Investigation on thermochemical energy network for efficient waste heat recovery [dataset]

The performance of a thermo-chemical fluid (TCF) based energy network is investigated to recover the waste heat for sustainable thermal management. Accordingly, an experimental setup of a TCF energy network is developed to investigate the effects of working fluids under three different waste heating profiles: Gaussian, steady, and regenerative thermal oxidiser (RTO). The profiles are emulated through the graphical user interface-based LabVIEW to mimic the actual heating profiles for analysing the network's performance. An artificial intelligence-based multi-layer perceptron simulator is also developed to map the TCF energy network performance under different thermal scenarios. Results demonstrate that higher air flow rates significantly enhanced the total energy recovery for a large spectrum of solution flow rates. At a solution mass flow rate of 0.03 kg/s, the network achieves the highest effectiveness for potential energy recovery to around 30%. Increasing the heating temperature significantly enhances the moisture recovery performance of the TCF network, while simultaneously diminishing the sensitivity of the network to variations in the liquid-to-gas flow rate (L/G) ratio. At 80°C, the network achieves peak δωₐ values up to 4.3 g/kgda, and the differences between L/G ratios become less pronounced. Across all profiles, the water removal to heat supplied (W/H ratio) decreases as the L/G ratio increases, indicating a consistent decline in performance at higher desiccant flow rates. The Gaussian heating profile offers the highest water removal to heat supplied (W/H ratio) at lower L/G ratios compared to steady and RTO heating profiles, with a peak of around 3.3 kg/kW at an L/G of around 0.2. Further, the simulator demonstrates strong predictive accuracy for the TCF-based energy network under lower L/G ratios and both Gaussian and steady heating profiles, with minimal errors (RMSE as low as 0.09 and relative error of 2.39%). These findings provide essential insights for operating the TCF energy network, emphasising the importance of optimising working fluid operating conditions and maintaining high operational temperatures.