Sustainability evaluation framework for building cooling systems: a comparative study of snow storage and conventional chiller systems

Kumar, V. R. Prasath; Hewage, Kasun; Haider, Husnain; Sadiq, Rehan

doi:10.1007/s10098-016-1198-8

Cited by 16 publications

(3 citation statements)

References 31 publications

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“…Different types of energy storage technologies have their own advantages and are suitable for different applications. Electrical energy storage technology, which can reduce the daily peak demand and the electrical equipment capacity of the enterprises, is beneficial to the full use of the existing equipment and the reduction of the investment cost [33]. Coordinating with the electricity price policy, it can also reduce the enterprises' operating cost.…”

Section: The Influence On the Utilization Rate Of Distribution Networmentioning

confidence: 99%

A review on the influence of intelligent power consumption technologies on the utilization rate of distribution network equipment

He¹,

Chen²,

Yang

et al. 2018

Prot Control Mod Power Syst

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The economy of distribution networks largely depends on the utilization rate of distribution network equipment. Most of the emerging intelligent power consumption technologies have a positive effect on equipment utilization and their use can save investment of distribution networks. In this paper, the influence of intelligent power consumption technologies on the utilization rate of distribution network equipment is reviewed. The evaluation methods and indexes are assessed first and then intelligent power consumption equipment with energy storage function, vehicle-to-grid (V2G) technology and time-of-use (TOU) tariff are reviewed respectively. It is concluded that these intelligent power consumption technologies and measures have great potential to improve utilization rate of distribution network equipment because of their effective improvement to power load. Meanwhile, recommendations on how to utilize these intelligent power consumption technologies to improve utilization rate of distribution network equipment are proposed.

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Section: The Influence On the Utilization Rate Of Distribution Networmentioning

confidence: 99%

A review on the influence of intelligent power consumption technologies on the utilization rate of distribution network equipment

He¹,

Chen²,

Yang

et al. 2018

Prot Control Mod Power Syst

View full text Add to dashboard Cite

show abstract

“…Facilities for power storage and ice thermal storage that are usually used at night to prevent electricity from reaching a peak in the daytime are widely applied in practice [9]. However, it has to be very careful to forecast the power consumption in the daytime, since either overestimation or underestimation will result in electricity waste, which would violate the intention.…”

Section: Introductionmentioning

confidence: 99%

A New Perspective on Improving Hospital Energy Administration Based on Recurrence Interval Analysis

Wang

Wei

2018

Energies

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Based on 15-min high-frequency power load data from a Chinese hospital, by adopting recurrence interval analysis, an attempt is made to provide a new perspective for improving hospital energy administration in electrical efficiency and safety. Initially, the definition of extreme fluctuation of the power load, as well as the recurrence interval, is given. Next, the stretched exponential distribution function is provided, which fits quite well with the probability density distribution of recurrence intervals. Then, tests on recurrence intervals, including scaling behavior and short-term and long-term memory effect are conducted. At last, a risk estimation method of VaR is proposed for hospital energy administrator to forecast risk probability. Results clearly indicate that the recurrence interval analysis (RIA) method works well on forecasting extreme power load fluctuation in hospital. However, there is no evidence to support the existence of the long-term memory effect of recurrence intervals, which means that hospital energy management plans have to be continuously fixed and updated with time. Some relevant applicant suggestions are provided for the energy administrator at the end of this paper.

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“…Applications which included both LCC and LCA for the definition of criteria to be used in MCDA are still rare (Piombo et al 2016). Decision analysis methods used in the above-mentioned studies involved different variants of AHP (Motuziene et al 2016;Khoshnava et al 2016), PROMETHEE II (Kumar et al 2017), Weighted Sum, TOPSIS (Čuláková et al 2013), VIKOR, and COPRAS (Ginevicius et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Multiple Criteria Assessment of Insulating Materials with a Group Decision Framework Incorporating Outranking Preference Model and Characteristic Class Profiles

et al. 2017

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We present a group decision making framework for evaluating sustainability of the insulating materials. We tested thirteen materials on a model that was applied to retrofit a traditional rural building through roof's insulation. To evaluate the materials from the socio-economic and environmental viewpoints, we combined life cycle costing and assessment with an adaptive comfort evaluation. In this way, the performances of each coating material were measured in terms of an incurred reduction of costs and consumption of resources, maintenance of the cultural and historic significance of buildings, and a guaranteed indoor thermal comfort. The comprehensive assessment of the materials involved their assignment to one of the three preferenceordered sustainability classes. For this purpose, we used a multiple criteria decision analysis approach that accounted for preferences of a few tens of rural buildings' owners. The proposed methodological framework incorporated an outranking-based preference model to compare the insulating materials with the characteristic class profiles while using the weights derived from the revised Simos procedure. The initial sorting recommendation for each material was validated against the outcomes of robustness analysis that combined the preferences of individual stakeholders either at the output or at the input level. The analysis revealed that the most favorable materials in terms of their overall sustainability were glass wool, hemp fibres, kenaf fibres, polystyrene foam, polyurethane, and rock wool. Electronic supplementary materialThe online version of this article (https://doi.org/10.1007/s10726-017-9549-3) contains supplementary material, which is available to authorized users. B Miłosz Kadziński

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Sustainability evaluation framework for building cooling systems: a comparative study of snow storage and conventional chiller systems

Cited by 16 publications

References 31 publications

A review on the influence of intelligent power consumption technologies on the utilization rate of distribution network equipment

A review on the influence of intelligent power consumption technologies on the utilization rate of distribution network equipment

A New Perspective on Improving Hospital Energy Administration Based on Recurrence Interval Analysis

Multiple Criteria Assessment of Insulating Materials with a Group Decision Framework Incorporating Outranking Preference Model and Characteristic Class Profiles

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