to constraints. Our proposed GSA model is evaluated and compared with one of the most well-known algorithms, Particle Swarm optimization (PSO) taking into account the fundamental system characteristics. Numerical results show that our proposed methodology significantly improves energy efficiency and reduces operational cost of the solar thermal system in contemporary built environment.
Highlights
With the advent of renewable energy, human beings have tried to overcome several severe limitations, including a limited supply of fossil fuels, high cost and carbon dioxide pollution
"Task 26" was a project initiated by the International Energy Agency (IEA) which conducts investigation on solar combisystems indicates that "if the direct use of solar energy is to make a significant contribution to the heat supply, it is necessary that solar-heating technologies must be developed and widely applied over and beyond the sole field of Domestic Hot Water (DHW) preparation"[2]
In order to technically evaluate the efficiency of Gravitational Search Algorithm (GSA), we will compare our methodology with the Particle Swarm Optimization (PSO) approach presented in [2]
Summary
With the advent of renewable energy, human beings have tried to overcome several severe limitations, including a limited supply of fossil fuels, high cost and carbon dioxide pollution. In order to phase out fossil fuels and reduce the related Co2 emissions, solar energy is introduced as one of the most promising sources which can be used to provide hot water as well as environmental heating energy (a.k.a. solar combisystems [1]). These systems are, derived from the combination of common heating systems with solar collectors. In [2], authors applied PSO to discuss the optimal sizing of the main components of a solar thermal system in order to provide heat for both DHW and SH needs.
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