• Design & Manufacturing
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• v.16 no.2
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• pp.20-25
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• 2022

In line with the rapid economic growth of many countries, fossil fuel energy sources are also rapidly depleting. Therefore, the price is also rising rapidly, so it is necessary to develop new and renewable energy sources such as hydropower, geothermal power, nuclear power, wind power and solar energy to replace fossil fuel energy in the future. In this study, development of rotating concentrator module system, development of rotating module control control system, development of lamp and charge control controller, configuration and prototype production of rotating concentrating solar LED street light system, efficiency of rotating concentrating solar LED street light, and power production. The research was conducted in the order of evaluation of comprehensive performance tests such as consumption and consumption. As a result, the developed high-efficiency rotation-concentrating hybrid solar LED street light module system has a 50% higher light-gathering efficiency than existing products by tracing sunlight by self-developing a rotation-collecting module on existing solar LED street lamps according to the characteristics of Korea's topography. and the power generation was improved by more than 40%.

• Journal of Power System Engineering
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• v.19 no.2
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• pp.78-83
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• 2015

In Korea, multi-housing in one of the most common types of residential space due to its easy management and convenience. In particular, south-facing plate-type(一) multi-housing has attracted a great deal of public interest because it consumes less energy compared with other types of multi-housing, making it advantageous from an energy-saving perspective. Although there have been many studies on the annual energy consumption of multi-housing in relation to building shape and area of window, there have not been sufficient research on the annual energy consumption of multi-housing in relation to individual units of the multi-housing. The purpose of this study is to propose a strategy for reducing energy consumption in plate-type(一) multi-housing, taking the units with the lowest energy consumption as the standard. The result, Standard Models's energy load was as 4000 ~ 5600kWh, and Passive Houses's energy load was less than Stand Models at the 1600kWh.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.4
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• pp.226-239
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• 2013

A number of systems have several on-chip memories with cache memory being one of them. Conventional cache memory consists of SRAM but the ratio of static energy to the total energy of the memory architecture becomes larger as the leakage power of traditional SRAM increases. Spin-Torque Transfer RAM (STT-RAM), which is a variety of Non-Volatile Memory (NVM), has many advantages over SRAM, such as high density, low leakage power, and non-volatility, but it consumes too much writing energy. This study evaluated a wide range of energy consumptions of a two-level cache using NVM partially on a mobile processor. Through a number of experimental evaluations, it was confirmed that the use of NVM partially in the two-level cache effectively reduces energy consumption significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• International journal of advanced smart convergence
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• v.4 no.1
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• pp.45-53
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• 2015

This paper is proposed mathematical load modelling based on system identification approach of energy consumption of residential air conditioning. Due to air conditioning is one of the significant equipment which consumes high energy and cause the peak load of power system especially in the summer time. The demand response is one of the solutions to decrease the load consumption and cutting peak load to avoid the reservation of power supply from power plant. In order to operate this solution, mathematical modelling of air conditioning which explains the behaviour is essential tool. The four type of linear model is selected for explanation the behaviour of this system. In order to obtain model, the experimental setup are performed by collecting input and output data every minute of 9,385 BTU/h air-conditioning split type with $25^{\circ}C$ thermostat setting of one sample house. The input data are composed of solar radiation ($W/m^2$) and ambient temperature ($^{\circ}C$). The output data are power and energy consumption of air conditioning. Both data are divided into two groups follow as training data and validation data for getting the exact model. The model is also verified with the other similar type of air condition by feed solar radiation and ambient temperature input data and compare the output energy consumption data. The best model in term of accuracy and model order is output error model with 70.78% accuracy and $17^{th}$ order. The model order reduction technique is used to reduce order of model to seven order for less complexity, then Kalman filtering technique is applied for remove white Gaussian noise for improve accuracy of model to be 72.66%. The obtained model can be also used for electrical load forecasting and designs the optimal size of renewable energy such photovoltaic system for supply the air conditioning.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.84-93
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• 2018

In this paper, we propose an Elman recurrent neural network to predict and analyze a time series of power energy consumption. To this end, we consider the volatility of the time series and apply the sample variance and the detrended fluctuation analyses to the volatilities. We demonstrate that there exists a correlation in the time series of the volatilities, which suggests that the power consumption time series contain a non-negligible amount of the non-linear correlation. Based on this finding, we adopt the Elman recurrent neural network as the model for the prediction of the power consumption. As the simplest form of the recurrent network, the Elman network is designed to learn sequential or time-varying pattern and could predict learned series of values. The Elman network has a layer of "context units" in addition to a standard feedforward network. By adjusting two parameters in the model and performing the cross validation, we demonstrated that the proposed model predicts the power consumption with the relative errors and the average errors in the range of 2%~5% and 3kWh~8kWh, respectively. To further confirm the experimental results, we performed two types of the cross validations designed for the time series data. We also support the validity of the model by analyzing the multi-step forecasting. We found that the prediction errors tend to be saturated although they increase as the prediction time step increases. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric and the gas energies.

• KIEAE Journal
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• v.16 no.5
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• pp.47-55
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• 2016

Purpose: As the energy consumed by buildings increases, there is a growing need for studies and technology development to address this issue. One of the solutions to excessive energy use by buildings is the light-shelf, which is a natural lighting system enabling efficient reduction in light energy, and research in this area has been intensive. However, most of the studies about the light-shelf are limited to the light environment, and thus the application of their findings to an actual environment in the form of a design may be problematic. Therefore, the purpose of the present study is to provide fundamental data for light-shelf design by carrying out a light-shelf performance evaluation on the basis of the light environment and the heating and cooling environment. Method: In the present study, a testbed was established to conduct a light-shelf performance evaluation by measuring the electric power consumption of lighting and heating and cooling devices depending on the existence of a light-shelf and its angle. Result: The findings of the present study are as follows: 1) With respect to the uniformity of the indoor light environment amenity, the optimum angle of a light-shelf was found to be $30^{\circ}$ for the summer solstice and the winter solstice. 2) With respect to the reduction of electric power consumption by indoor lighting devices, the optimum light-shelf angle at the summer solstice is $30^{\circ}$, at which time electric power consumption may be reduced by 10.2% in comparison with when no light-shelf is applied. However, at the winter solstice, a light-shelf may increase the energy consumption for lighting in comparison with when no light-shelf is applied, and this should be taken into account in the design of a light-shelf. 3) In terms of reducing the electric power consumption of heating and cooling devices, the optimum angle of a light-shelf was found to be $30^{\circ}$ for the summer solstice, while a light-shelf is inappropriate for the winter solstice since a light-shelf creates shade and thus increases the heating energy consumption. 4) To summarize the findings above, the optimum angle of a light-shelf is $30^{\circ}$ for the summer solstice, but the installation of a light-shelf may in some circumstances increase the energy consumed by lighting devices as well as by heating and cooling devices. Therefore, more studies and technology development may need to be performed to solve the problem of increased energy consumption at the winter solstice.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.12
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• pp.1078-1085
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• 2011

In this paper, we analyze the relationship between energy per bit and the data rate with the variation of the system bandwidth. A existing power model is mathematical model to express power consumption of each device. In this paper, we have to investigate the system level energy model for the RF front-end of a wireless transceiver. Also, the effects of the signal bandwidth, PAR, date rate, modulation level, transmission distance, specific attenuation of frequency band, and the signal center frequency on the RF front-end energy consumption and system capacity are considered. Eventually, we analyze the relationship between energy per bit and the data rate with the variation of the system bandwidth so that we simulate the minimum energy per bit in the several Gbps data rate using Shannon capacity theory.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.137.2-137.2
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• 2010

With current real economic growth of more than 10% per year, the Chinese energy consumption is rapidly increasing. Coal supply consists of the vast majority of China's total energy consumption requirements in 2008. China, the largest energy consumer, is expected to be heavily dependent on coal for future power generation, too (IEA,2009). A growing concern on global warming, on the other hand, drives Chinese government to declare her commitment to the reduction of CO2 emission by 2020. In this paper, China's energy market is examined for the current and future primary energy mix. Coal is found to be the biggest part accounting for 68.7% of total primary energy consumption while coal-fired power accounts for over 80% of the total power generation. The importance of Clean Coal Technology is being discussed based on the findings of the importance of coal in China's economy and its sustainable development. Among the technologies involved, a brief investigation of IGCC(Integrated Gasification Combined Cycle) technology with a review on current IGCC projects in China are provided from the perspective of environmental benefits. Studies on regional Chinese power market is also conducted. It is found that the regulated power tariff in electricity system makes the power suppliers suffer from financial loss and changes in the electricity price system is under serious consideration by Chinese government. Even though Chinese power market system causes difficulties of commercialization for IGCC technology, the potential benefits will be high due to China's huge requirements of power generating capacity and its heavy reliance on coal if the electricity price system can be changed smoothly.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.239-242
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• 2005

A high speed address recovery technique for AC plasma display Panel(PDP) is proposed. By removing the GND switching operation, the recovery speed can be increased and switching loss due to GND switch also becomes to be reduced. The proposed method is able to perform load-adaptive operation by controlling the voltage level of energy recovery capacitor, which prevents increasing inefficient power consumption caused by circuit loss during recovery operation. Thus, the technique shows the minimum address power consumption according to various displayed images, different from Prior methods operating in fixed mode regardless of images. Test results with 50" HD single-scan PDP(resolution = 1366$\times$768) show that less than 350ns of recovery time is successfully accomplished and about 54% of the maximum power consumption can be reduced, tracing minimum power consumption curves.