| 1. |
- Behzadi, Amirmohammad, et al.
(författare)
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Smart design and control of thermal energy storage in low-temperature heating and high-temperature cooling systems : A comprehensive review
- 2022
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Ingår i: Renewable & sustainable energy reviews. - : Elsevier BV. - 1364-0321 .- 1879-0690. ; 166, s. 112625-
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Forskningsöversikt (refereegranskat)abstract
- Thermal energy storage (TES) is recognized as a well-established technology added to the smart energy systems to support the immediate increase in energy demand, flatten the rapid supply-side changes, and reduce energy costs through an efficient and sustainable integration. On the utilization side, low-temperature heating (LTH) and high-temperature cooling (HTC) systems have grown popular because of their excellent performance in terms of energy efficiency, cost-effectiveness, and ease of integration with renewable resources. This article presents the current state-of-the-art regarding the smart design of TES integrated with LTH and HTC systems. TES is first explained in basic concepts, classification, and design possibilities. Secondly, the literature on well-known existing control approaches, strategies, and optimization methods applied to thermal energy storage is reviewed. Thirdly, the specifications, types, benefits, and drawbacks of the LTH and HTC systems from the viewpoints of supply and demand sides are discussed. Fourthly, the smart design of TES integrated with the LTH and HTC systems based on the control approach/strategy, optimization method, building type, and energy supplier is investigated to find the newest technology, ideas, and features and detect the existing gaps. The present article will provide a realistically feasible solution for having a smart storage configuration with the maximum possible energy efficiency, reliability, and cost-effectiveness for the building owners and the energy suppliers.
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| 2. |
- Földváry Ličina, Veronika, et al.
(författare)
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Development of the ASHRAE Global Thermal Comfort Database II
- 2018
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Ingår i: Building and Environment. - : Elsevier BV. - 0360-1323. ; 142, s. 502-512
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Tidskriftsartikel (refereegranskat)abstract
- Recognizing the value of open-source research databases in advancing the art and science of HVAC, in 2014 the ASHRAE Global Thermal Comfort Database II project was launched under the leadership of University of California at Berkeley's Center for the Built Environment and The University of Sydney's Indoor Environmental Quality (IEQ) Laboratory. The exercise began with a systematic collection and harmonization of raw data from the last two decades of thermal comfort field studies around the world. The ASHRAE Global Thermal Comfort Database II (Comfort Database), now an online, open-source database, includes approximately 81,846 complete sets of objective indoor climatic observations with accompanying “right-here-right-now” subjective evaluations by the building occupants who were exposed to them. The database is intended to support diverse inquiries about thermal comfort in field settings. A simple web-based interface to the database enables filtering on multiple criteria, including building typology, occupancy type, subjects' demographic variables, subjective thermal comfort states, indoor thermal environmental criteria, calculated comfort indices, environmental control criteria and outdoor meteorological information. Furthermore, a web-based interactive thermal comfort visualization tool has been developed that allows end-users to quickly and interactively explore the data.
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| 3. |
- Nasiri, Fuzhan, et al.
(författare)
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Data Analytics and Information Technologies for Smart Energy Storage Systems : A State-of-the-Art Review
- 2022
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Ingår i: Sustainable cities and society. - : Elsevier BV. - 2210-6707. ; 84, s. 104004-
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Forskningsöversikt (refereegranskat)abstract
- This article provides a state-of-the-art review on emerging applications of smart tools such as data analytics and smart technologies such as internet-of-things in case of design, management and control of energy storage systems. In particular, we have established a classification of the types and targets of various predictive analytics for estimation of load, energy prices, renewable energy inputs, state of the charge, fault diagnosis, etc. In addition, the applications of information technologies, and in particular, use of cloud, internet-of-things, building management systems and building information modeling and their contributions to management of energy storage systems will be reviewed in details. The paper concludes by highlighting the emerging issues in smart energy storage systems and providing directions for future research.
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