Exergy analysis and particle swarm optimization of clean energy router based on a solar‐thermal‐assisted advanced adiabatic compressed air energy storage system

Abstract

Abstract The clean Energy router based on advanced adiabatic compressed air energy storage (AA‐CAES) has the characteristics of large capacity, high efficiency and zero carbon emission which are an effective mitigation scheme for the integration of renewables and peak‐shaving and a new clean energy technology for storing energy in the world. A novel solar‐thermal‐assisted AA‐CAES (ST‐AA‐CAES) is proposed in this paper, integrating variable thermal energy storage to improve the system electric to electric (E2E) and round‐trip efficiency (RTE). The efficiency and exergy evaluation of ST‐AA‐CAES are carried out to determine the performance of ST‐AA ‐CAES. The results illustrate that E2E, RTE, and exergy efficiency can reach 56.4%, 95.5%, and 55.9%, respectively. Meanwhile, the details of exergy efficiency and destruction of each subsystem are demonstrated. Particle swarm optimization algorithm is applied to analyse the economy of optimally integrated energy systems which has the advantages of high accuracy, convenient implementation and fast convergence. The system can be applied in abundant solar energy resources area with high efficiency and multi‐energy supply capability.

Keywords

• hybrid renewable energy systems
• optimisation
• thermal energy storage