In this paper, a model-based optimization
strategy for a liquid
desiccant regenerator operating with lithium chloride solution is
presented. By analyzing the characteristics of the components, such
as electric heater, pump, and fan, energy predictive models for the
components in the regenerator are developed. To minimize the energy
usage while maintaining the regeneration rate within an accepted level,
one multiobjective optimization problem is formulated with two objectives,
the constraints of decision variables, components interactions, and
the outdoor conditions. A multiobjective optimization strategy based
on decreasing inertia weight particle swarm optimization (DIWPSO)
is proposed to obtain the optimal nondominated solutions of the optimization
problem, and a decision making strategy is introduced to select the
final solution, desiccant solution flow rate, desiccant solution temperature,
and the regenerating air flow rate, to minimize the energy usage in
the regenerator. Experimental studies are carried out on an existing
system to compare the energy consumption and regeneration rate between
the proposed optimization strategy and conventional strategy to evaluate
energy saving performance of the proposed strategy. Experimental results
demonstrate that an average of 8.55% energy can be saved by implementing
the proposed optimization strategy in liquid desiccant regenerator.