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This paper proposes a hybrid algorithm to solve the optimal energy dispatch of an ice storage air-conditioning system. Based on a real air-conditioning system, the data, including the return temperature of chilled water, the supply temperature of chilled water, the return temperature of ice storage water, and the supply temperature of ice storage water, are measured. The least-squares regression (LSR) is used to obtain the input-output (I/O) curve for the cooling load and power consumption of chillers and ice storage tank. The objective is to minimize overall cost in a daily schedule while satisfying all constraints, including cooling loading under the time-of-use (TOU) rate. Based on the Radial Basis Function Network (RBFN) and Ant Colony Optimization, an Ant-Based Radial Basis Function Network (ARBFN) is constructed in the searching process. Simulation results indicate that reasonable solutions provide a practical and flexible framework allowing the economic dispatch of ice storage air-conditioning systems, and offering greater energy efficiency in dispatching chillers. [ABSTRACT FROM AUTHOR]

Abstract: Parallel flow condenser (PFC), which is widely used in automobile air conditioning (AAC) industries, was modeled and optimized in this paper. A sample of designed and manufactured condenser of this type was modeled and tested. In the proposed physical model the condenser is divided into three regions of superheat, saturated (two-phase) and subcooled. The modeling results validated by comparison with the experimental data. In optimization section, the condenser heat transfer rate was maximized while its pressure drop was minimized applying genetic algorithm multi-objective optimization technique. A set of Pareto optimal solutions as well as the final optimal design point were presented for our case study. The optimum design parameters resulted in heat transfer rate increase for 7.1% and decrease in pressure drop for 96% in comparison with the corresponding manufactured operating parameters. [Copyright &y& Elsevier]

This paper describes the development and evaluation of a simple algorithm for night ventilation precooling that can be integrated at low cost within a controller for packaged air conditioners that employ economizers, such as rooftop units. In addition to reducing operating costs, the algorithm ensures that indoor comfort is maintained. The basic night ventilation precooling algorithm was developed based upon a simple optimization and heuristics derived from simulation results. The cost savings potential of the algorithm was evaluated using simulations for a range of buildings and climates throughout California. The buildings were representative of small commercial buildings that employ packaged air-conditioning equipment with integrated economizers. The annual savings in compressor energy for night ventilation ranged from about 0 to 53% depending on the location and building type. The savings in total air-conditioning electrical energy usage are much smaller than the compressor savings due to an increase in fan energy. The annual electrical energy savings varied between about 0 and 8%. The electrical demand cost savings associated with night ventilation varied between about 0 and 28%, whereas the total annual electrical cost savings ranged from about 0 to 17%. The greatest percent savings occurred in cooler coastal climates having smaller total loads but significant opportunities for night ventilation precooling. [ABSTRACT FROM AUTHOR]