scholarly journals IMPROVING BUILDING ENERGY EFFICIENCY USING DISTRIBUTED ARTIFICIAL INTELLIGENCE

2013 ◽  
Vol 3 (1) ◽  
Author(s):  
Milica Radic ◽  
Dejan Petkovic
Keyword(s):  
Artificial Intelligence ◽  
Energy Efficiency ◽  
Intelligent Agents ◽  
Energy Savings ◽  
Building Energy ◽  
Hvac Systems ◽  
Distributed Artificial Intelligence ◽  
Building Energy Efficiency ◽  
Reduce Energy Consumption ◽  
Temperature Levels

Saving energy in buildings without losing the comfort of the occupants is contradictory request. It has been shown that the use of smart thermostats to HVAC systems reduce energy consumption as much as thirty percent. Depending on the number of different, pre-defined temperature levels, energy savings might be even greater. The method for determining the coefficient of utilization which is based on a normal time temperature distribution is proposed. Key words:Building energy efficiency, TRIZ matrix, Intelligent agents, Coefficient of utilization

scholarly journals Improving the Energy Efficiency of Buildings Based on Fluid Dynamics Models: A Critical Review

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5384
Author(s):  
Xiaoshu Lü ◽  
Tao Lu ◽  
Tong Yang ◽  
Heidi Salonen ◽  
Zhenxue Dai ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Energy Efficiency ◽  
Energy Use ◽  
Energy Savings ◽  
Simulation Models ◽  
Building Energy ◽  
Building Energy Efficiency ◽  
Open Questions ◽  
Building Energy Systems ◽  
Dynamics Models

The built environment is the global sector with the greatest energy use and greenhouse gas emissions. As a result, building energy savings can make a major contribution to tackling the current energy and climate change crises. Fluid dynamics models have long supported the understanding and optimization of building energy systems and have been responsible for many important technological breakthroughs. As Covid-19 is continuing to spread around the world, fluid dynamics models are proving to be more essential than ever for exploring airborne transmission of the coronavirus indoors in order to develop energy-efficient and healthy ventilation actions against Covid-19 risks. The purpose of this paper is to review the most important and influential fluid dynamics models that have contributed to improving building energy efficiency. A detailed, yet understandable description of each model’s background, physical setup, and equations is provided. The main ingredients, theoretical interpretations, assumptions, application ranges, and robustness of the models are discussed. Models are reviewed with comprehensive, although not exhaustive, publications in the literature. The review concludes by outlining open questions and future perspectives of simulation models in building energy research.

scholarly journals A Hybrid Simulation Model to Predict the Cooling Energy Consumption for Residential Housing in Hong Kong

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4850
Author(s):  
Kwok Wai Mui ◽  
Ling Tim Wong ◽  
Manoj Kumar Satheesan ◽  
Anjana Balachandran
Keyword(s):  
Energy Efficiency ◽  
Hong Kong ◽  
Energy Consumption ◽  
Energy Demand ◽  
Building Materials ◽  
Energy Savings ◽  
Hybrid Simulation ◽  
Residential Building ◽  
Building Energy ◽  
Building Energy Efficiency

In Hong Kong, buildings consume 90% of the electricity generated and over 60% of the city’s carbon emissions are attributable to generating power for buildings. In 2018, Hong Kong residential sector consumed 41,965 TJ (26%) of total electricity generated, with private housing accounting for 52% and public housing taking in 26%, making them the two major contributors of greenhouse gas emissions. Furthermore, air conditioning was the major source consuming 38% of the electricity generated for the residential building segment. Strategizing building energy efficiency measures to reduce the cooling energy consumption of the residential building sector can thus have far-reaching benefits. This study proposes a hybrid simulation strategy that integrates artificial intelligence techniques with a building energy simulation tool (EnergyPlus™) to predict the annual cooling energy consumption of residential buildings in Hong Kong. The proposed method predicts long-term thermal energy demand (annual cooling energy consumption) based on short-term (hourly) simulated data. The hybrid simulation model can analyze the impacts of building materials, construction solutions, and indoor–outdoor temperature variations on the cooling energy consumed in apartments. The results indicate that using low thermal conductivity building materials for windows and external walls can reduce the annual cooling energy consumption by 8.19%, and decreasing the window-to-wall ratio from 80% to 40% can give annual cooling energy savings of up to 18%. Moreover, significant net annual cooling energy savings of 13.65% can be achieved by changing the indoor set-point temperature from 24 °C to 26 °C. The proposed model will serve as a reference for building energy efficiency practitioners to identify key relationships between building physical characteristics and operational strategies to minimize cooling energy demand at a minimal time in comparison to traditional energy estimation methods.

Drivers of Investment in Commercial Real Estate Sustainability: 2006–2018

2019 ◽  
Vol 11 (1) ◽  
pp. 130-155
Author(s):  
Michael Brooks ◽  
J.J. McArthur
Keyword(s):  
Energy Efficiency ◽  
Real Estate ◽  
Public Relations ◽  
Building Energy ◽  
Business Case ◽  
Commercial Real Estate ◽  
Building Energy Efficiency ◽  
Number Of Factors ◽  
Near Future ◽  
Asset Managers

We investigate the factors (“drivers”) that motivated investment in energy efficiency in commercial real estate office buildings over the 2006–2011 and 2012–2017 period, and looking forward from 2018 in the context of growing concern over carbon emissions around the world. These insights were collected from large Canadian asset managers through interviews conducted in 2017 and 2018. Key findings were that (1) organizations noted an increasing number of factors driving investment decisions over the three periods; (2) cost drivers (payback period and anticipated financial returns) were the top two drivers in 2006–2017; (3) public relations factors became significantly more important looking forward, with brand (reputational impact) as the top-ranked driver and tenant attraction tied for third place; and (4) mitigation against risks such as resilience and anticipated compliance consistently increased in importance. This study contributes to a comprehensive understanding of past, present, and near-future sustainable real estate investment priorities, changing owner behaviors, and the perceived business case for building energy efficiency investments.

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