| Project/Area Number |
10650587
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Architectural environment/equipment
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| Research Institution | Mie University |
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Principal Investigator |
SAGARA Kazunobu Mie Univ., Faculty of Engineering, Professor, 工学部, 教授 (30109285)
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| Co-Investigator(Kenkyū-buntansha) |
KITANO Hiroaki Mie Univ., Faculty of Engineering, Research Associate, 工学部, 助手 (80293801)
TERASHINA Takane Mie Univ., Faculty of Engineering, Associate Professor, 工学部, 助教授 (90217422)
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| Project Period (FY) |
1998 – 2000
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| Project Status |
Completed (Fiscal Year 2000)
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| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2000: ¥300,000 (Direct Cost: ¥300,000)
Fiscal Year 1999: ¥1,500,000 (Direct Cost: ¥1,500,000)
Fiscal Year 1998: ¥1,700,000 (Direct Cost: ¥1,700,000)
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| Keywords | Thermal Energy Storage / Fault / Detection / Diagnosis / Air-conditioning / Fuzzy / Expert System / Simulation |
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| Research Abstract |
The objective of this research project is the optimum operation of HVAC system having thermal energy storage without any faults. In order to realize the fault detection and diagnosis, the performance indices of storage operation, the tool for fault detection and diagnosis and the optimum operation with computer simulation were studied. The following is the summary of the obtained results.
1. The indices for the peak shift and peak cut operations were presented to evaluate the operation condition in actual systems. And, the usefulness of these indices were validated by using the measured data in actual systems.
2. An expert system was constructed by combining the fuzzy abduction algorithm for fault detection and diagnosis with knowledge database for reasons and symptoms of faults. And, the effect of the membership function on the obtained diagnosis result was studied.
3. The model parameters of physical models for chiller and air-handling unit in thermal energy storage system were identified from the measured data in actual systems. And, these models were combined with the mixing model of water tank for thermal energy storage, and a computer program allowing to simulate the operation condition was built up as a tool for cost/benefit analysis of fault improvement.
4. The temperature profile in water tank was predicted by using the mixing model of water tank and the measured data. And, by convergence calculation to obtain the minimum error of the predicted temperature profile, the flow rate through the water tank, chillers and air-handling units were estimated as well as the characteristics of chillers and air-handling units in actual systems. This procedure was found to allow to simulate the operation condition accurately without any physical models for chillers and air-handling units.
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