• KIEAE Journal
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• v.15 no.4
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• pp.69-76
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• 2015

Purpose: This study is to investigate the effects of facade insulation and window remodeling of an existing old middle school building on the reduction of energy consumption. Method: To analyze energy performance of building, using DesignBuilder v3.4, building energy simulation tool based EnergyPlus engine. Energy consumption and problem of target building was analyzed based on data and survey. Based on building energy simulations it analyzed the variation of energy demand for the building according to U-value of wall, glazing properties and external shading devices. Result: When insulation of building was reinforced, cooling and heating load was decreased. Glazing properties that minimize cooling and heating energy consumption were analyzed. In conclusion, it is important to choose SHGC and U-value of window fit in characteristic of target building. Setting external blind for cooling load decreases 5%.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.4
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• pp.137-144
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• 2016

Commercial buildings account for a significant proportion of the total building energy use in Korea, and cooling energy, in turn, accounts for the largest proportion of total energy consumption in commercial buildings. Under this circumstance, chiller staging is considered to be a reasonable and practical solution for cooling energy saving. In this study, the part-load ratio and the operating characteristics of a vapor compression chiller were analysed within an office building. In addition, energy consumption among different chiller staging schemes was comparatively analysed. As a result, significant proportions of total operating hours, cooling load and energy consumption turned out to be in the part load ratio range from 0% through 50%, and thus energy consumption was significantly affected by the chiller COP at low part-load conditions, indicating that the chiller operation at the part-load is an important factor in commercial buildings. In addition, utilizing a sequential chiller staging scheme can reduce the annual cooling energy usage by more than 10.3% compared to operating a single chiller.

• Asian Journal of Business Environment
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• v.14 no.3
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• pp.23-35
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• 2024

Purpose: The study focuses on the impact of Foreign Direct Investment (FDI), trade openness, and energy consumption on carbon dioxide emissions in the Ivory Coast. It aims to quantitatively evaluate the effects of FDI, energy consumption, and trade openness on CO₂ emissions in Ivory Coast. Research design, data, and methodology: The research uses an econometric framework and the Autoregressive Distributed Lag (ARDL) model to analyze time-series data from 1980 to 2021 between these factors. Results: The analysis revealed that FDI significantly impacts the carbon dioxide emissions, FDI showed a negative impact on carbon emissions in the long-run equilibrium term. Also, energy consumption impacted CO₂ emissions in the long-run equilibrium term. Conclusion: To mitigate the upsurge of CO₂ emissions in the Ivorian context, concrete policy, including enactment and adherence to strict environmental regulations, adoption and prioritization of eco-friendly products and technologies, and investment in renewable energy infrastructure are recommended. The study contributes to the global discussion on sustainable development by offering a model for similar assessments in other emerging nations facing simultaneous economic growth and environmental conservation challenges.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.198-199
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• 2015

Construction equipment is a major energy consumption source in construction projects. If 10% reduction of the diesel fuel usage is achieved in the construction industry, it may reduce 5% of the total energy usage. Energy saving operation is a major issue in equipment-intensive operations (e.g., earthmoving or paving operations). Identifying optimal equipment fleet is important measure to achieve low-energy consumption in those operations. This study presents a system which finds an optimal equipment fleet by computing the low-energy performance of earthmoving operations. It establishes construction operation model and compares numerous combinations using alternative equipment allocation plans. It implements sensitivity analysis that facilitates searching the lowest energy consumption equipment fleet by enumerating all cases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5357-5381
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• 2018

Cloud computing offers a wide range of on-demand resources over the internet. Utility-based resource allocation in cloud data centers significantly increases the number of cloud users. Heavy usage of cloud data center encounters many problems such as sacrificing system performance, increasing operational cost and high-energy consumption. Therefore, the result of the system damages the environment extremely due to heavy carbon (CO2) emission. However, dynamic allocation of energy-efficient resources in cloud data centers overcomes these problems. In this paper, we have proposed Energy and Service Level Agreement (SLA) Aware Resource Allocation Heuristic Algorithms. These algorithms are essential for reducing power consumption and SLA violation without diminishing the performance and Quality-of-Service (QoS) in cloud data centers. Our proposed model is organized as follows: a) SLA violation detection model is used to prevent Virtual Machines (VMs) from overloaded and underloaded host usage; b) for reducing power consumption of VMs, we have introduced Enhanced minPower and maxUtilization (EMPMU) VM migration policy; and c) efficient utilization of cloud resources and VM placement are achieved using SLA-aware Modified Best Fit Decreasing (MBFD) algorithm. We have validated our test results using CloudSim toolkit 3.0.3. Finally, experimental results have shown better resource utilization, reduced energy consumption and SLA violation in heterogeneous dynamic cloud environment.

• Journal of Energy Engineering
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• v.5 no.1
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• pp.1-7
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• 1996

Coal consumption in Asia is projected to increase by about 1.3 billion tons over the 1993-2010 period. The expansion in coal consumption for electricity generation is the dominant factor in the large increase in coal consumption. Without effective control measures, the projected increase in coal consumption will have a serious impact on environmental effects of increased coal use in Asia. Thus, the introduction of appropriate CCTs is considered essential to achieving the twin goals of expanded use of coal decreased environmental impacts.

• Journal of Korean Society of Transportation
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• v.28 no.2
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• pp.161-169
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• 2010

The amount of energy consumed by a transportation system in a city is influenced not just by a transportation system itself but also by city's spatial character. Yet there have been very limited studies on this subject. This study investigates the factors that influence the energy consumption by a transportation system and city's spatial character. The model of an urban area confined within a definite boundary is assumed in order to develop the relationships between the energy consumption and the transportation system. Various assumptions on the character of a city and activities are made. An equation for computation of the energy consumption is derived with such factors as modal split, densities of residents and workers, as well as technological development. Using the equation, sensitivity analyses are performed in order to identify the relationships between energy consumption and influencing factors. It is found that the modal split is the most powerful factor that determines the energy consumption by the transportation system. Yet it is also found that the densities of residents and workers and the technological factors are very important in determining the amount of energy consumption as well.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.2
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• pp.38-46
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• 2012

This paper discusses the energy consumption for a mid-size electric vehicle(EV) under various conditions. In order to analyze which driving style is more efficient in terms of the system of the EV, we develop the electric vehicle model and apply several types of speed profiles such as different steady speeds, acceleration/deceleration, and a real world driving cycle including the elevation profile obtained from a GPS device. The results show that the energy consumption of the EV is affected by the operating efficiency of components when driving at low speed, while it depends on required power at wheels when driving at high speed. Also this paper investigates the effect of the elevation of a road and the rate of electrical braking on the energy consumption as well as the fuel economy of a conventional vehicle model under the same conditions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.5
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• pp.777-781
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• 2012

In this paper, an electrical power simulation program was developed to predict the energy consumption of the electrical railway propulsion system, which considered the actual operating conditions of the electric railway vehicles. The developed program was designed to predictable the energy consumption during a virtual driving in the actual route of the virtual railway vehicles equipped with a propulsion system consisting of power conversion equipments and traction motors. In addition, the accuracy verification of the electrical power simulation program for a propulsion system was performed by using a real power consumption data, which was measured during the driving of the railway vehicles in the Gyeongui Line. In conclusion, the electrical power simulation program for a propulsion system was validated throughout a comparative investigation between the simulated values and the experimental values and the energy consumption characteristics of electric railway vehicles on the existing route or the new route will be possible to predict throughout the virtual simulation considering the driving conditions of the electric railway vehicles.