Multivariate hyperplane optimization of integrated photovoltaic/thermal – Assisted desiccant evaporative cooling system

Abstract

The escalating demand for sustainable air conditioning systems in buildings has catalyzed the development of green and efficient alternative air handling systems like the integrated photovoltaic/thermal regenerative desiccant cooling system (PV/T-DCS). This study investigates a multivariate optimization strategy for PV/T-DCS tailored for high-density, hot, and humid urban environments. By integrating a photovoltaic/thermal (PV/T) system with a liquid desiccant-based evaporative cooling system, the objectives of the proposed system configuration and optimization scheme include maximizing cooling capacity, minimizing energy consumption, and reducing emissions. This research executes multivariate hyperplane optimization to balance technical, environmental, energy, and financial goals by employing a novel operational strategy tested under local climatic conditions. Results indicate that the PV/T-DCS system achieves a 58.1 % reduction in energy consumption and a 61 % decrease in carbon dioxide (CO2) emissions compared to conventional systems, providing an effective cooling capacity of 22.9 kW and generating annual savings of 22,766 HKD. This optimization framework may underscore the potential of integrating renewable energy in desiccant air conditioning systems and adapting these technologies to bolster sustainability in air handling systems.