• Journal of Urban Science
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• v.11 no.1
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• pp.15-20
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• 2022

The issue of hotel energy use is growing more significant as the hotel industry expands. It is important to take into account the electrical installation and space-specific features in a room unit in order to comprehend the energy consumption of a hotel guestroom. In light of this, this study aimed to analyze standby power for enhancing the energy efficiency of a hotel guestroom during check-out status. This study was conducted in three steps: (i) data collection; (ii) analysis of energy consumption patterns; and (iii) analysis of energy efficiency improvement plan. The main findings of this study can be summarized as follows. First, 32.24% of energy was used in fan coil unit) during check-out status. Second, a hotel guestroom had a 4.30% energy saving potential, based on energy consumption patterns during check-out status. This study can contribute to support hotel management to operate guestrooms differently by helping them identify patterns in energy use and realize potential savings.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.426-432
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• 2022

HVAC systems play a critical role in reducing energy consumption in buildings. Integrating occupants' thermal comfort evaluation into HVAC control strategies is believed to reduce building energy consumption while minimizing their thermal discomfort. Advanced technologies, such as visual sensors and deep learning, enable the recognition of occupants' discomfort-related actions, thus making it possible to estimate their thermal discomfort. Unfortunately, it remains unclear how accurate a deep learning-based classifier is to recognize occupants' discomfort-related actions in a working environment. Therefore, this research evaluates the classification performance of occupants' discomfort-related actions while sitting at a computer desk. To achieve this objective, this study collected RGB video data on nine college students' cold discomfort-related actions and then trained a deep learning-based classifier using the collected data. The classification results are threefold. First, the trained classifier has an average accuracy of 93.9% for classifying six cold discomfort-related actions. Second, each discomfort-related action is recognized with more than 85% accuracy. Third, classification errors are mostly observed among similar discomfort-related actions. These results indicate that using human action data will enable facility managers to estimate occupants' thermal discomfort and, in turn, adjust the operational settings of HVAC systems to improve the energy efficiency of buildings in conjunction with their thermal comfort levels.

• Proceedings of the SAREK Conference
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• 2005.11a
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• pp.223-228
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• 2005

This study develops an optimization program to use optimum design of building HVAC system reducing building energy use and cost. Doe20pt developed is an interface program between DOE2 and GenOpt to perform the optimization procedure more easily. The optimum results can be used to estimate the economical efficiency concerning the building management.

• Journal of Energy Engineering
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• v.28 no.1
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• pp.37-44
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• 2019

Domestic buildings account for 25% of national greenhouse gas emissions and 20% of energy consumption, so energy efficiency improvement of buildings is recognized as the main target of national energy demand management. To improve the energy efficiency of the building, policies are implemented by preparing "zero-energy building national roadmaps" and enhancing the efficiency of national energy demand management through early activation as a result of expansion of the mandatory zero-energy building. Also, there is a growing need to verify the performance of energy savings after the construction is completed. Therefore, methods for evaluating energy performance of buildings should be suggested. This paper aims to develop and present methods for verifying energy performance of Zero Energy School, which can be applied internationally, by visiting domestic schools on-site at the same time as international standards and guidance analysis.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.2
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• pp.11-17
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• 2019

As interest in the efficiency use of energy has been recently rising, studies have been performed in utilizing various types of eco-friendly green energy and natural energy. Especially there has been rapidly increase in the fields using ESS (Energy Storage System), which is the technology for storing the energy from nature. The application fields of ESS is continuously growing and expanding to various types of technologies. However, in recent years there have been continuing problems with the safety of ESS. And related researches are going on. In this paper, we has proposed a system structure to utilize more secure ESS and has monitored the system status of ESS in real time by using smart phone app. This paper has also proposed a new method to configure secure ESS by implementing GUI (Graphical User Interface) to control the system. And then explain experimental results to investigate the efficiency of the proposed ESS.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.188-193
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• 2022

The energy efficiency of memory systems is an important task in designing future computer systems as memory capacity continues to increase to accommodate the growing big data. In this article, we present an energy-efficient last-level cache management policy for future mobile systems. The proposed policy makes use of low-power PCM (phase-change memory) as the main memory medium, and reduces the amount of data written to PCM, thereby saving memory energy consumptions. To do so, the policy keeps track of the modified cache lines within each cache block, and replaces the last-level cache block that incurs the smallest PCM writing upon cache replacement requests. Also, the policy considers the access bit of cache blocks along with the cache line modifications in order not to degrade the cache hit ratio. Simulation experiments using SPEC benchmarks show that the proposed policy reduces the power consumption of PCM memory by 22.7% on average without degrading performances.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.12
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• pp.1627-1636
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• 2014

In real-time electricity price environment, the energy management system can provide the significant advantage to the residential, commercial and industrial customers since it can reduce the electricity charge by controlling the load operation effectively in response to time-varying price. However, the earlier studies for load management mainly focus on the residential and commercial customers except for the industrial customers because most of load operations in industrial sector are intimately related with production schedule. So, it is possible that the inappropriate control of loads in industrial sector causes huge economic loss. In this paper, therefore, we propose load control algorithm for factory energy management system(F-EMS) to achieve not only minimizing the electricity charges but also maintaining production efficiency by considering characteristics of load operation and production schedule. Considering characteristics of load operation and production schedule, the proposed load control algorithm can reflect the various characteristics of specific industrial customer and control their loads within the range that the production efficiency is maintained. Simulation results show that the proposed load control algorithm for F-EMS leads to significant reduction in the electricity charges and peak power in industrial sector.

• Asia Pacific Journal of Business Review
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• v.5 no.2
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• pp.19-44
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• 2021

Sub Saharan Africa (SSA) is receiving increased investments in the energy sector under the belt and road initiative (BRI) project since its inception in 2013. SSA has a worse energy efficiency ratio coupled with deficient electricity access, through analysis showed varied impacts on the SSA countries due to the BRI initiative. This study dilves into the influencing factors for Energy Efficiency (EE) in 38 SSA countries, applying the probit and logit approach for 2000-2018. The Multiple-regression model shows significant results of some variables such as foreign direct investment, gross domestic product, and port infrastructure quality being significant on EE under BRI initiative countries. However, the logit and probit models produce similar results and the marginal effect for the entire variable, except energy imports that do not likely impact EE. Furthermore, the interaction of quality of port infrastructure and foreign direct investment variables produces significant results, highlighting the increased investments SSA receives under the BRI initiative in the energy and transport sectors. The model Percent correctly predicted (PCP) value was about 84%, indicating it correctly classified the variables and about 16% not classified. The study recommends EE performance standards should be incorporated on energy projects in SSA to ensure that these projects are energy efficient and decouple SSA's energy demand from economic growth. The research proffers suggestions for policy regarding the BRI initiative in SSA and the implications on sustainable energy and building a community with a shared future.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.11-25
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• 2024

The proliferation of IoT devices has presented an unprecedented challenge in managing device identities securely and efficiently. In this paper, we introduce an innovative Hybrid Blockchain-Based Approach for IoT Identity Management that prioritizes both security and efficiency. Our hybrid solution, strategically combines the advantages of direct and indirect connections, yielding exceptional performance. This approach delivers reduced latency, optimized network utilization, and energy efficiency by leveraging local cluster interactions for routine tasks while resorting to indirect blockchain connections for critical processes. This paper presents a comprehensive solution to the complex challenges associated with IoT identity management. Our Hybrid Blockchain-Based Approach sets a new benchmark for secure and efficient identity management within IoT ecosystems, arising from the synergy between direct and indirect connections. This serves as a foundational framework for future endeavors, including optimization strategies, scalability enhancements, and the integration of advanced encryption methodologies. In conclusion, this paper underscores the importance of tailored strategies in shaping the future of IoT identity management through innovative blockchain integration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.819-837
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• 2014

Data centers, which implement cloud service, have been faced up with quick growth of energy consumption and low efficiency of energy. 60GHz wireless communication technology, as a new option to data centers, can provide feasible approach to alleviate the problems. Aiming at energy optimization in 60GHz wireless data centers (WDCs), we investigate virtualization technology to assign virtual resources to minimum number of servers, and turn off other servers or adjust them to the state of low power. By comprehensive analysis of wireless data centers, we model virtual network and physical network in WDCs firstly, and propose Virtual Resource Mapping Packing Algorithm (VRMPA) to solve energy management problems. According to VRMPA, we adopt packing algorithm and sort physical resource only once, which improves efficiency of virtual resource allocation. Simulation results show that, under the condition of guaranteeing network load, VPMPA algorithm can achieve better virtual request acceptance rate and higher utilization rate of energy consumption.