Spatial Energy Efficiency Patterns in New York and Implications for Energy Demand and the Rebound Effect

2021 ◽  
Vol 16 (2) ◽  
pp. 135-161
Author(s):  
Joseph Nyangon ◽  
John Byrne
2012 ◽  
Vol 433-440 ◽  
pp. 4384-4389
Author(s):  
Jin Long Ouyang ◽  
Kazunori Hokao

The ubiquitous discrepancies between predicted and actual outcome of energy efficiency improvement have attracted much attention of the Chinese experts in the field of household energy efficiency. But few people in China realize that it is rebound effect that induces such discrepancies, which at present has been widely accepted in the developed countries. First, in this article the definition and formation process of the rebound effect in the household sector have been described. Then, a high rebound effect of at least more than 30% and more than 50% has been perceived through the combination of the actual situation of China and the experience of other countries. Finally, the influence of the rebound effect in the household sector has been proven negative on the energy demand and energy security of China.


2021 ◽  
Vol 13 (13) ◽  
pp. 7251
Author(s):  
Mushk Bughio ◽  
Muhammad Shoaib Khan ◽  
Waqas Ahmed Mahar ◽  
Thorsten Schuetze

Electric appliances for cooling and lighting are responsible for most of the increase in electricity consumption in Karachi, Pakistan. This study aims to investigate the impact of passive energy efficiency measures (PEEMs) on the potential reduction of indoor temperature and cooling energy demand of an architectural campus building (ACB) in Karachi, Pakistan. PEEMs focus on the building envelope’s design and construction, which is a key factor of influence on a building’s cooling energy demand. The existing architectural campus building was modeled using the building information modeling (BIM) software Autodesk Revit. Data related to the electricity consumption for cooling, building masses, occupancy conditions, utility bills, energy use intensity, as well as space types, were collected and analyzed to develop a virtual ACB model. The utility bill data were used to calibrate the DesignBuilder and EnergyPlus base case models of the existing ACB. The cooling energy demand was compared with different alternative building envelope compositions applied as PEEMs in the renovation of the existing exemplary ACB. Finally, cooling energy demand reduction potentials and the related potential electricity demand savings were determined. The quantification of the cooling energy demand facilitates the definition of the building’s electricity consumption benchmarks for cooling with specific technologies.


Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3852
Author(s):  
Daniel Plörer ◽  
Sascha Hammes ◽  
Martin Hauer ◽  
Vincent van Karsbergen ◽  
Rainer Pfluger

A significant proportion of the total energy consumption in office buildings is attributable to lighting. Enhancements in energy efficiency are currently achieved through strategies to reduce artificial lighting by intelligent daylight utilization. Control strategies in the field of daylighting and artificial lighting are mostly rule-based and focus either on comfort aspects or energy objectives. This paper aims to provide an overview of published scientific literature on enhanced control strategies, in which new control approaches are critically analysed regarding the fulfilment of energy efficiency targets and comfort criteria simultaneously. For this purpose, subject-specific review articles from the period between 2015 and 2020 and their research sources from as far back as 1978 are analysed. Results show clearly that building controls increasingly need to address multiple trades to achieve a maximum improvement in user comfort and energy efficiency. User acceptance can be highlighted as a decisive factor in achieving targeted system efficiencies, which are highly determined by the ability of active user interaction in the automatic control system. The future trend is moving towards decentralized control concepts including appropriate occupancy detection and space zoning. Simulation-based controls and learning systems are identified as appropriate methods that can play a decisive role in reducing building energy demand through integral control concepts.


Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3311
Author(s):  
Víctor Pérez-Andreu ◽  
Carolina Aparicio-Fernández ◽  
José-Luis Vivancos ◽  
Javier Cárcel-Carrasco

The number of buildings renovated following the introduction of European energy-efficiency policy represents a small number of buildings in Spain. So, the main Spanish building stock needs an urgent energy renovation. Using passive strategies is essential, and thermal characterization and predictive tests of the energy-efficiency improvements achieving acceptable levels of comfort for their users are urgently necessary. This study analyzes the energy performance and thermal comfort of the users in a typical Mediterranean dwelling house. A transient simulation has been used to acquire the scope of Spanish standards for its energy rehabilitation, taking into account standard comfort conditions. The work is based on thermal monitoring of the building and a numerical validated model developed in TRNSYS. Energy demands for different models have been calculated considering different passive constructive measures combined with real wind site conditions and the behavior of users related to natural ventilation. This methodology has given us the necessary information to decide the best solution in relation to energy demand and facility of implementation. The thermal comfort for different models is not directly related to energy demand and has allowed checking when and where the measures need to be done.


2012 ◽  
Vol 621 ◽  
pp. 352-355
Author(s):  
Zhong Fu Tan ◽  
Shu Xiang Wang ◽  
Chen Zhang ◽  
Li Qiong Lin ◽  
Yin Hui Zhao

This paper analyses multi influencing factors of energy demand, using energy demand forecast regression model reveals inner relations between each factor and energy demand. Establish simulation model of the relation between GDP, energy intense and energy demand. Under the change in population, urbanization and energy efficiency, this paper gives analysis model of energy demand change.


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