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In recent years, CO2 heat pump water heating systems have been developed, and their performances have been enhanced while their functions have been expanded. In a multi-functional system, used for both hot water supply and bath heating, hot water retrieved from the top of a storage tank is returned to its bottom or side after heat exchange for bath heating, which destroys the stratified temperature distribution in the storage tank and degrades the system performance. In this paper, the performance of a multi-functional CO2 heat pump water heating system has been evaluated by numerical simulation. A system model was created by combining component models for a CO2 heat pump, mixing valves, a storage tank, a heat exchanger, and a bathtub. Partly, perfect mixing by hot water return was assumed in the component model for the storage tank, and its validity was verified through experiments. A performance analysis has been conducted under daily repeated hot water and bath heating demands, and the system performance was evaluated at a periodically steady state. As a result, the system efficiency and the volume of unused hot water in the multi-functional system decreased by 4.9% and 16.3%, respectively, as compared to those in the uni-functional system, when hot water returned to the bottom of the storage tank. When the position for hot water return is heightened, the system efficiency becomes higher than that in the uni-functional system, while the volume of unused hot water decreases furthermore.

application/pdf, Article, Energy. 87, p.435-447

application/pdf, Article, Energy Conversion and Management. 92, p.92-104

application/pdf, Article, Energy Conversion and Management. 2014, 84, p.196-208

This paper describes about a decision model for solar energy utilization and an investigation of optimal configuration of solar energy system considering electricity transportation between interprofessional consumers. Solar energy is effective energy source for CO2 reduction. Available collectable area for solar energy is limited to consumer's condition. A photovoltaic can supply electricity which is flexible. However its efficiency is low compared to solar heat collector. A solar heat collector has high efficiency. But heat demand varies with consumer type. We investigate optimal ratio of photovoltaic and solar heat collector in several condition. The result shows that solar heat collector is effective energy supply system for consumers which require high hot water demand in daytime. On the other hand, electrical heat pump for hot water supply varies optimal configuration of solar energy system due to the shift of energy source from gas to electricity. To introduce electrical heat pump for hot water supply increases the ratio of photovoltaic due to the increase in electricity demand. However, there is no consumer without solar heat collector. Therefore, solar heat collector does not compare with electrification of consumer.

In designing energy supply systems, designers should consider that energy demands and costs as parameters have some uncertainties, evaluate the robustness in system performances against the uncertainties, and design the systems rationally to heighten the robustness. A robust optimal design method of energy supply systems under only uncertain energy demands was revised so that it can be applied to systems with complex configurations and large numbers of periods for variations in energy demands. In addition, a method of comparing performances of two energy supply systems under only uncertain energy demands was proposed by utilizing a part of the revised robust optimal design method. In this paper, the revised robust optimal design method as well as the proposed performance comparison method are extended so that they can be applied to the robust optimal design and the performance comparison of energy supply systems under not only uncertain energy demands but also uncertain energy costs. Through a case study on a gas turbine cogeneration system for district energy supply, the validity and effectiveness of the extended optimal design method and features of the robust optimal design are clarified. In addition, the gas turbine cogeneration system is compared with a conventional energy supply system using the extended performance comparison method.

Typical adsorptive desiccant cooling process mainly consisting of a rotary dehumidifier and a sensible heat exchanger can be driven with low-temperature heat energy like solar energy or waste heat, and it has been expected to be alternative air conditioning equipment considering various energy/environmental problems such as global warming. However, the fact that the cooling performance is decreased significantly as ambient humidity increases was also found. This is mainly due to a simultaneous increase of humidity and temperature in the process outlet air of dehumidifier. For the use of the cooling process in high humid condition, two process configurations were proposed and investigated by means of simple calculation. One of the proposed configurations, the 4-wheel cycle with double stage dehumidification, indicated a sufficient cooling performance for the use in factories or laboratories even though the ambient humidity was nearly 20 g/kg. Furthermore, the process performance was improved more with water spray evaporative cooling at the inlet of a regeneration air stream in the pre-dehumidification section. This means that lower humidity and lower temperature of air supplied to the process inlet of the dehumidifier is strongly required to give the cooling process a sufficient performance for actual use. Meanwhile, it was found that lower temperature heat around 50–60°C could drive the 4-wheel desiccant cycle in a moderate ambient humidity. The other, a 3-wheel cycle equipped with a total heat exchanger, gave us a reasonable improvement in the cooling effect and COP with less additional investment than that for the 4-wheel cycle.

Some optimal operation methods based on the mixed-integer linear programming have been proposed to operate energy supply plants properly from the viewpoints of economics, energy saving, and CO2 emission reduction. However, most of the methods are effective only under certain energy demands. In operating an energy supply plant actually, it is necessary to determine the operational strategy properly based on predicted energy demands. In this case, realized energy demands may differ from the predicted ones. Therefore, it is necessary to determine the operational strategy so that it is robust against the uncertainty in energy demands. In this paper, an optimization method based on the mixed-integer linear programming is proposed to conduct the robust optimal operation of energy supply plants under uncertain energy demands. The uncertainty in energy demands is expressed by their intervals. The operational strategy is determined to minimize the maximum regret in the operational cost under the uncertainty. In addition, a hierarchical relationships among operation modes and on/off states of equipment, energy demands, and energy flow rates of equipment are taken into account. First, a general formulation of a robust optimal operation problem is presented, which is followed by a general solution procedure. Then, in a numerical study, the proposed method is applied to a gas turbine cogeneration plant for district energy supply. Through the study, some features of the robust optimal operation are clarified, and the validity and effectiveness of the proposed method are ascertained.Copyright © 2014 by ASME

Optimization approaches based on the mixed-integer linear programming (MILP) have been utilized to design energy supply systems. In this paper, an MILP method utilizing the hierarchical relationship between design and operation is extended to search not only the optimal solution but also suboptimal ones which follow the optimal one without any omissions, what are called K-best solutions, efficiently in a multiobjective optimal design problem. At the upper level, the values of design variables for the K-best solutions are searched by the branch and bound method. At the lower level, the values of operation variables are optimized independently at each period by the branch and bound method under the values of design variables given tentatively. Incumbents for the K-best solutions and an upper bound for all the values of the objective function for the K-best solutions are renewed if necessary between both the levels. This method is implemented into a commercial MILP solver. A practical case study on the multiobjective optimal design of a cogeneration system is conducted, and the validity and effectiveness of the method are clarified.