J.C. Atuonwu

Improving Adsorption Dryer Energy Efficiency by Simultaneous Optimization and Heat Integration

Conventionally, energy-saving techniques in drying technology are sequential in nature. First, the dryer is optimized without heat recovery and then, based on the obtained process conditions, heat recovery possibilities are explored. This work presents a methodology for energy-efficient adsorption dryer design that considers sensible and latent heat recovery as an integral part of drying system design. A one-step pinch-based optimization problem is formulated to determine the operating conditions for optimal energy performance of such an integrated system subject to product quality. Because the inlet and target stream properties of the heat recovery network are determined by the adsorption drying conditions, they are unknown a priori and thus are determined simultaneously within the overall optimization using the pinch location method. Energy balances are written above and below the various pinch point possibilities and the optimal pinch point is that which minimizes the amount of external heating utility required while satisfying drying and thermodynamic constraints. Results for a single-stage zeolite adsorption drying process with simultaneous heat recovery optimization show a 15% improvement in efficiency compared to a sequentially optimized system. The improvement is traceable to alterations in enthalpy-related variables like temperatures and flow rates. The discrepancy in optimal operating conditions between the sequential and simultaneous cases underscores the need to change system operating conditions when retrofitting for heat recovery because previous optimal conditions become suboptimal when heat recovery is introduced. Also, compared to a conventional dryer (without an adsorption process) operating under similar conditions, energy consumption is reduced by about 55%.

A Mixed Integer Formulation for Energy-efficient Multistage Adsorption Dryer Design

This work presents a mixed integer nonlinear programming (MINLP) formulation for the design of energy-efficient multistage adsorption dryers within constraints on product temperature and moisture content. Apart from optimizing temperatures and flows, the aim is to select the most efficient adsorbent per stage and product to air flow configuration. Superstructure models consisting of commonly used adsorbents such as zeolite, alumina, and silica-gel are developed and optimized for a two-stage, low-temperature, adsorption drying system. Results show that the optimal configuration is a hybrid system with zeolite as the first-stage adsorbent and silica-gel as the second-stage adsorbent in counter-current flow between drying air and product. A specific energy consumption of 2,275 kJ/kg is achieved, which reduces to 1,730 kJ/kg with heat recovery by a heat exchanger. Compared to a conventional two-stage dryer at the same drying temperature, this represents a 59% reduction in energy consumption. The optimal system ensures the exhaust air temperature of the first-stage regenerator is high enough to regenerate the second-stage adsorbent so no utility energy is spent in the second stage. A higher second-stage adsorbent wheel speed favors energy performance as it becomes optimized for energy recovery while the first is optimized for dehumidification. Although this work considers three candidate adsorbents in a two-stage system, the same reasoning can be applied to systems with more stages and adsorbents. The developed superstructure optimization methodology can, by extension, be applied to optimize multistage hybrid drying systems in general for any objective.

Optimizing Energy Efficiency in Low Temperature Drying by Zeolite Adsorption and Process Integration

Drying is an energy intensive process, with low efficiencies, particularly at low drying temperatures required for heat-sensitive products. This work presents an energy efficient method for drying heat-sensitive products based on drying air dehumidification by zeolites and process integration. Two optimization approaches are considered: sequential and simultaneous. In the sequential approach, a zeolite adsorption dryer is optimized for energy efficiency, subject to product temperature and final moisture constraints using the zeolite, drying and regeneration air flowrates as well as the regeneration air inlet temperature as decision variables. Heat is then optimally recovered from the process exhaust streams using pinch analysis. In the simultaneous method, heat recovery is considered an integral part of the drying process and the entire system simultaneously optimized. Since the heat recovery stream properties are now unknown a priori, the pinch point is not unique but determined by optimization. The sequential and simultaneous methods reduce energy consumption by about 45 % and 55 % respectively, compared to a conventional convective dryer at the same drying temperature of 50°C. Copyright

On Dryer Energy Performance and Controllability: Generalized Modeling and Experimental Validation

This work presents an approach to compute dryer energy efficiency using air flowrate step responses and establish a link between drying energy efficiency and process controllability. The approach is based on the temperature drop between the dryer inlet and outlet air under adiabatic conditions and so decouples water evaporation from heat loss and product heating effects on dryer temperature drop. As such, the computation is accurate even for dryers with significant heat losses where the traditional use of actual temperature drop measurements is grossly inaccurate. The approach is tested and verified on two experimental case studies involving significant heat losses: the first, a continuous fluidized-bed dryer (from literature); the second, a conventional and zeolite wheel-assisted batch dryer designed in the current study.

Improving dryer controllability & energy efficiency

This work shows from energy balances and process resiliency analysis, the relationship between dryer controllability and energy performance. It is shown that using the process gain matrix, the dryer temperature drop and hence, energy efficiency can be reliably calculated. Conditions necessary for simultaneous energy efficiency and controllability improvement are established. By pre-conditioning the drying air using a desiccant adsorption system, such conditions are shown to be achievable for the same input choice as a conventional dryer. Also, extra degrees of freedom introduced by the desiccant system promote controllability with the advantage best exploited using full multivariable control. Energy efficiency disturbance resilience is also improved.

Reducing drying energy consumption by adsorbent property optimization in multistage systems

This work presents a mixed integer nonlinear programming method for the design of energy efficient multistage adsorption dryers within product temperature and moisture constraints. The aim is to find the adsorbent type and properties that minimize specific energy consumption. The results show that the adsorbents chosen in each stage have highest sorption capacities for corresponding drying air conditions. Heat requirements are matched so, zero utility energy is spent regenerating the second stage adsorbent. The adsorbent flow speeds are such that the first stage is optimized for dehumidification and the second for heat recovery. Overall, the optimal system reduces specific energy consumption by about 64% compared to a conventional system at the same drying temperature. Also, drying capacity is improved which permits the use of smaller dryers.