95/05153 A case study of energy savings by using the water-side economiser system in large office building in Montreal

This article outlines a socio-political theory appropriate for the study of the ecological repercussions of contemporary media technologies. More specifically, this approach provides a means of assessing the material impacts of media technologies and the representations of capitalist ecological crises. This approach builds on the work of ecological economists, ecosocialist scholars, and Marx’s writings on the conditions of production to argue that capitalism necessarily results in ecological destabilization. Taking Apple’s 2016 Environmental Responsibility Report as a case study, the article uses the theory to analyze Apple’s responses to ecological crises. The article asserts that Apple’s reactions are emblematic of the capitalist compulsion for increasing rates of productivity. However, unless the matter/energy savings achieved through higher rates of productivity surpass the overall increase in the flow of matter/energy in production, ecological crises will continue. Ultimately, capital accumulation ensures continued ecological destabilization.

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Detailed Cross Comparison of Building Energy Simulation Tools Results using a reference office building as a case study

Energy and Buildings ◽

10.1016/j.enbuild.2021.111260 ◽

2021 ◽

pp. 111260

Author(s):

Mara Magni ◽

Fabian Ochs ◽

Samuel de Vries ◽

Alessandro Maccarini ◽

Ferdinand Sigg

Keyword(s):

Building Energy ◽

Energy Simulation ◽

Office Building ◽

Building Energy Simulation ◽

Simulation Tools

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Analysis of biophilic design in communal space of an office building. Case study: Pertubuhan Arkitek Malaysia (PAM) centre

10.1063/5.0052824 ◽

2021 ◽

Author(s):

Ismi Ibrahim ◽

Rizal Khairuddin ◽

Azli Abdullah ◽

Izzati M Amin ◽

Julaihi Wahid

Keyword(s):

Office Building ◽

Biophilic Design ◽

Communal Space

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A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand

Energies ◽

10.3390/en14010156 ◽

2020 ◽

Vol 14 (1) ◽

pp. 156

Author(s):

Paige Wenbin Tien ◽

Shuangyu Wei ◽

John Calautit

Keyword(s):

Deep Learning ◽

Real Time ◽

Energy Demand ◽

Energy Savings ◽

Internal Heat ◽

Electrical Equipment ◽

Building Energy ◽

Hvac Systems ◽

Equipment Usage

Because of extensive variations in occupancy patterns around office space environments and their use of electrical equipment, accurate occupants’ behaviour detection is valuable for reducing the building energy demand and carbon emissions. Using the collected occupancy information, building energy management system can automatically adjust the operation of heating, ventilation and air-conditioning (HVAC) systems to meet the actual demands in different conditioned spaces in real-time. Existing and commonly used ‘fixed’ schedules for HVAC systems are not sufficient and cannot adjust based on the dynamic changes in building environments. This study proposes a vision-based occupancy and equipment usage detection method based on deep learning for demand-driven control systems. A model based on region-based convolutional neural network (R-CNN) was developed, trained and deployed to a camera for real-time detection of occupancy activities and equipment usage. Experiments tests within a case study office room suggested an overall accuracy of 97.32% and 80.80%. In order to predict the energy savings that can be attained using the proposed approach, the case study building was simulated. The simulation results revealed that the heat gains could be over or under predicted when using static or fixed profiles. Based on the set conditions, the equipment and occupancy gains were 65.75% and 32.74% lower when using the deep learning approach. Overall, the study showed the capabilities of the proposed approach in detecting and recognising multiple occupants’ activities and equipment usage and providing an alternative to estimate the internal heat emissions.

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What are the Impacts on the HVAC System when it Provides Frequency Regulation? – A Comprehensive Case Study with a Medium Office Building

Energy and Buildings ◽

10.1016/j.enbuild.2021.110995 ◽

2021 ◽

pp. 110995

Author(s):

Xing Lu ◽

Veronica Adetola ◽

Zheng O'Neill

Keyword(s):

Office Building ◽

Frequency Regulation ◽

Hvac System

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Increased Plant Quality, Greenhouse Productivity and Energy Efficiency with Broad-Spectrum LED Systems: A Case Study for Thyme (Thymus vulgaris L.)

Plants ◽

10.3390/plants10050960 ◽

2021 ◽

Vol 10 (5) ◽

pp. 960

Author(s):

Jenny Manuela Tabbert ◽

Hartwig Schulz ◽

Andrea Krähmer

Keyword(s):

Broad Spectrum ◽

Energy Savings ◽

Light Emitting Diode ◽

Thymus Vulgaris ◽

Light Spectrum ◽

Light Emitting ◽

Biomass Yields ◽

Lighting Systems

A light-emitting diode (LED) system covering plant-receptive wavebands from ultraviolet to far-red radiation (360 to 760 nm, “white” light spectrum) was investigated for greenhouse productions of Thymus vulgaris L. Biomass yields and amounts of terpenoids were examined, and the lights’ productivity and electrical efficiency were determined. All results were compared to two conventionally used light fixture types (high-pressure sodium lamps (HPS) and fluorescent lights (FL)) under naturally low irradiation conditions during fall and winter in Berlin, Germany. Under LED, development of Thymus vulgaris L. was highly accelerated resulting in distinct fresh yield increases per square meter by 43% and 82.4% compared to HPS and FL, respectively. Dry yields per square meter also increased by 43.1% and 88.6% under LED compared to the HPS and FL lighting systems. While composition of terpenoids remained unaffected, their quantity per gram of leaf dry matter significantly increased under LED and HPS as compared to FL. Further, the power consumption calculations revealed energy savings of 31.3% and 20.1% for LED and FL, respectively, compared to HPS. In conclusion, the implementation of a broad-spectrum LED system has tremendous potential for increasing quantity and quality of Thymus vulgaris L. during naturally insufficient light conditions while significantly reducing energy consumption.

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