Optimization of a seasonal storage solar system using Genetic Algorithms

• Author(s): Durão, Bruno ; Joyce, António ; Mendes, J. Farinha
• Date: 2014
• Persistent ID: http://hdl.handle.net/10400.9/2170
• Origin: Repositório do LNEG
• Subject(s): Solar Energy; Thermal Storage; Seasonal Storage; Genetic Algorithms
• Document Type: Article
• Language: English

Description

Seasonal storage solar systems are capable of storing thermal energy, from one season to another (typically a few months). In the present paper solar thermal energy generated during summer time, is stored for use in winter time (typically 120 days). The analyzed system consists of solar thermal collectors and a sensible heat storage device using water as storing media. The area of solar collector and the capacity of the storage tank are the basic sizing parameters, which have to meet the requirements of the load. The present case study considers the utilization of the seasonal storage solar system for heating greenhouses, with a 50 kW heating load. The whole system was modeled using a dynamic modeling tool and the sizing parameters were optimized through a Genetic Algorithm process. This optimization process was compared with other optimization methods by a pattern search, and the results showed the benefits of the Genetic Algorithm process.