期刊
COMPUTERS & CHEMICAL ENGINEERING
卷 71, 期 -, 页码 648-662出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2013.10.016
关键词
Daily thermal storage; District energy systems; Mixed integer linear programming; Evolutionary algorithm; Multi-objective optimization; CO2 mitigation
资金
- Veolia Environnement Recherche et Innovation (VERO)
District heating is an efficient way of providing heat to urban areas. The use of storage tanks integrated with district heating network would permit to increase the annual utilization of base load equipment, avoiding over estimation of the size of backup equipment, and balancing the energy demand fluctuation during day and night. In the present work a multi-objective optimization model for sizing and operation optimization of district heating systems with heat storage tanks is presented. The model includes process design and energy integration techniques for optimizing the temperature intervals, the volume and the operation strategy of thermal storage tanks. The proposed model is demonstrated by means of two test cases. Results show that the efficiency, environmental impacts and total costs of an urban system can be improved after integrating the thermal storage by 4.7%, 5% and 2% respectively. (C) 2013 Elsevier Ltd. All rights reserved.
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