Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/76011
Title: Model-based optimal design of active cool thermal energy storage for maximal life-cycle cost saving from demand management in commercial buildings
Authors: Cui, BR 
Gao, DC 
Xiao, F 
Wang, SW 
Keywords: Active cool thermal energy storage
Building demand management
Demand response
Peak load management
Genetic algorithm
Issue Date: 2017
Publisher: Pergamon Press
Source: Applied energy, 2017, v. 201, p. 382-396 How to cite?
Journal: Applied energy 
Abstract: This paper provides a method to evaluate the cost-saving potential of active cool thermal energy storage (CTES) integrated with HVAC system for demand management in commercial building. Active storage is capable of shifting peak demand for peak load management (PLM) as well as providing longer duration and larger capacity for demand response (DR). In this research, a model-based optimal design method using genetic algorithm is developed to optimize the capacity of active CTES for maximizing the life-cycle cost saving including capital cost associated with storage capacity as well as incentives from both fast DR and PLM. In the method, the active CTES operates under a fast DR control strategy during DR events and under the storage-priority operation mode to shift peak demand during normal days. The optimal storage capacities, maximum annual net cost saving and corresponding power reduction setpoints during DR events are obtained by using the proposed optimal design method. This research provides guidance in comprehensive evaluation of the cost-saving potential of active CTES integrated with HVAC system for building demand management including both fast DR and PLM.
URI: http://hdl.handle.net/10397/76011
ISSN: 0306-2619
EISSN: 1872-9118
DOI: 10.1016/j.apenergy.2016.12.035
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