An integrated performance based solution approach for commercial buildings energy modeling and energy savings: Case study of a retail building in Bangladesh

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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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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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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Stochastic control for risk under deregulated electricity market — a case study using a new formulation

Canadian Journal of Civil Engineering ◽

10.1139/l05-030 ◽

2005 ◽

Vol 32 (4) ◽

pp. 719-725 ◽

Cited By ~ 12

Author(s):

Joyce Li Zhang ◽

K Ponnambalam

Keyword(s):

Electricity Market ◽

Explicit Method ◽

State Variables ◽

Risk Minimization ◽

Solution Approach ◽

Second Moments ◽

Deregulated Electricity Market ◽

New Formulation ◽

Dual Dynamic Programming

This paper describes the implementation of a new solution approach — Fletcher-Ponnambalam model (FP) — for risk management in hydropower system under deregulated electricity market. The FP model is an explicit method developed for the first and second moments of the storage state distributions in terms of moments of the inflow distributions. This method provides statistical information on the nature of random behaviour of the system state variables without any discretization and hence suitable for multi-reservoir problems. Also avoiding a scenario-based optimization makes it computationally inexpensive, as there is little growth to the size of the original problem. In this paper, the price uncertainty was introduced into the FP model in addition to the inflow uncertainty. Lake Nipigon reservoir system is chosen as the case study and FP results are compared with the stochastic dual dynamic programming (SDDP). Our studies indicate that the method could achieve optimum operations, considering risk minimization as one of the objectives in optimization.Key words: reservoir operations, explicit method, uncertainty, stochastic programming, risk.

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BIM Energy Modeling: Case Study of a Teaching Module for Sustainable Design and Construction Courses

Journal of Professional Issues in Engineering Education and Practice ◽

10.1061/(asce)ei.1943-5541.0000230 ◽

2015 ◽

Vol 141 (2) ◽

Cited By ~ 12

Author(s):

Anderson M. Lewis ◽

Rodolfo Valdes-Vasquez ◽

Caroline Clevenger ◽

Tripp Shealy

Keyword(s):

Sustainable Design ◽

Energy Modeling ◽

Teaching Module ◽

Design And Construction

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Integrating GIS-Based Point of Interest and Community Boundary Datasets for Urban Building Energy Modeling

Energies ◽

10.3390/en14041049 ◽

2021 ◽

Vol 14 (4) ◽

pp. 1049

Author(s):

Zhang Deng ◽

Yixing Chen ◽

Xiao Pan ◽

Zhiwen Peng ◽

Jingjing Yang

Keyword(s):

Large Scale ◽

Residential Buildings ◽

Building Energy ◽

Energy Performance ◽

Energy Modeling ◽

Office Buildings ◽

Building Energy Modeling ◽

Downtown Area ◽

Point Of Interest

Urban building energy modeling (UBEM) is arousing interest in building energy modeling, which requires a large building dataset as an input. Building use is a critical parameter to infer archetype buildings for UBEM. This paper presented a case study to determine building use for city-scale buildings by integrating the Geographic Information System (GIS) based point-of-interest (POI) and community boundary datasets. A total of 68,966 building footprints, 281,767 POI data, and 3367 community boundaries were collected for Changsha, China. The primary building use was determined when a building was inside a community boundary (i.e., hospital or residential boundary) or the building contained POI data with main attributes (i.e., hotel or office building). Clustering analysis was used to divide buildings into sub-types for better energy performance evaluation. The method successfully identified building uses for 47,428 buildings among 68,966 building footprints, including 34,401 residential buildings, 1039 office buildings, 141 shopping malls, and 932 hotels. A validation process was carried out for 7895 buildings in the downtown area, which showed an overall accuracy rate of 86%. A UBEM case study for 243 office buildings in the downtown area was developed with the information identified from the POI and community boundary datasets. The proposed building use determination method can be easily applied to other cities. We will integrate the historical aerial imagery to determine the year of construction for a large scale of buildings in the future.

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Undersaturated Hydrocarbon Reservoir Waterflooding: A simulation Approach to Performance Assessment

10.2118/207148-ms ◽

2021 ◽

Author(s):

Adekunle Tirimisiyu Adeniyi ◽

Miracle Imwonsa Osatemple ◽

Abdulwahab Giwa

Keyword(s):

Oil Recovery ◽

Net Present Value ◽

Oil Production ◽

Base Case ◽

Present Value ◽

Sweep Efficiency ◽

Recovery Method ◽

Solution Approach ◽

Hydrocarbon Reservoir

Abstract There are a good numbers of brown hydrocarbon reservoirs, with a substantial amount of bypassed oil. These reservoirs are said to be brown, because a huge chunk of its recoverable oil have been produced. Since a significant number of prominent oil fields are matured and the number of new discoveries is declining, it is imperative to assess performances of waterflooding in such reservoirs; taking an undersaturated reservoir as a case study. It should be recalled that Waterflooding is widely accepted and used as a means of secondary oil recovery method, sometimes after depletion of primary energy sources. The effects of permeability distribution on flood performances is of concerns in this study. The presence of high permeability streaks could lead to an early water breakthrough at the producers, thus reducing the sweep efficiency in the field. A solution approach adopted in this study was reserve water injection. A reverse approach because, a producing well is converted to water injector while water injector well is converted to oil producing well. This optimization method was applied to a waterflood process carried out on a reservoir field developed by a two - spot recovery design in the Niger Delta area of Nigeria that is being used as a case study. Simulation runs were carried out with a commercial reservoir oil simulator. The result showed an increase in oil production with a significant reduction in water-cut. The Net Present Value, NPV, of the project was re-evaluated with present oil production. The results of the waterflood optimization revealed that an increase in the net present value of up to 20% and an increase in cumulative production of up to 27% from the base case was achieved. The cost of produced water treatment for re-injection and rated higher water pump had little impact on the overall project economy. Therefore, it can conclude that changes in well status in wells status in an heterogenous hydrocarbon reservoir will increase oil production.

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