Model-based optimal design of active cool thermal energy storage for maximal life-cycle cost saving from demand management in commercial buildings

Journal Article · Fri Dec 23 00:00:00 EST 2016 · Applied Energy

DOI:https://doi.org/10.1016/j.apenergy.2016.12.035· OSTI ID:1366386

Cui, Borui ^[1]; Gao, Dian-ce ^[2]; Xiao, Fu ^[2]; Wang, Shengwei ^[2]

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1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hong Kong Polytechnic Univ. (Hong Kong). Dept. of Building Services Engineering
2. Hong Kong Polytechnic Univ. (Hong Kong). Dept. of Building Services Engineering

This article provides a method in comprehensive evaluation of cost-saving potential of active cool thermal energy storage (CTES) integrated with HVAC system for demand management in non-residential building. The active storage is beneficial by shifting peak demand for peak load management (PLM) as well as providing longer duration and larger capacity of demand response (DR). In this research, a model-based optimal design method using genetic algorithm is developed to optimize the capacity of active CTES aiming for maximizing the life-cycle cost saving concerning 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 while 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 set-points during DR event are obtained by using the proposed optimal design method. Lastly, this research provides guidance in comprehensive evaluation of cost-saving potential of CTES integrated with HVAC system for building demand management including both fast DR and PLM.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Building Technologies Research and Integration Center (BTRIC)
• Sponsoring Organization: USDOE Laboratory Directed Research and Development (LDRD) Program
• Grant/Contract Number: AC05-00OR22725; 152181/14E
• OSTI ID: 1366386
• Journal Information: Applied Energy, Vol. 201, Issue C; ISSN 0306-2619
• Publisher: Elsevier
• Country of Publication: United States
• Language: English

Related Subjects

25 ENERGY STORAGE
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
Active cool thermal energy storage
Building demand management
Demand response
Peak load management
Genetic algorithm