4.8 Article

Optimal deployment of thermal energy storage under diverse economic and climate conditions

期刊

APPLIED ENERGY
卷 119, 期 -, 页码 488-496

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2014.01.047

关键词

Thermal energy storage; Chilled water storage; Cooling; Optimization; Distributed energy resources; Net present value

资金

  1. Office of Electricity Delivery and Energy Reliability, Distributed Energy Program of the U.S. Department of Energy [DE-AC02-05CH11231]
  2. Fundacao para a Ciencia e Tecnologia
  3. MIT Portugal Program

向作者/读者索取更多资源

This paper presents an investigation of the economic benefit of thermal energy storage (TES) for cooling, across a range of economic and climate conditions. Chilled water TES systems are simulated for a large office building in four distinct locations, Miami in the U.S.; Lisbon, Portugal; Shanghai, China; and Mumbai, India. Optimal system size and operating schedules are determined using the optimization model DER-CAM, such that total cost, including electricity and amortized capital costs are minimized. The economic impacts of each optimized TES system is then compared to systems sized using a simple heuristic method, which bases system size as fraction (50% and 100%) of total daily on-peak summer cooling loads. Results indicate that TES systems of all sizes can be effective in reducing annual electricity costs (5-15%) and peak electricity consumption (13-33%). The investigation also identifies a number of criteria which drive TES investment, including low capital costs, electricity tariffs with high power demand charges and prolonged cooling seasons. In locations where these drivers clearly exist, the heuristically sized systems capture much of the value of optimally sized systems; between 60% and 100% in terms of net present value. However, in instances where these drivers are less pronounced, the heuristic tends to oversize systems, and optimization becomes crucial to ensure economically beneficial deployment of TES, increasing the net present value of heuristically sized systems by as much as 10 times in some instances. (C) 2014 Elsevier Ltd. All rights reserved.

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