The formulation, characteristics and solution of HVAC system optimized design problems

The formulation, characteristics and solution of HVAC system optimized design problem

Energy aspects of HVAC system configurations — problem definition and test cases

This paper reports on the energy implications of HVAC system configuration by analyzing the energy balance and psychrometrics of typical and innovative systems. Three criteria were shown to be significant: (1) the ability to minimize outside air load, (2) the ability to eliminate simultaneous cooling and heating and use mixing effectively, and (3) the availability of interzonal airflow. Configurations that meet these criteria would be able to deliver the desired indoor air quality with reduced energy consumption. The performance of ten two-zone system configurations, including single-duct, dual-duct, fan-coil-based variations, and other specialized systems in the literature, were analyzed for a number of operational conditions. The results confirmed that fan-coil-based configurations with interzonal airflow paths perform better than other configurations. The conclusion of this study may be used as a guideline for multi-zone system designs

Modeling the dynamic response of conduits

A method for the dynamic modeling of a fluid conduit is developed, based on its discretization into a sequence of well-mixed flow nodes. This enables the time delay produced by the fluid flow to be simply modeled in any time domain simulation. An optimal level of discretization, based on the residence time distribution produced by fully developed turbulent flow, is presented. The model is capable of calculating the response to changes in flow rate, fluid inlet temperature, and species concentration. The thermal response is based on a second-order model for each node, taking account of the thermal capacitance of the fluid and of the conduit inner wall. It is demonstrated that the model predicts a time delay, then a rapid initial response due to flow effects, followed by slower dynamics controlled by the thermal inertia of the walls. An intermodel comparison of output for a prototype duct is made with three published models, and an empirical validation is reported

Evolutionary synthesis of HVAC system configurations : algorithm development (RP-1049)

This paper describes the development of a model-based optimization procedure for the synthesis of novel heating, ventilating, and air-conditioning system configurations. The optimization problem can be considered as having three suboptimization problems: the choice of a component set; the design of the topological connections between the components; and the design of a system operating strategy. In an attempt to limit the computational effort required to obtain a design solution, the approach adopted in this research is to solve all three subproblems simultaneously. The computational effort has been further limited by implementing simplified component models and including the system performance evaluation as part of the optimization problem (there being no need, in this respect, to simulate the system performance). The optimization problem has been solved using a Genetic Algorithm (GA) that has data structures and search operators specifically developed for the solution of HVAC system optimization problems. The performance of the algorithm and various search operators has been examined for a two-zone optimization problem, the objective of the optimization being to find a system design that minimizes system energy use. In particular, the performance of the algorithm in finding feasible system designs has been examined. It was concluded that the search was unreliable when the component set was optimized, but if the component set was fixed as a boundary condition on the search, then the algorithm had an 81% probability of finding a feasible system design. The optimality of the solutions is not examined in this paper but is described in an associated publication (Wright and Zhang 2008). It was concluded that, given a candidate set of system components, the algorithm described here provides an effective tool for exploring the design of novel HVAC systems