Economic and Experimental Assessment of KCOOH Hybrid Liquid Desiccant-Vapor Compression System

Abstract

A liquid desiccant dehumidification cooling system is a promising, energy-saving, high-efficiency, environmentally friendly technology that maintains thermal comfort effectively indoors by utilizing renewable energy sources or waste heat to enhance system efficiency. In this research, a small-scale (6 kW cooling capacity) hybrid liquid desiccant air-conditioning system (HLDAC) is proposed to evaluate the dehumidification performance of a non-corrosive potassium formate (KCOOH) solution. For this, four input parameters, namely, inlet air flow rate, inlet desiccant temperature, inlet desiccant concentration, and inlet specific air humidity, were selected. Moreover, the different combinations of experiments were designed by employing response surface methodology (RSM) to evaluate the dehumidification performance parameters, namely, dehumidifier latent heat load, coefficient of performance of hybrid system, and moisture removal rate (MRR). Further, a comparative performance analysis between the hybrid system and a standalone vapor compression system (VCS) unit was carried out. The result showed a remarkable increase in coefficient of performance, which was observed at about 28.48% over the standalone VCS unit. Furthermore, the economic assessment of the proposed hybrid system is presented in this paper. Finally, from the economic analysis, it was concluded that the hybrid system had a payback time of 2.65 years compared to the VCS unit.

Analysis of Liquid Air Energy Storage System with Organic Rankine Cycle and Heat Regeneration System

“…After the expanders, the temperature of the heating water is lower. In general, the data obtained are consistent with the data presented in [41].…”

Microgrid Robust Planning Model and Its Modification Strategy Based on Improved Grey Relational Theory

“…∆P max wt,t , ∆P max pv,t and ∆P max load,t are the maximum fluctuation values of WT, PV and demand-side load, respectively. To ensure the stable operation of the microgrid system, the fluctuation range of the above uncertainties is constrained, as shown in Equation (4).…”

“…The distributed renewable energy connected microgrid, which is represented by wind power and photovoltaic (PV), has been developed rapidly [1,2]. The microgrid planning model has become the research focus, combined with the joint planning for robustness of the wind-PV-energy storage system (ESS), because the optimal planning scheme is very important for the economic and sustainability of the power grid [3,4]. Most researchers focus on the planning model's setting and solving methods, such as the speed of the solving method and the applicability of the optimal scheme, but the adjustment effect of planning elements on the optimal solution is ignored.…”